kittycad.models.modeling_cmd

Classes

OptionCameraDragEnd(**data)	Camera drag ended
OptionCameraDragMove(**data)	Camera drag continued.
OptionCameraDragStart(**data)	Camera drag started.
OptionCenterOfMass(**data)	Get the center of mass of entities in the scene or the default scene.
OptionClosePath(**data)	Closes a path, converting it to a 2D solid.
OptionCurveGetControlPoints(**data)	Get control points of the given curve.
OptionCurveGetEndPoints(**data)	Find the start and end of a curve.
OptionCurveGetType(**data)	Get type of the given curve.
OptionCurveSetConstraint(**data)	Get the plane for sketch mode.
OptionDefaultCameraCenterToScene(**data)	Updates the camera to center to the center of the current scene's bounds
OptionDefaultCameraCenterToSelection(**data)	Updates the camera to center to the center of the current selection (or the origin if nothing is selected)
OptionDefaultCameraFocusOn(**data)	Focus the default camera upon an object in the scene.
OptionDefaultCameraGetSettings(**data)	Gets the default camera's camera settings
OptionDefaultCameraLookAt(**data)	Change what the default camera is looking at.
OptionDefaultCameraPerspectiveSettings(**data)	Change what the default camera is looking at.
OptionDefaultCameraSetOrthographic(**data)	Use orthographic projection.
OptionDefaultCameraSetPerspective(**data)	Use perspective projection.
OptionDefaultCameraZoom(**data)	Adjust zoom of the default camera.
OptionDensity(**data)	Get the density of entities in the scene or the default scene.
OptionDisableDryRun(**data)	Sets whether or not changes to the scene or its objects will be done as a "dry run" In a dry run, successful commands won't actually change the model.
OptionEdgeLinesVisible(**data)	Changes visibility of scene-wide edge lines on brep solids
OptionEnableDryRun(**data)	Sets whether or not changes to the scene or its objects will be done as a "dry run" In a dry run, successful commands won't actually change the model.
OptionEnableSketchMode(**data)	Sketch on some entity (e.g. a plane, a face).
OptionEngineUtilEvaluatePath(**data)	Evaluates the position of a path in one shot (engine utility for kcl executor)
OptionEntityCircularPattern(**data)	Create a circular pattern using this entity.
OptionEntityFade(**data)	Fade entity in or out.
OptionEntityGetAllChildUuids(**data)	What are all UUIDs of this entity's children?
OptionEntityGetChildUuid(**data)	What is the UUID of this entity's n-th child?
OptionEntityGetDistance(**data)	What is the distance between these two entities?
OptionEntityGetNumChildren(**data)	How many children does the entity have?
OptionEntityGetParentId(**data)	What is this entity's parent?
OptionEntityGetSketchPaths(**data)	What are all UUIDs of all the paths sketched on top of this entity?
OptionEntityLinearPattern(**data)	Create a linear pattern using this entity.
OptionEntityLinearPatternTransform(**data)	Create a pattern using this entity by specifying the transform for each desired repetition.
OptionEntityMakeHelix(**data)	Create a helix using the input cylinder and other specified parameters.
OptionEntityMirror(**data)	Mirror the input entities over the specified axis.
OptionEntityMirrorAcrossEdge(**data)	Mirror the input entities over the specified edge.
OptionEntitySetOpacity(**data)	Set opacity of the entity.
OptionExport(**data)	Export the scene to a file.
OptionExtendPath(**data)	Extend a path by adding a new segment which starts at the path's "pen".
OptionExtrude(**data)	Command for extruding a solid 2d.
OptionFaceGetCenter(**data)	Obtains the surface "center of mass"
OptionFaceGetGradient(**data)	Determines the gradient (dFdu, dFdv) + normal vector on a brep face evaluated by parameters u,v
OptionFaceGetPosition(**data)	Determines a position on a brep face evaluated by parameters u,v
OptionFaceIsPlanar(**data)	Determines whether a brep face is planar and returns its surface-local planar axes if so
OptionGetEntityType(**data)	What type of entity is this?
OptionGetNumObjects(**data)	Get the number of objects in the scene
OptionGetSketchModePlane(**data)	Get the plane for sketch mode.
OptionHandleMouseDragEnd(**data)	Stop dragging the mouse.
OptionHandleMouseDragMove(**data)	Continue dragging the mouse.
OptionHandleMouseDragStart(**data)	Start dragging the mouse.
OptionHighlightSetEntities(**data)	Changes the current highlighted entity to these entities.
OptionHighlightSetEntity(**data)	Changes the current highlighted entity to whichever one is at the given window coordinate.
OptionImportFiles(**data)	Import files to the current model.
OptionLoft(**data)	Command for lofting sections to create a solid
OptionMakeAxesGizmo(**data)	Add a gizmo showing the axes.
OptionMakeOffsetPath(**data)	Make a new path by offsetting an object by a given distance.
OptionMakePlane(**data)	Make a new plane
OptionMass(**data)	Get the mass of entities in the scene or the default scene.
OptionMouseClick(**data)	Send a mouse click event Updates modified/selected entities.
OptionMouseMove(**data)	Send a mouse move event
OptionMovePathPen(**data)	Move the path's "pen".
OptionNewAnnotation(**data)	Create a new annotation
OptionObjectBringToFront(**data)	Bring an object to the front of the scene
OptionObjectSetMaterialParamsPbr(**data)	Set the material properties of an object
OptionObjectVisible(**data)	Hide or show an object
OptionPathGetCurveUuid(**data)	Obtain curve id by index
OptionPathGetCurveUuidsForVertices(**data)	Obtain curve ids for vertex ids
OptionPathGetInfo(**data)	Query the given path.
OptionPathGetSketchTargetUuid(**data)	Obtain the sketch target id (if the path was drawn in sketchmode) for a path
OptionPathGetVertexUuids(**data)	Obtain vertex ids for a path
OptionPlaneIntersectAndProject(**data)	Utility method.
OptionPlaneSetColor(**data)	Set the color of a plane.
OptionReconfigureStream(**data)	Reconfigure the stream.
OptionRemoveSceneObjects(**data)	Remove scene objects.
OptionRevolve(**data)	Command for revolving a solid 2d.
OptionRevolveAboutEdge(**data)	Command for revolving a solid 2d about a brep edge
OptionSceneClearAll(**data)	Removes all of the Objects in the scene
OptionSelectAdd(**data)	Adds one or more entities (by UUID) to the selection.
OptionSelectClear(**data)	Clear the selection
OptionSelectGet(**data)	Find all IDs of selected entities
OptionSelectRemove(**data)	Removes one or more entities (by UUID) from the selection.
OptionSelectReplace(**data)	Replaces current selection with these entities (by UUID).
OptionSelectWithPoint(**data)	Modifies the selection by simulating a "mouse click" at the given x,y window coordinate Returns ID of whatever was selected.
OptionSendObject(**data)	Send object to front or back.
OptionSetBackgroundColor(**data)	Set the background color of the scene.
OptionSetCurrentToolProperties(**data)	Set the properties of the tool lines for the scene.
OptionSetDefaultSystemProperties(**data)	Set the default system properties used when a specific property isn't set.
OptionSetSceneUnits(**data)	Set the units of the scene.
OptionSetSelectionFilter(**data)	What kind of entities can be selected?
OptionSetSelectionType(**data)	When you select some entity with the current tool, what should happen to the entity?
OptionSetTool(**data)	Set the current tool.
OptionSketchModeDisable(**data)	Disable sketch mode.
OptionSolid2DAddHole(**data)	Add a hole to a Solid2d object before extruding it.
OptionSolid3DFilletEdge(**data)	Fillets the given edge with the specified radius.
OptionSolid3DGetAllEdgeFaces(**data)	Gets all faces which use the given edge.
OptionSolid3DGetAllOppositeEdges(**data)	Gets all edges which are opposite the given edge, across all possible faces.
OptionSolid3DGetCommonEdge(**data)	Gets the shared edge between these two faces if it exists
OptionSolid3DGetExtrusionFaceInfo(**data)	Get a concise description of all of an extrusion's faces.
OptionSolid3DGetNextAdjacentEdge(**data)	Gets the next adjacent edge for the given edge, along the given face.
OptionSolid3DGetOppositeEdge(**data)	Gets the edge opposite the given edge, along the given face.
OptionSolid3DGetPrevAdjacentEdge(**data)	Gets the previous adjacent edge for the given edge, along the given face.
OptionSolid3DShellFace(**data)	Command for shelling a solid3d face
OptionStartPath(**data)	Start a new path.
OptionSurfaceArea(**data)	Get the surface area of entities in the scene or the default scene.
OptionTakeSnapshot(**data)	Take a snapshot of the current view.
OptionUpdateAnnotation(**data)	Update an annotation
OptionViewIsometric(**data)	Fit the view to the scene with an isometric view.
OptionVolume(**data)	Get the volume of entities in the scene or the default scene.
OptionZoomToFit(**data)	Fit the view to the specified object(s).

class kittycad.models.modeling_cmd.OptionCameraDragEnd(**data)

Camera drag ended

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'interaction': <enum 'CameraDragInteractionType'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['camera_drag_end'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionCameraDragEnd'>, 'config': {'title': 'OptionCameraDragEnd'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionCameraDragEnd'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionCameraDragEnd'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionCameraDragEnd:94467866658000', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'interaction': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'CameraDragInteractionType'>, 'members': [CameraDragInteractionType.PAN, CameraDragInteractionType.ROTATE, CameraDragInteractionType.ZOOM], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.camera_drag_interaction_type.CameraDragInteractionType:94467849400224', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'camera_drag_end', 'schema': {'expected': ['camera_drag_end'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionCameraDragEnd', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a284d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc6e130,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "camera_drag_end",                                             },                                             expected_py: None,                                             name: "literal['camera_drag_end']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "interaction": SerField {                         key_py: Py(                             0x00007fa14e7e0670,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb029b2fa0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionCameraDragEnd",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCameraDragEnd", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "interaction",                         lookup_key: Simple {                             key: "interaction",                             py_key: Py(                                 0x00007fa14ae89ab0,                             ),                             path: LookupPath(                                 [                                     S(                                         "interaction",                                         Py(                                             0x00007fa14ae89a70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e7e0670,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb029b2fa0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "rotate": 1,                                             "zoom": 2,                                             "pan": 0,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b38d970,                                         ),                                         Py(                                             0x00007fa14b38d9d0,                                         ),                                         Py(                                             0x00007fa14b38da30,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'pan', 'rotate' or 'zoom'",                                 strict: false,                                 class_repr: "CameraDragInteractionType",                                 name: "str-enum[CameraDragInteractionType]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b0201e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b020210,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc6e130,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "camera_drag_end": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc6e130,                                                 ),                                             ],                                         },                                         expected_repr: "'camera_drag_end'",                                         name: "literal['camera_drag_end']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['camera_drag_end']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14b020240,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14b020270,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ae89940,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ae89940,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCameraDragEnd",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a284d0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionCameraDragEnd",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, interaction: kittycad.models.camera_drag_interaction_type.CameraDragInteractionType, type: Literal['camera_drag_end'] = 'camera_drag_end', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

interaction: CameraDragInteractionType

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'interaction': FieldInfo(annotation=CameraDragInteractionType, required=True), 'type': FieldInfo(annotation=Literal['camera_drag_end'], required=False, default='camera_drag_end'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['camera_drag_end']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionCameraDragMove(**data)

Camera drag continued.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'interaction': <enum 'CameraDragInteractionType'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'sequence': typing.Optional[int], 'type': typing.Literal['camera_drag_move'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionCameraDragMove'>, 'config': {'title': 'OptionCameraDragMove'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionCameraDragMove'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionCameraDragMove'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionCameraDragMove:94467866642944', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'interaction': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'CameraDragInteractionType'>, 'members': [CameraDragInteractionType.PAN, CameraDragInteractionType.ROTATE, CameraDragInteractionType.ZOOM], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.camera_drag_interaction_type.CameraDragInteractionType:94467849400224', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'sequence': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'camera_drag_move', 'schema': {'expected': ['camera_drag_move'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionCameraDragMove', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a24a00,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc6deb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "camera_drag_move",                                             },                                             expected_py: None,                                             name: "literal['camera_drag_move']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "sequence": SerField {                         key_py: Py(                             0x00007fa14fa3b790,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Int(                                                 IntSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                     "interaction": SerField {                         key_py: Py(                             0x00007fa14e7e0670,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb029b2fa0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionCameraDragMove",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCameraDragMove", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "interaction",                         lookup_key: Simple {                             key: "interaction",                             py_key: Py(                                 0x00007fa14ae880b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "interaction",                                         Py(                                             0x00007fa14ae88070,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e7e0670,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb029b2fa0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "zoom": 2,                                             "pan": 0,                                             "rotate": 1,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b38d970,                                         ),                                         Py(                                             0x00007fa14b38d9d0,                                         ),                                         Py(                                             0x00007fa14b38da30,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'pan', 'rotate' or 'zoom'",                                 strict: false,                                 class_repr: "CameraDragInteractionType",                                 name: "str-enum[CameraDragInteractionType]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "sequence",                         lookup_key: Simple {                             key: "sequence",                             py_key: Py(                                 0x00007fa14ae88130,                             ),                             path: LookupPath(                                 [                                     S(                                         "sequence",                                         Py(                                             0x00007fa14ae880f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3b790,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Int(                                             IntValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[int]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[int]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe7b40,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe7b70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc6deb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "camera_drag_move": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc6deb0,                                                 ),                                             ],                                         },                                         expected_repr: "'camera_drag_move'",                                         name: "literal['camera_drag_move']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['camera_drag_move']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14afe7ba0,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14afe7bd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ae37f00,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ae37f00,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCameraDragMove",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a24a00,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionCameraDragMove",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, interaction: kittycad.models.camera_drag_interaction_type.CameraDragInteractionType, sequence: Optional[int] = None, type: Literal['camera_drag_move'] = 'camera_drag_move', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

interaction: CameraDragInteractionType

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'interaction': FieldInfo(annotation=CameraDragInteractionType, required=True), 'sequence': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['camera_drag_move'], required=False, default='camera_drag_move'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

sequence: Optional[int]

type: Literal['camera_drag_move']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionCameraDragStart(**data)

Camera drag started.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'interaction': <enum 'CameraDragInteractionType'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['camera_drag_start'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionCameraDragStart'>, 'config': {'title': 'OptionCameraDragStart'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionCameraDragStart'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionCameraDragStart'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionCameraDragStart:94467866634688', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'interaction': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'CameraDragInteractionType'>, 'members': [CameraDragInteractionType.PAN, CameraDragInteractionType.ROTATE, CameraDragInteractionType.ZOOM], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.camera_drag_interaction_type.CameraDragInteractionType:94467849400224', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'camera_drag_start', 'schema': {'expected': ['camera_drag_start'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionCameraDragStart', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a229c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "interaction": SerField {                         key_py: Py(                             0x00007fa14e7e0670,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb029b2fa0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc6ff70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "camera_drag_start",                                             },                                             expected_py: None,                                             name: "literal['camera_drag_start']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionCameraDragStart",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCameraDragStart", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "interaction",                         lookup_key: Simple {                             key: "interaction",                             py_key: Py(                                 0x00007fa14ae36270,                             ),                             path: LookupPath(                                 [                                     S(                                         "interaction",                                         Py(                                             0x00007fa14ae36230,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e7e0670,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb029b2fa0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "pan": 0,                                             "rotate": 1,                                             "zoom": 2,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b38d970,                                         ),                                         Py(                                             0x00007fa14b38d9d0,                                         ),                                         Py(                                             0x00007fa14b38da30,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'pan', 'rotate' or 'zoom'",                                 strict: false,                                 class_repr: "CameraDragInteractionType",                                 name: "str-enum[CameraDragInteractionType]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe7990,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe7450,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc6ff70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "camera_drag_start": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc6ff70,                                                 ),                                             ],                                         },                                         expected_repr: "'camera_drag_start'",                                         name: "literal['camera_drag_start']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['camera_drag_start']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14afe74e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14afe7390,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ae360c0,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ae360c0,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCameraDragStart",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a229c0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionCameraDragStart",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, interaction: kittycad.models.camera_drag_interaction_type.CameraDragInteractionType, type: Literal['camera_drag_start'] = 'camera_drag_start', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

interaction: CameraDragInteractionType

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'interaction': FieldInfo(annotation=CameraDragInteractionType, required=True), 'type': FieldInfo(annotation=Literal['camera_drag_start'], required=False, default='camera_drag_start'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['camera_drag_start']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionCenterOfMass(**data)

Get the center of mass of entities in the scene or the default scene.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_ids': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'output_unit': <enum 'UnitLength'>, 'type': typing.Literal['center_of_mass']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionCenterOfMass'>, 'config': {'title': 'OptionCenterOfMass'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionCenterOfMass'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionCenterOfMass'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionCenterOfMass:94467868073968', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'output_unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitLength'>, 'members': [UnitLength.CM, UnitLength.FT, UnitLength.IN, UnitLength.M, UnitLength.MM, UnitLength.YD], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_length.UnitLength:94467861018320', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'center_of_mass', 'schema': {'expected': ['center_of_mass'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCenterOfMass', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b81ff0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc6fb30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "center_of_mass",                                             },                                             expected_py: None,                                             name: "literal['center_of_mass']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_ids": SerField {                         key_py: Py(                             0x00007fa14b038970,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "output_unit": SerField {                         key_py: Py(                             0x00007fa14bb4f470,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb034c76d0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionCenterOfMass",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCenterOfMass", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_ids",                         lookup_key: Simple {                             key: "entity_ids",                             py_key: Py(                                 0x00007fa14adeaf70,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_ids",                                         Py(                                             0x00007fa14adeaf30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b038970,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "output_unit",                         lookup_key: Simple {                             key: "output_unit",                             py_key: Py(                                 0x00007fa14adeaff0,                             ),                             path: LookupPath(                                 [                                     S(                                         "output_unit",                                         Py(                                             0x00007fa14adeafb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bb4f470,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb034c76d0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "ft": 1,                                             "m": 3,                                             "yd": 5,                                             "mm": 4,                                             "cm": 0,                                             "in": 2,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b3c4c50,                                         ),                                         Py(                                             0x00007fa14b3c51f0,                                         ),                                         Py(                                             0x00007fa14b3c52b0,                                         ),                                         Py(                                             0x00007fa14b3c5310,                                         ),                                         Py(                                             0x00007fa14b3c5370,                                         ),                                         Py(                                             0x00007fa14b3c53d0,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'cm', 'ft', 'in', 'm', 'mm' or 'yd'",                                 strict: false,                                 class_repr: "UnitLength",                                 name: "str-enum[UnitLength]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc71b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc71e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc6fb30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "center_of_mass": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc6fb30,                                                 ),                                             ],                                         },                                         expected_repr: "'center_of_mass'",                                         name: "literal['center_of_mass']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['center_of_mass']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCenterOfMass",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b81ff0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionCenterOfMass",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_ids: List[str], output_unit: kittycad.models.unit_length.UnitLength, type: Literal['center_of_mass'] = 'center_of_mass') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_ids: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_ids': FieldInfo(annotation=List[str], required=True), 'output_unit': FieldInfo(annotation=UnitLength, required=True), 'type': FieldInfo(annotation=Literal['center_of_mass'], required=False, default='center_of_mass')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

output_unit: UnitLength

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['center_of_mass']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionClosePath(**data)

Closes a path, converting it to a 2D solid.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path_id': <class 'str'>, 'type': typing.Literal['close_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionClosePath'>, 'config': {'title': 'OptionClosePath'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionClosePath'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionClosePath'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionClosePath:94467866618672', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'path_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'close_path', 'schema': {'expected': ['close_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionClosePath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a1eb30,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "path_id": SerField {                         key_py: Py(                             0x00007fa14afd3120,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc6f5b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "close_path",                                             },                                             expected_py: None,                                             name: "literal['close_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionClosePath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionClosePath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "path_id",                         lookup_key: Simple {                             key: "path_id",                             py_key: Py(                                 0x00007fa14afe7570,                             ),                             path: LookupPath(                                 [                                     S(                                         "path_id",                                         Py(                                             0x00007fa14afe75a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd3120,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe75d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe7600,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc6f5b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "close_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc6f5b0,                                                 ),                                             ],                                         },                                         expected_repr: "'close_path'",                                         name: "literal['close_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['close_path']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionClosePath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a1eb30,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionClosePath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, path_id: str, type: Literal['close_path'] = 'close_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'path_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['close_path'], required=False, default='close_path')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path_id: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['close_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionCurveGetControlPoints(**data)

Get control points of the given curve.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'curve_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['curve_get_control_points']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionCurveGetControlPoints'>, 'config': {'title': 'OptionCurveGetControlPoints'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionCurveGetControlPoints'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionCurveGetControlPoints'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionCurveGetControlPoints:94467867792672', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'curve_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'curve_get_control_points', 'schema': {'expected': ['curve_get_control_points'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCurveGetControlPoints', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b3d520,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd06c90,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "curve_get_control_points",                                             },                                             expected_py: None,                                             name: "literal['curve_get_control_points']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "curve_id": SerField {                         key_py: Py(                             0x00007fa14b09ad70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCurveGetControlPoints",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCurveGetControlPoints", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "curve_id",                         lookup_key: Simple {                             key: "curve_id",                             py_key: Py(                                 0x00007fa14ada84f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "curve_id",                                         Py(                                             0x00007fa14ada84b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b09ad70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad56790,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad567c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd06c90,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "curve_get_control_points": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd06c90,                                                 ),                                             ],                                         },                                         expected_repr: "'curve_get_control_points'",                                         name: "literal['curve_get_control_points']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['curve_get_control_points']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCurveGetControlPoints",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b3d520,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionCurveGetControlPoints",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, curve_id: str, type: Literal['curve_get_control_points'] = 'curve_get_control_points') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

curve_id: str

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'curve_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['curve_get_control_points'], required=False, default='curve_get_control_points')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['curve_get_control_points']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionCurveGetEndPoints(**data)

Find the start and end of a curve.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'curve_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['curve_get_end_points']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionCurveGetEndPoints'>, 'config': {'title': 'OptionCurveGetEndPoints'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionCurveGetEndPoints'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionCurveGetEndPoints'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionCurveGetEndPoints:94467867923232', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'curve_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'curve_get_end_points', 'schema': {'expected': ['curve_get_end_points'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCurveGetEndPoints', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b5d320,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "curve_id": SerField {                         key_py: Py(                             0x00007fa14b09ad70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14beb7ef0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "curve_get_end_points",                                             },                                             expected_py: None,                                             name: "literal['curve_get_end_points']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCurveGetEndPoints",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCurveGetEndPoints", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "curve_id",                         lookup_key: Simple {                             key: "curve_id",                             py_key: Py(                                 0x00007fa14add1270,                             ),                             path: LookupPath(                                 [                                     S(                                         "curve_id",                                         Py(                                             0x00007fa14add11f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b09ad70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc5080,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc50b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14beb7ef0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "curve_get_end_points": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14beb7ef0,                                                 ),                                             ],                                         },                                         expected_repr: "'curve_get_end_points'",                                         name: "literal['curve_get_end_points']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['curve_get_end_points']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCurveGetEndPoints",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b5d320,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionCurveGetEndPoints",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, curve_id: str, type: Literal['curve_get_end_points'] = 'curve_get_end_points') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

curve_id: str

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'curve_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['curve_get_end_points'], required=False, default='curve_get_end_points')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['curve_get_end_points']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionCurveGetType(**data)

Get type of the given curve.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'curve_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['curve_get_type']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionCurveGetType'>, 'config': {'title': 'OptionCurveGetType'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionCurveGetType'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionCurveGetType'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionCurveGetType:94467867776464', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'curve_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'curve_get_type', 'schema': {'expected': ['curve_get_type'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCurveGetType', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b395d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14beb7f70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "curve_get_type",                                             },                                             expected_py: None,                                             name: "literal['curve_get_type']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "curve_id": SerField {                         key_py: Py(                             0x00007fa14b09ad70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionCurveGetType",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCurveGetType", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "curve_id",                         lookup_key: Simple {                             key: "curve_id",                             py_key: Py(                                 0x00007fa14ad9f330,                             ),                             path: LookupPath(                                 [                                     S(                                         "curve_id",                                         Py(                                             0x00007fa14ad9f3b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b09ad70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad56220,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad56250,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14beb7f70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "curve_get_type": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14beb7f70,                                                 ),                                             ],                                         },                                         expected_repr: "'curve_get_type'",                                         name: "literal['curve_get_type']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['curve_get_type']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCurveGetType",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b395d0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionCurveGetType",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, curve_id: str, type: Literal['curve_get_type'] = 'curve_get_type') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

curve_id: str

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'curve_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['curve_get_type'], required=False, default='curve_get_type')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['curve_get_type']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionCurveSetConstraint(**data)

Get the plane for sketch mode.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'constraint_bound': <enum 'PathComponentConstraintBound'>, 'constraint_type': <enum 'PathComponentConstraintType'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['curve_set_constraint']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionCurveSetConstraint'>, 'config': {'title': 'OptionCurveSetConstraint'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionCurveSetConstraint'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionCurveSetConstraint'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionCurveSetConstraint:94467867688720', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'constraint_bound': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'PathComponentConstraintBound'>, 'members': [PathComponentConstraintBound.UNCONSTRAINED, PathComponentConstraintBound.PARTIALLY_CONSTRAINED, PathComponentConstraintBound.FULLY_CONSTRAINED], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.path_component_constraint_bound.PathComponentConstraintBound:94467866073616', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'constraint_type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'PathComponentConstraintType'>, 'members': [PathComponentConstraintType.UNCONSTRAINED, PathComponentConstraintType.VERTICAL, PathComponentConstraintType.HORIZONTAL, PathComponentConstraintType.EQUAL_LENGTH, PathComponentConstraintType.PARALLEL, PathComponentConstraintType.ANGLE_BETWEEN], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.path_component_constraint_type.PathComponentConstraintType:94467866076960', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'curve_set_constraint', 'schema': {'expected': ['curve_set_constraint'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCurveSetConstraint', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b23f10,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "constraint_type": SerField {                         key_py: Py(                             0x00007fa14b01e9b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb0399a720,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14beb7e30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "curve_set_constraint",                                             },                                             expected_py: None,                                             name: "literal['curve_set_constraint']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "constraint_bound": SerField {                         key_py: Py(                             0x00007fa14b01e930,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb03999a10,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionCurveSetConstraint",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionCurveSetConstraint", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "constraint_bound",                         lookup_key: Simple {                             key: "constraint_bound",                             py_key: Py(                                 0x00007fa14aef20b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "constraint_bound",                                         Py(                                             0x00007fa14ad2deb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01e930,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb03999a10,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "fully_constrained": 2,                                             "partially_constrained": 1,                                             "unconstrained": 0,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b11ae70,                                         ),                                         Py(                                             0x00007fa14b11af30,                                         ),                                         Py(                                             0x00007fa14b11aff0,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'unconstrained', 'partially_constrained' or 'fully_constrained'",                                 strict: false,                                 class_repr: "PathComponentConstraintBound",                                 name: "str-enum[PathComponentConstraintBound]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "constraint_type",                         lookup_key: Simple {                             key: "constraint_type",                             py_key: Py(                                 0x00007fa14ad6c4b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "constraint_type",                                         Py(                                             0x00007fa14ad6c530,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01e9b0,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb0399a720,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "unconstrained": 0,                                             "angle_between": 5,                                             "equal_length": 3,                                             "vertical": 1,                                             "horizontal": 2,                                             "parallel": 4,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b11b350,                                         ),                                         Py(                                             0x00007fa14b11b2f0,                                         ),                                         Py(                                             0x00007fa14b11bc50,                                         ),                                         Py(                                             0x00007fa14b11bcb0,                                         ),                                         Py(                                             0x00007fa14b11bd10,                                         ),                                         Py(                                             0x00007fa14b11bd70,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'unconstrained', 'vertical', 'horizontal', 'equal_length', 'parallel' or 'angle_between'",                                 strict: false,                                 class_repr: "PathComponentConstraintType",                                 name: "str-enum[PathComponentConstraintType]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ad6c3f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ad6c430,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b024300,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b024360,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14beb7e30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "curve_set_constraint": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14beb7e30,                                                 ),                                             ],                                         },                                         expected_repr: "'curve_set_constraint'",                                         name: "literal['curve_set_constraint']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['curve_set_constraint']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionCurveSetConstraint",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b23f10,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionCurveSetConstraint",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, constraint_bound: kittycad.models.path_component_constraint_bound.PathComponentConstraintBound, constraint_type: kittycad.models.path_component_constraint_type.PathComponentConstraintType, object_id: str, type: Literal['curve_set_constraint'] = 'curve_set_constraint') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

constraint_bound: PathComponentConstraintBound

constraint_type: PathComponentConstraintType

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'constraint_bound': FieldInfo(annotation=PathComponentConstraintBound, required=True), 'constraint_type': FieldInfo(annotation=PathComponentConstraintType, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['curve_set_constraint'], required=False, default='curve_set_constraint')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['curve_set_constraint']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDefaultCameraCenterToScene(**data)

Updates the camera to center to the center of the current scene’s bounds

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'camera_movement': <enum 'CameraMovement'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_center_to_scene']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraCenterToScene'>, 'config': {'title': 'OptionDefaultCameraCenterToScene'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraCenterToScene'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraCenterToScene'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraCenterToScene:94467868189760', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'camera_movement': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'vantage', 'schema': {'cls': <enum 'CameraMovement'>, 'members': [CameraMovement.VANTAGE, CameraMovement.NONE], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.camera_movement.CameraMovement:94467849439920', 'sub_type': 'str', 'type': 'enum'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_center_to_scene', 'schema': {'expected': ['default_camera_center_to_scene'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraCenterToScene', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b9e440,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd07000,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_center_to_scene",                                             },                                             expected_py: None,                                             name: "literal['default_camera_center_to_scene']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "camera_movement": SerField {                         key_py: Py(                             0x00007fa14bc6fef0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bbeb7b0,                                         ),                                     ),                                     serializer: Enum(                                         EnumSerializer {                                             class: Py(                                                 0x000055eb029bcab0,                                             ),                                             serializer: Some(                                                 Str(                                                     StrSerializer,                                                 ),                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraCenterToScene",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraCenterToScene", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "camera_movement",                         lookup_key: Simple {                             key: "camera_movement",                             py_key: Py(                                 0x00007fa14ae071f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "camera_movement",                                         Py(                                             0x00007fa14ae070b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bc6fef0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bbeb7b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: StrEnum(                                     EnumValidator {                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                         class: Py(                                             0x000055eb029bcab0,                                         ),                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "vantage": 0,                                                     "none": 1,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14b38dcd0,                                                 ),                                                 Py(                                                     0x00007fa14b38dd30,                                                 ),                                             ],                                         },                                         missing: None,                                         expected_repr: "'vantage' or 'none'",                                         strict: false,                                         class_repr: "CameraMovement",                                         name: "str-enum[CameraMovement]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[str-enum[CameraMovement]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae005a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae004e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd07000,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_center_to_scene": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd07000,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_center_to_scene'",                                         name: "literal['default_camera_center_to_scene']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_center_to_scene']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraCenterToScene",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b9e440,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraCenterToScene",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, camera_movement: kittycad.models.camera_movement.CameraMovement = 'vantage', type: Literal['default_camera_center_to_scene'] = 'default_camera_center_to_scene') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

camera_movement: CameraMovement

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'camera_movement': FieldInfo(annotation=CameraMovement, required=False, default='vantage'), 'type': FieldInfo(annotation=Literal['default_camera_center_to_scene'], required=False, default='default_camera_center_to_scene')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_center_to_scene']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDefaultCameraCenterToSelection(**data)

Updates the camera to center to the center of the current selection (or the origin if nothing is selected)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'camera_movement': <enum 'CameraMovement'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_center_to_selection']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraCenterToSelection'>, 'config': {'title': 'OptionDefaultCameraCenterToSelection'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraCenterToSelection'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraCenterToSelection'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraCenterToSelection:94467868169696', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'camera_movement': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'vantage', 'schema': {'cls': <enum 'CameraMovement'>, 'members': [CameraMovement.VANTAGE, CameraMovement.NONE], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.camera_movement.CameraMovement:94467849439920', 'sub_type': 'str', 'type': 'enum'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_center_to_selection', 'schema': {'expected': ['default_camera_center_to_selection'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraCenterToSelection', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b995e0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2ad30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_center_to_selection",                                             },                                             expected_py: None,                                             name: "literal['default_camera_center_to_selection']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "camera_movement": SerField {                         key_py: Py(                             0x00007fa14bc6fef0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bbeb7b0,                                         ),                                     ),                                     serializer: Enum(                                         EnumSerializer {                                             class: Py(                                                 0x000055eb029bcab0,                                             ),                                             serializer: Some(                                                 Str(                                                     StrSerializer,                                                 ),                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraCenterToSelection",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraCenterToSelection", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "camera_movement",                         lookup_key: Simple {                             key: "camera_movement",                             py_key: Py(                                 0x00007fa14aef1a30,                             ),                             path: LookupPath(                                 [                                     S(                                         "camera_movement",                                         Py(                                             0x00007fa14b065eb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bc6fef0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bbeb7b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: StrEnum(                                     EnumValidator {                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                         class: Py(                                             0x000055eb029bcab0,                                         ),                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "vantage": 0,                                                     "none": 1,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14b38dcd0,                                                 ),                                                 Py(                                                     0x00007fa14b38dd30,                                                 ),                                             ],                                         },                                         missing: None,                                         expected_repr: "'vantage' or 'none'",                                         strict: false,                                         class_repr: "CameraMovement",                                         name: "str-enum[CameraMovement]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[str-enum[CameraMovement]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc74b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc7690,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2ad30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_center_to_selection": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2ad30,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_center_to_selection'",                                         name: "literal['default_camera_center_to_selection']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_center_to_selection']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraCenterToSelection",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b995e0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraCenterToSelection",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, camera_movement: kittycad.models.camera_movement.CameraMovement = 'vantage', type: Literal['default_camera_center_to_selection'] = 'default_camera_center_to_selection') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

camera_movement: CameraMovement

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'camera_movement': FieldInfo(annotation=CameraMovement, required=False, default='vantage'), 'type': FieldInfo(annotation=Literal['default_camera_center_to_selection'], required=False, default='default_camera_center_to_selection')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_center_to_selection']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDefaultCameraFocusOn(**data)

Focus the default camera upon an object in the scene.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_focus_on'], 'uuid': <class 'str'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraFocusOn'>, 'config': {'title': 'OptionDefaultCameraFocusOn'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraFocusOn'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraFocusOn'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraFocusOn:94467868096544', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_focus_on', 'schema': {'expected': ['default_camera_focus_on'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'uuid': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraFocusOn', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b87820,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "uuid": SerField {                         key_py: Py(                             0x00007fa14e427de0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14beb7ab0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_focus_on",                                             },                                             expected_py: None,                                             name: "literal['default_camera_focus_on']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraFocusOn",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraFocusOn", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc7cf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc7d20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14beb7ab0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_focus_on": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14beb7ab0,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_focus_on'",                                         name: "literal['default_camera_focus_on']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_focus_on']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "uuid",                         lookup_key: Simple {                             key: "uuid",                             py_key: Py(                                 0x00007fa14adc7d50,                             ),                             path: LookupPath(                                 [                                     S(                                         "uuid",                                         Py(                                             0x00007fa14adc7d80,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e427de0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraFocusOn",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b87820,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraFocusOn",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['default_camera_focus_on'] = 'default_camera_focus_on', uuid: str) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['default_camera_focus_on'], required=False, default='default_camera_focus_on'), 'uuid': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_focus_on']

classmethod update_forward_refs(**localns)

Return type:

None

uuid: str

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDefaultCameraGetSettings(**data)

Gets the default camera’s camera settings

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_get_settings']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraGetSettings'>, 'config': {'title': 'OptionDefaultCameraGetSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraGetSettings'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraGetSettings'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraGetSettings:94467866676640', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_get_settings', 'schema': {'expected': ['default_camera_get_settings'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraGetSettings', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a2cda0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2ac90,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_get_settings",                                             },                                             expected_py: None,                                             name: "literal['default_camera_get_settings']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraGetSettings",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraGetSettings", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b020750,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b020780,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2ac90,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_get_settings": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2ac90,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_get_settings'",                                         name: "literal['default_camera_get_settings']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_get_settings']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraGetSettings",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a2cda0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraGetSettings",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['default_camera_get_settings'] = 'default_camera_get_settings') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['default_camera_get_settings'], required=False, default='default_camera_get_settings')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_get_settings']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDefaultCameraLookAt(**data)

Change what the default camera is looking at.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'center': <class 'kittycad.models.point3d.Point3d'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'sequence': typing.Optional[int], 'type': typing.Literal['default_camera_look_at'], 'up': <class 'kittycad.models.point3d.Point3d'>, 'vantage': <class 'kittycad.models.point3d.Point3d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraLookAt'>, 'config': {'title': 'OptionDefaultCameraLookAt'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraLookAt'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraLookAt'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraLookAt:94467866691568', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'sequence': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_look_at', 'schema': {'expected': ['default_camera_look_at'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'up': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'vantage': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraLookAt', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a307f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "center": SerField {                         key_py: Py(                             0x00007fa14ef08150,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14beb6cf0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_look_at",                                             },                                             expected_py: None,                                             name: "literal['default_camera_look_at']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "sequence": SerField {                         key_py: Py(                             0x00007fa14fa3b790,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Int(                                                 IntSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "vantage": SerField {                         key_py: Py(                             0x00007fa14bbeb7b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "up": SerField {                         key_py: Py(                             0x00007fa14d9ed0b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 5,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraLookAt",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55eb0330e750), serializer: Fields(GeneralFieldsSerializer { fields: {"z": SerField { key_py: Py(0x7fa14fa3e1a0), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7fa14fa3e170), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7fa14fa3e140), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraLookAt", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "center",                         lookup_key: Simple {                             key: "center",                             py_key: Py(                                 0x00007fa14afe79f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "center",                                         Py(                                             0x00007fa14afe78a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ef08150,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "sequence",                         lookup_key: Simple {                             key: "sequence",                             py_key: Py(                                 0x00007fa14ae88f70,                             ),                             path: LookupPath(                                 [                                     S(                                         "sequence",                                         Py(                                             0x00007fa14ae88db0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3b790,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Int(                                             IntValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[int]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[int]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe77e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe7900,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14beb6cf0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_look_at": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14beb6cf0,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_look_at'",                                         name: "literal['default_camera_look_at']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_look_at']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "up",                         lookup_key: Simple {                             key: "up",                             py_key: Py(                                 0x00007fa14afe7810,                             ),                             path: LookupPath(                                 [                                     S(                                         "up",                                         Py(                                             0x00007fa14afe7870,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d9ed0b0,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "vantage",                         lookup_key: Simple {                             key: "vantage",                             py_key: Py(                                 0x00007fa14afe7720,                             ),                             path: LookupPath(                                 [                                     S(                                         "vantage",                                         Py(                                             0x00007fa14afe7780,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bbeb7b0,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraLookAt",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a307f0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraLookAt",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fa14fa3e140), path: LookupPath([S("x", Py(0x7fa14fa3e140))]) }, name_py: Py(0x7fa14fa3e140), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fa14fa3e170), path: LookupPath([S("y", Py(0x7fa14fa3e170))]) }, name_py: Py(0x7fa14fa3e170), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fa14fa3e1a0), path: LookupPath([S("z", Py(0x7fa14fa3e1a0))]) }, name_py: Py(0x7fa14fa3e1a0), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb0330e750), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, center: kittycad.models.point3d.Point3d, sequence: Optional[int] = None, type: Literal['default_camera_look_at'] = 'default_camera_look_at', up: kittycad.models.point3d.Point3d, vantage: kittycad.models.point3d.Point3d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

center: Point3d

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'center': FieldInfo(annotation=Point3d, required=True), 'sequence': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['default_camera_look_at'], required=False, default='default_camera_look_at'), 'up': FieldInfo(annotation=Point3d, required=True), 'vantage': FieldInfo(annotation=Point3d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

sequence: Optional[int]

type: Literal['default_camera_look_at']

up: Point3d

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

vantage: Point3d

class kittycad.models.modeling_cmd.OptionDefaultCameraPerspectiveSettings(**data)

Change what the default camera is looking at.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'center': <class 'kittycad.models.point3d.Point3d'>, 'fov_y': typing.Optional[float], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'sequence': typing.Optional[int], 'type': typing.Literal['default_camera_perspective_settings'], 'up': <class 'kittycad.models.point3d.Point3d'>, 'vantage': <class 'kittycad.models.point3d.Point3d'>, 'z_far': typing.Optional[float], 'z_near': typing.Optional[float]}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraPerspectiveSettings'>, 'config': {'title': 'OptionDefaultCameraPerspectiveSettings'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraPerspectiveSettings'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraPerspectiveSettings'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraPerspectiveSettings:94467866699232', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'fov_y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'sequence': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_perspective_settings', 'schema': {'expected': ['default_camera_perspective_settings'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'up': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'vantage': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'z_far': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'z_near': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraPerspectiveSettings', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a325e0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "up": SerField {                         key_py: Py(                             0x00007fa14d9ed0b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "fov_y": SerField {                         key_py: Py(                             0x00007fa14bbea670,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Float(                                                 FloatSerializer {                                                     inf_nan_mode: Null,                                                 },                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "z_far": SerField {                         key_py: Py(                             0x00007fa14afe4060,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Float(                                                 FloatSerializer {                                                     inf_nan_mode: Null,                                                 },                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "center": SerField {                         key_py: Py(                             0x00007fa14ef08150,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "vantage": SerField {                         key_py: Py(                             0x00007fa14bbeb7b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "z_near": SerField {                         key_py: Py(                             0x00007fa14afe4150,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Float(                                                 FloatSerializer {                                                     inf_nan_mode: Null,                                                 },                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "sequence": SerField {                         key_py: Py(                             0x00007fa14fa3b790,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Int(                                                 IntSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2a7e0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_perspective_settings",                                             },                                             expected_py: None,                                             name: "literal['default_camera_perspective_settings']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 8,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraPerspectiveSettings",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55eb0330e750), serializer: Fields(GeneralFieldsSerializer { fields: {"y": SerField { key_py: Py(0x7fa14fa3e170), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7fa14fa3e1a0), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7fa14fa3e140), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraPerspectiveSettings", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "center",                         lookup_key: Simple {                             key: "center",                             py_key: Py(                                 0x00007fa14b020c00,                             ),                             path: LookupPath(                                 [                                     S(                                         "center",                                         Py(                                             0x00007fa14b020c30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ef08150,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "fov_y",                         lookup_key: Simple {                             key: "fov_y",                             py_key: Py(                                 0x00007fa14b020c60,                             ),                             path: LookupPath(                                 [                                     S(                                         "fov_y",                                         Py(                                             0x00007fa14b020c90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bbea670,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Float(                                             FloatValidator {                                                 strict: false,                                                 allow_inf_nan: true,                                             },                                         ),                                         name: "nullable[float]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[float]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "sequence",                         lookup_key: Simple {                             key: "sequence",                             py_key: Py(                                 0x00007fa14ae964f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "sequence",                                         Py(                                             0x00007fa14ae964b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3b790,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Int(                                             IntValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[int]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[int]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b020cc0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b020d20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2a7e0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_perspective_settings": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2a7e0,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_perspective_settings'",                                         name: "literal['default_camera_perspective_settings']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_perspective_settings']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "up",                         lookup_key: Simple {                             key: "up",                             py_key: Py(                                 0x00007fa14b020d50,                             ),                             path: LookupPath(                                 [                                     S(                                         "up",                                         Py(                                             0x00007fa14b020d80,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d9ed0b0,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "vantage",                         lookup_key: Simple {                             key: "vantage",                             py_key: Py(                                 0x00007fa14b020db0,                             ),                             path: LookupPath(                                 [                                     S(                                         "vantage",                                         Py(                                             0x00007fa14b020de0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bbeb7b0,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "z_far",                         lookup_key: Simple {                             key: "z_far",                             py_key: Py(                                 0x00007fa14b020e10,                             ),                             path: LookupPath(                                 [                                     S(                                         "z_far",                                         Py(                                             0x00007fa14b020e40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe4060,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Float(                                             FloatValidator {                                                 strict: false,                                                 allow_inf_nan: true,                                             },                                         ),                                         name: "nullable[float]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[float]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "z_near",                         lookup_key: Simple {                             key: "z_near",                             py_key: Py(                                 0x00007fa14b020e70,                             ),                             path: LookupPath(                                 [                                     S(                                         "z_near",                                         Py(                                             0x00007fa14b020ea0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe4150,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Float(                                             FloatValidator {                                                 strict: false,                                                 allow_inf_nan: true,                                             },                                         ),                                         name: "nullable[float]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[float]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraPerspectiveSettings",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a325e0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraPerspectiveSettings",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fa14fa3e140), path: LookupPath([S("x", Py(0x7fa14fa3e140))]) }, name_py: Py(0x7fa14fa3e140), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fa14fa3e170), path: LookupPath([S("y", Py(0x7fa14fa3e170))]) }, name_py: Py(0x7fa14fa3e170), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fa14fa3e1a0), path: LookupPath([S("z", Py(0x7fa14fa3e1a0))]) }, name_py: Py(0x7fa14fa3e1a0), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb0330e750), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, center: kittycad.models.point3d.Point3d, fov_y: Optional[float] = None, sequence: Optional[int] = None, type: Literal['default_camera_perspective_settings'] = 'default_camera_perspective_settings', up: kittycad.models.point3d.Point3d, vantage: kittycad.models.point3d.Point3d, z_far: Optional[float] = None, z_near: Optional[float] = None) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

center: Point3d

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

fov_y: Optional[float]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'center': FieldInfo(annotation=Point3d, required=True), 'fov_y': FieldInfo(annotation=Union[float, NoneType], required=False, default=None), 'sequence': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['default_camera_perspective_settings'], required=False, default='default_camera_perspective_settings'), 'up': FieldInfo(annotation=Point3d, required=True), 'vantage': FieldInfo(annotation=Point3d, required=True), 'z_far': FieldInfo(annotation=Union[float, NoneType], required=False, default=None), 'z_near': FieldInfo(annotation=Union[float, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

sequence: Optional[int]

type: Literal['default_camera_perspective_settings']

up: Point3d

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

vantage: Point3d

z_far: Optional[float]

z_near: Optional[float]

class kittycad.models.modeling_cmd.OptionDefaultCameraSetOrthographic(**data)

Use orthographic projection.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_set_orthographic']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraSetOrthographic'>, 'config': {'title': 'OptionDefaultCameraSetOrthographic'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraSetOrthographic'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraSetOrthographic'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraSetOrthographic:94467868116672', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_set_orthographic', 'schema': {'expected': ['default_camera_set_orthographic'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraSetOrthographic', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b8c6c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2a6f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_set_orthographic",                                             },                                             expected_py: None,                                             name: "literal['default_camera_set_orthographic']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraSetOrthographic",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraSetOrthographic", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad57180,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad56c10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2a6f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_set_orthographic": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2a6f0,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_set_orthographic'",                                         name: "literal['default_camera_set_orthographic']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_set_orthographic']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraSetOrthographic",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b8c6c0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraSetOrthographic",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['default_camera_set_orthographic'] = 'default_camera_set_orthographic') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['default_camera_set_orthographic'], required=False, default='default_camera_set_orthographic')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_set_orthographic']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDefaultCameraSetPerspective(**data)

Use perspective projection.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'parameters': typing.Optional[kittycad.models.perspective_camera_parameters.PerspectiveCameraParameters], 'type': typing.Literal['default_camera_set_perspective']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraSetPerspective'>, 'config': {'title': 'OptionDefaultCameraSetPerspective'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraSetPerspective'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraSetPerspective'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraSetPerspective:94467868161744', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'parameters': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.perspective_camera_parameters.PerspectiveCameraParameters'>, 'config': {'title': 'PerspectiveCameraParameters'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.perspective_camera_parameters.PerspectiveCameraParameters'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.perspective_camera_parameters.PerspectiveCameraParameters'>>]}, 'ref': 'kittycad.models.perspective_camera_parameters.PerspectiveCameraParameters:94467866251984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'fov_y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'z_far': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'z_near': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'PerspectiveCameraParameters', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_set_perspective', 'schema': {'expected': ['default_camera_set_perspective'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraSetPerspective', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b976d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "parameters": SerField {                         key_py: Py(                             0x00007fa14ea42f70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Model(                                                 ModelSerializer {                                                     class: Py(                                                         0x000055eb039c52d0,                                                     ),                                                     serializer: Fields(                                                         GeneralFieldsSerializer {                                                             fields: {                                                                 "fov_y": SerField {                                                                     key_py: Py(                                                                         0x00007fa14bbea670,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         WithDefault(                                                                             WithDefaultSerializer {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14f947100,                                                                                     ),                                                                                 ),                                                                                 serializer: Nullable(                                                                                     NullableSerializer {                                                                                         serializer: Float(                                                                                             FloatSerializer {                                                                                                 inf_nan_mode: Null,                                                                                             },                                                                                         ),                                                                                     },                                                                                 ),                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "z_near": SerField {                                                                     key_py: Py(                                                                         0x00007fa14afe4150,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         WithDefault(                                                                             WithDefaultSerializer {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14f947100,                                                                                     ),                                                                                 ),                                                                                 serializer: Nullable(                                                                                     NullableSerializer {                                                                                         serializer: Float(                                                                                             FloatSerializer {                                                                                                 inf_nan_mode: Null,                                                                                             },                                                                                         ),                                                                                     },                                                                                 ),                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "z_far": SerField {                                                                     key_py: Py(                                                                         0x00007fa14afe4060,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         WithDefault(                                                                             WithDefaultSerializer {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14f947100,                                                                                     ),                                                                                 ),                                                                                 serializer: Nullable(                                                                                     NullableSerializer {                                                                                         serializer: Float(                                                                                             FloatSerializer {                                                                                                 inf_nan_mode: Null,                                                                                             },                                                                                         ),                                                                                     },                                                                                 ),                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                             },                                                             computed_fields: Some(                                                                 ComputedFields(                                                                     [],                                                                 ),                                                             ),                                                             mode: SimpleDict,                                                             extra_serializer: None,                                                             filter: SchemaFilter {                                                                 include: None,                                                                 exclude: None,                                                             },                                                             required_fields: 3,                                                         },                                                     ),                                                     has_extra: false,                                                     root_model: false,                                                     name: "PerspectiveCameraParameters",                                                 },                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2a650,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_set_perspective",                                             },                                             expected_py: None,                                             name: "literal['default_camera_set_perspective']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraSetPerspective",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraSetPerspective", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "parameters",                         lookup_key: Simple {                             key: "parameters",                             py_key: Py(                                 0x00007fa14ae047b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "parameters",                                         Py(                                             0x00007fa14ae04770,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ea42f70,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Model(                                             ModelValidator {                                                 revalidate: Never,                                                 validator: ModelFields(                                                     ModelFieldsValidator {                                                         fields: [                                                             Field {                                                                 name: "fov_y",                                                                 lookup_key: Simple {                                                                     key: "fov_y",                                                                     py_key: Py(                                                                         0x00007fa14ae006c0,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "fov_y",                                                                                 Py(                                                                                     0x00007fa14ae006f0,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14bbea670,                                                                 ),                                                                 validator: WithDefault(                                                                     WithDefaultValidator {                                                                         default: Default(                                                                             Py(                                                                                 0x00007fa14f947100,                                                                             ),                                                                         ),                                                                         on_error: Raise,                                                                         validator: Nullable(                                                                             NullableValidator {                                                                                 validator: Float(                                                                                     FloatValidator {                                                                                         strict: false,                                                                                         allow_inf_nan: true,                                                                                     },                                                                                 ),                                                                                 name: "nullable[float]",                                                                             },                                                                         ),                                                                         validate_default: false,                                                                         copy_default: false,                                                                         name: "default[nullable[float]]",                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "z_far",                                                                 lookup_key: Simple {                                                                     key: "z_far",                                                                     py_key: Py(                                                                         0x00007fa14ae00720,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "z_far",                                                                                 Py(                                                                                     0x00007fa14ae00750,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14afe4060,                                                                 ),                                                                 validator: WithDefault(                                                                     WithDefaultValidator {                                                                         default: Default(                                                                             Py(                                                                                 0x00007fa14f947100,                                                                             ),                                                                         ),                                                                         on_error: Raise,                                                                         validator: Nullable(                                                                             NullableValidator {                                                                                 validator: Float(                                                                                     FloatValidator {                                                                                         strict: false,                                                                                         allow_inf_nan: true,                                                                                     },                                                                                 ),                                                                                 name: "nullable[float]",                                                                             },                                                                         ),                                                                         validate_default: false,                                                                         copy_default: false,                                                                         name: "default[nullable[float]]",                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "z_near",                                                                 lookup_key: Simple {                                                                     key: "z_near",                                                                     py_key: Py(                                                                         0x00007fa14ae00780,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "z_near",                                                                                 Py(                                                                                     0x00007fa14ae007b0,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14afe4150,                                                                 ),                                                                 validator: WithDefault(                                                                     WithDefaultValidator {                                                                         default: Default(                                                                             Py(                                                                                 0x00007fa14f947100,                                                                             ),                                                                         ),                                                                         on_error: Raise,                                                                         validator: Nullable(                                                                             NullableValidator {                                                                                 validator: Float(                                                                                     FloatValidator {                                                                                         strict: false,                                                                                         allow_inf_nan: true,                                                                                     },                                                                                 ),                                                                                 name: "nullable[float]",                                                                             },                                                                         ),                                                                         validate_default: false,                                                                         copy_default: false,                                                                         name: "default[nullable[float]]",                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                         ],                                                         model_name: "PerspectiveCameraParameters",                                                         extra_behavior: Ignore,                                                         extras_validator: None,                                                         strict: false,                                                         from_attributes: false,                                                         loc_by_alias: true,                                                     },                                                 ),                                                 class: Py(                                                     0x000055eb039c52d0,                                                 ),                                                 post_init: None,                                                 frozen: false,                                                 custom_init: false,                                                 root_model: false,                                                 undefined: Py(                                                     0x00007fa14d802350,                                                 ),                                                 name: "PerspectiveCameraParameters",                                             },                                         ),                                         name: "nullable[PerspectiveCameraParameters]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[PerspectiveCameraParameters]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae007e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae00810,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2a650,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_set_perspective": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2a650,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_set_perspective'",                                         name: "literal['default_camera_set_perspective']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_set_perspective']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraSetPerspective",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b976d0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraSetPerspective",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, parameters: Optional[kittycad.models.perspective_camera_parameters.PerspectiveCameraParameters] = None, type: Literal['default_camera_set_perspective'] = 'default_camera_set_perspective') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'parameters': FieldInfo(annotation=Union[PerspectiveCameraParameters, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['default_camera_set_perspective'], required=False, default='default_camera_set_perspective')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

parameters: Optional[PerspectiveCameraParameters]

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_set_perspective']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDefaultCameraZoom(**data)

Adjust zoom of the default camera.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'magnitude': <class 'float'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['default_camera_zoom']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDefaultCameraZoom'>, 'config': {'title': 'OptionDefaultCameraZoom'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDefaultCameraZoom'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDefaultCameraZoom'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDefaultCameraZoom:94467866719728', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'magnitude': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_camera_zoom', 'schema': {'expected': ['default_camera_zoom'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultCameraZoom', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a375f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "magnitude": SerField {                         key_py: Py(                             0x00007fa14d8610f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14beb68b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "default_camera_zoom",                                             },                                             expected_py: None,                                             name: "literal['default_camera_zoom']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionDefaultCameraZoom",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDefaultCameraZoom", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "magnitude",                         lookup_key: Simple {                             key: "magnitude",                             py_key: Py(                                 0x00007fa14ae970f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "magnitude",                                         Py(                                             0x00007fa14ae970b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d8610f0,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b0213e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b021410,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14beb68b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "default_camera_zoom": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14beb68b0,                                                 ),                                             ],                                         },                                         expected_repr: "'default_camera_zoom'",                                         name: "literal['default_camera_zoom']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['default_camera_zoom']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDefaultCameraZoom",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a375f0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDefaultCameraZoom",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, magnitude: float, type: Literal['default_camera_zoom'] = 'default_camera_zoom') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

magnitude: float

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'magnitude': FieldInfo(annotation=float, required=True), 'type': FieldInfo(annotation=Literal['default_camera_zoom'], required=False, default='default_camera_zoom')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['default_camera_zoom']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDensity(**data)

Get the density of entities in the scene or the default scene.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_ids': typing.List[str], 'material_mass': <class 'float'>, 'material_mass_unit': <enum 'UnitMass'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'output_unit': <enum 'UnitDensity'>, 'type': typing.Literal['density']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDensity'>, 'config': {'title': 'OptionDensity'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDensity'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDensity'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDensity:94467868045984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'material_mass': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'material_mass_unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitMass'>, 'members': [UnitMass.G, UnitMass.KG, UnitMass.LB], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_mass.UnitMass:94467863219280', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'output_unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitDensity'>, 'members': [UnitDensity.LB_FT3, UnitDensity.KG_M3], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_density.UnitDensity:94467863217504', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'density', 'schema': {'expected': ['density'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDensity', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b7b2a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14cbce4c0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "density",                                             },                                             expected_py: None,                                             name: "literal['density']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_ids": SerField {                         key_py: Py(                             0x00007fa14b038970,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "output_unit": SerField {                         key_py: Py(                             0x00007fa14bb4f470,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb036e0560,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "material_mass": SerField {                         key_py: Py(                             0x00007fa14bbd5030,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "material_mass_unit": SerField {                         key_py: Py(                             0x00007fa14bbd4f30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb036e0c50,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 5,             },         ),         has_extra: false,         root_model: false,         name: "OptionDensity",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDensity", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_ids",                         lookup_key: Simple {                             key: "entity_ids",                             py_key: Py(                                 0x00007fa14adcbcf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_ids",                                         Py(                                             0x00007fa14adca730,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b038970,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "material_mass",                         lookup_key: Simple {                             key: "material_mass",                             py_key: Py(                                 0x00007fa14adcb370,                             ),                             path: LookupPath(                                 [                                     S(                                         "material_mass",                                         Py(                                             0x00007fa14adcb570,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bbd5030,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "material_mass_unit",                         lookup_key: Simple {                             key: "material_mass_unit",                             py_key: Py(                                 0x00007fa14adcbeb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "material_mass_unit",                                         Py(                                             0x00007fa14adcbc30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bbd4f30,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb036e0c50,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "g": 0,                                             "lb": 2,                                             "kg": 1,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b3c7dd0,                                         ),                                         Py(                                             0x00007fa14b3c7e30,                                         ),                                         Py(                                             0x00007fa14b3c7e90,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'g', 'kg' or 'lb'",                                 strict: false,                                 class_repr: "UnitMass",                                 name: "str-enum[UnitMass]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "output_unit",                         lookup_key: Simple {                             key: "output_unit",                             py_key: Py(                                 0x00007fa14adcb670,                             ),                             path: LookupPath(                                 [                                     S(                                         "output_unit",                                         Py(                                             0x00007fa14adcba30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bb4f470,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb036e0560,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "kg:m3": 1,                                             "lb:ft3": 0,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b3c7cb0,                                         ),                                         Py(                                             0x00007fa14b3c7d10,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'lb:ft3' or 'kg:m3'",                                 strict: false,                                 class_repr: "UnitDensity",                                 name: "str-enum[UnitDensity]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc62b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc6160,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14cbce4c0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "density": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14cbce4c0,                                                 ),                                             ],                                         },                                         expected_repr: "'density'",                                         name: "literal['density']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['density']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDensity",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b7b2a0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDensity",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_ids: List[str], material_mass: float, material_mass_unit: kittycad.models.unit_mass.UnitMass, output_unit: kittycad.models.unit_density.UnitDensity, type: Literal['density'] = 'density') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_ids: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

material_mass: float

material_mass_unit: UnitMass

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_ids': FieldInfo(annotation=List[str], required=True), 'material_mass': FieldInfo(annotation=float, required=True), 'material_mass_unit': FieldInfo(annotation=UnitMass, required=True), 'output_unit': FieldInfo(annotation=UnitDensity, required=True), 'type': FieldInfo(annotation=Literal['density'], required=False, default='density')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

output_unit: UnitDensity

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['density']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionDisableDryRun(**data)

Sets whether or not changes to the scene or its objects will be done as a “dry run” In a dry run, successful commands won’t actually change the model. This is useful for catching errors before actually making the change.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['disable_dry_run']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionDisableDryRun'>, 'config': {'title': 'OptionDisableDryRun'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionDisableDryRun'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionDisableDryRun'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionDisableDryRun:94467867728720', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'disable_dry_run', 'schema': {'expected': ['disable_dry_run'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDisableDryRun', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b2db50,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14beb6c30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "disable_dry_run",                                             },                                             expected_py: None,                                             name: "literal['disable_dry_run']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionDisableDryRun",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionDisableDryRun", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad55920,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad55950,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14beb6c30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "disable_dry_run": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14beb6c30,                                                 ),                                             ],                                         },                                         expected_repr: "'disable_dry_run'",                                         name: "literal['disable_dry_run']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['disable_dry_run']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionDisableDryRun",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b2db50,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionDisableDryRun",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['disable_dry_run'] = 'disable_dry_run') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['disable_dry_run'], required=False, default='disable_dry_run')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['disable_dry_run']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEdgeLinesVisible(**data)

Changes visibility of scene-wide edge lines on brep solids

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'hidden': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['edge_lines_visible']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEdgeLinesVisible'>, 'config': {'title': 'OptionEdgeLinesVisible'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEdgeLinesVisible'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEdgeLinesVisible'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEdgeLinesVisible:94467867301200', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'hidden': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'edge_lines_visible', 'schema': {'expected': ['edge_lines_visible'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEdgeLinesVisible', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ac5550,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "hidden": SerField {                         key_py: Py(                             0x00007fa14e0bbea0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14beb6f70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "edge_lines_visible",                                             },                                             expected_py: None,                                             name: "literal['edge_lines_visible']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEdgeLinesVisible",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEdgeLinesVisible", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "hidden",                         lookup_key: Simple {                             key: "hidden",                             py_key: Py(                                 0x00007fa14b026850,                             ),                             path: LookupPath(                                 [                                     S(                                         "hidden",                                         Py(                                             0x00007fa14b026880,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e0bbea0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b0268b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b0268e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14beb6f70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "edge_lines_visible": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14beb6f70,                                                 ),                                             ],                                         },                                         expected_repr: "'edge_lines_visible'",                                         name: "literal['edge_lines_visible']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['edge_lines_visible']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEdgeLinesVisible",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ac5550,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEdgeLinesVisible",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, hidden: bool, type: Literal['edge_lines_visible'] = 'edge_lines_visible') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

hidden: bool

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'hidden': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['edge_lines_visible'], required=False, default='edge_lines_visible')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['edge_lines_visible']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEnableDryRun(**data)

Sets whether or not changes to the scene or its objects will be done as a “dry run” In a dry run, successful commands won’t actually change the model. This is useful for catching errors before actually making the change.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['enable_dry_run']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEnableDryRun'>, 'config': {'title': 'OptionEnableDryRun'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEnableDryRun'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEnableDryRun'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEnableDryRun:94467867709344', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'enable_dry_run', 'schema': {'expected': ['enable_dry_run'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEnableDryRun', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b28fa0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be49730,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "enable_dry_run",                                             },                                             expected_py: None,                                             name: "literal['enable_dry_run']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionEnableDryRun",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEnableDryRun", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad55440,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad55470,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be49730,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "enable_dry_run": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be49730,                                                 ),                                             ],                                         },                                         expected_repr: "'enable_dry_run'",                                         name: "literal['enable_dry_run']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['enable_dry_run']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEnableDryRun",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b28fa0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEnableDryRun",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['enable_dry_run'] = 'enable_dry_run') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['enable_dry_run'], required=False, default='enable_dry_run')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['enable_dry_run']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEnableSketchMode(**data)

Sketch on some entity (e.g. a plane, a face).

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'adjust_camera': <class 'bool'>, 'animated': <class 'bool'>, 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'ortho': <class 'bool'>, 'planar_normal': typing.Optional[kittycad.models.point3d.Point3d], 'type': typing.Literal['enable_sketch_mode']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEnableSketchMode'>, 'config': {'title': 'OptionEnableSketchMode'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEnableSketchMode'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEnableSketchMode'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEnableSketchMode:94467867696192', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'adjust_camera': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'animated': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'ortho': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'planar_normal': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'enable_sketch_mode', 'schema': {'expected': ['enable_sketch_mode'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEnableSketchMode', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b25c40,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "ortho": SerField {                         key_py: Py(                             0x00007fa14bbea7c0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "planar_normal": SerField {                         key_py: Py(                             0x00007fa14b01ecb0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Model(                                                 ModelSerializer {                                                     class: Py(                                                         0x000055eb0330e750,                                                     ),                                                     serializer: Fields(                                                         GeneralFieldsSerializer {                                                             fields: {                                                                 "z": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3e1a0,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "y": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3e170,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "x": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3e140,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                             },                                                             computed_fields: Some(                                                                 ComputedFields(                                                                     [],                                                                 ),                                                             ),                                                             mode: SimpleDict,                                                             extra_serializer: None,                                                             filter: SchemaFilter {                                                                 include: None,                                                                 exclude: None,                                                             },                                                             required_fields: 3,                                                         },                                                     ),                                                     has_extra: false,                                                     root_model: false,                                                     name: "Point3d",                                                 },                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "adjust_camera": SerField {                         key_py: Py(                             0x00007fa14b01ebf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "animated": SerField {                         key_py: Py(                             0x00007fa14b01ec30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4c070,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "enable_sketch_mode",                                             },                                             expected_py: None,                                             name: "literal['enable_sketch_mode']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 6,             },         ),         has_extra: false,         root_model: false,         name: "OptionEnableSketchMode",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEnableSketchMode", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "adjust_camera",                         lookup_key: Simple {                             key: "adjust_camera",                             py_key: Py(                                 0x00007fa14ad92370,                             ),                             path: LookupPath(                                 [                                     S(                                         "adjust_camera",                                         Py(                                             0x00007fa14ad92330,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01ebf0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "animated",                         lookup_key: Simple {                             key: "animated",                             py_key: Py(                                 0x00007fa14ad923f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "animated",                                         Py(                                             0x00007fa14ad923b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01ec30,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14ad92430,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14ad92470,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "ortho",                         lookup_key: Simple {                             key: "ortho",                             py_key: Py(                                 0x00007fa14ad54690,                             ),                             path: LookupPath(                                 [                                     S(                                         "ortho",                                         Py(                                             0x00007fa14ad546c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bbea7c0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "planar_normal",                         lookup_key: Simple {                             key: "planar_normal",                             py_key: Py(                                 0x00007fa14ad924b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "planar_normal",                                         Py(                                             0x00007fa14ad924f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01ecb0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Model(                                             ModelValidator {                                                 revalidate: Never,                                                 validator: ModelFields(                                                     ModelFieldsValidator {                                                         fields: [                                                             Field {                                                                 name: "x",                                                                 lookup_key: Simple {                                                                     key: "x",                                                                     py_key: Py(                                                                         0x00007fa14fa3e140,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "x",                                                                                 Py(                                                                                     0x00007fa14fa3e140,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "y",                                                                 lookup_key: Simple {                                                                     key: "y",                                                                     py_key: Py(                                                                         0x00007fa14fa3e170,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "y",                                                                                 Py(                                                                                     0x00007fa14fa3e170,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "z",                                                                 lookup_key: Simple {                                                                     key: "z",                                                                     py_key: Py(                                                                         0x00007fa14fa3e1a0,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "z",                                                                                 Py(                                                                                     0x00007fa14fa3e1a0,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3e1a0,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                         ],                                                         model_name: "Point3d",                                                         extra_behavior: Ignore,                                                         extras_validator: None,                                                         strict: false,                                                         from_attributes: false,                                                         loc_by_alias: true,                                                     },                                                 ),                                                 class: Py(                                                     0x000055eb0330e750,                                                 ),                                                 post_init: None,                                                 frozen: false,                                                 custom_init: false,                                                 root_model: false,                                                 undefined: Py(                                                     0x00007fa14d802350,                                                 ),                                                 name: "Point3d",                                             },                                         ),                                         name: "nullable[Point3d]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[Point3d]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad54150,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad547b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4c070,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "enable_sketch_mode": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4c070,                                                 ),                                             ],                                         },                                         expected_repr: "'enable_sketch_mode'",                                         name: "literal['enable_sketch_mode']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['enable_sketch_mode']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEnableSketchMode",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b25c40,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEnableSketchMode",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, adjust_camera: bool, animated: bool, entity_id: str, ortho: bool, planar_normal: Optional[kittycad.models.point3d.Point3d] = None, type: Literal['enable_sketch_mode'] = 'enable_sketch_mode') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

adjust_camera: bool

animated: bool

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'adjust_camera': FieldInfo(annotation=bool, required=True), 'animated': FieldInfo(annotation=bool, required=True), 'entity_id': FieldInfo(annotation=str, required=True), 'ortho': FieldInfo(annotation=bool, required=True), 'planar_normal': FieldInfo(annotation=Union[Point3d, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['enable_sketch_mode'], required=False, default='enable_sketch_mode')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

ortho: bool

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

planar_normal: Optional[Point3d]

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['enable_sketch_mode']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEngineUtilEvaluatePath(**data)

Evaluates the position of a path in one shot (engine utility for kcl executor)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path_json': <class 'str'>, 't': <class 'float'>, 'type': typing.Literal['engine_util_evaluate_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEngineUtilEvaluatePath'>, 'config': {'title': 'OptionEngineUtilEvaluatePath'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEngineUtilEvaluatePath'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEngineUtilEvaluatePath'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEngineUtilEvaluatePath:94467866432160', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'path_json': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 't': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'engine_util_evaluate_path', 'schema': {'expected': ['engine_util_evaluate_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEngineUtilEvaluatePath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb039f12a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "t": SerField {                         key_py: Py(                             0x00007fa14fa3e080,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "path_json": SerField {                         key_py: Py(                             0x00007fa14afd7ef0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2a380,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "engine_util_evaluate_path",                                             },                                             expected_py: None,                                             name: "literal['engine_util_evaluate_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionEngineUtilEvaluatePath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEngineUtilEvaluatePath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "path_json",                         lookup_key: Simple {                             key: "path_json",                             py_key: Py(                                 0x00007fa14af39c30,                             ),                             path: LookupPath(                                 [                                     S(                                         "path_json",                                         Py(                                             0x00007fa14af3aeb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd7ef0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "t",                         lookup_key: Simple {                             key: "t",                             py_key: Py(                                 0x00007fa14fa3e080,                             ),                             path: LookupPath(                                 [                                     S(                                         "t",                                         Py(                                             0x00007fa14fa3e080,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3e080,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afd3d20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afd3cf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2a380,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "engine_util_evaluate_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2a380,                                                 ),                                             ],                                         },                                         expected_repr: "'engine_util_evaluate_path'",                                         name: "literal['engine_util_evaluate_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['engine_util_evaluate_path']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEngineUtilEvaluatePath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb039f12a0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEngineUtilEvaluatePath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, path_json: str, t: float, type: Literal['engine_util_evaluate_path'] = 'engine_util_evaluate_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'path_json': FieldInfo(annotation=str, required=True), 't': FieldInfo(annotation=float, required=True), 'type': FieldInfo(annotation=Literal['engine_util_evaluate_path'], required=False, default='engine_util_evaluate_path')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path_json: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

t: float

type: Literal['engine_util_evaluate_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityCircularPattern(**data)

Create a circular pattern using this entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'arc_degrees': <class 'float'>, 'axis': <class 'kittycad.models.point3d.Point3d'>, 'center': <class 'kittycad.models.point3d.Point3d'>, 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'num_repetitions': <class 'int'>, 'rotate_duplicates': <class 'bool'>, 'type': typing.Literal['entity_circular_pattern']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityCircularPattern'>, 'config': {'title': 'OptionEntityCircularPattern'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityCircularPattern'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityCircularPattern'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityCircularPattern:94467861889984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'arc_degrees': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'center': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'num_repetitions': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'rotate_duplicates': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_circular_pattern', 'schema': {'expected': ['entity_circular_pattern'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityCircularPattern', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb0359c3c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4d670,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_circular_pattern",                                             },                                             expected_py: None,                                             name: "literal['entity_circular_pattern']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "rotate_duplicates": SerField {                         key_py: Py(                             0x00007fa14aff66f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "center": SerField {                         key_py: Py(                             0x00007fa14ef08150,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "axis": SerField {                         key_py: Py(                             0x00007fa14c13dce0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "num_repetitions": SerField {                         key_py: Py(                             0x00007fa14aff6470,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Int(                                 IntSerializer,                             ),                         ),                         required: true,                     },                     "arc_degrees": SerField {                         key_py: Py(                             0x00007fa14aff6630,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 7,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityCircularPattern",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55eb0330e750), serializer: Fields(GeneralFieldsSerializer { fields: {"z": SerField { key_py: Py(0x7fa14fa3e1a0), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7fa14fa3e140), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7fa14fa3e170), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityCircularPattern", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "arc_degrees",                         lookup_key: Simple {                             key: "arc_degrees",                             py_key: Py(                                 0x00007fa14d4a7d70,                             ),                             path: LookupPath(                                 [                                     S(                                         "arc_degrees",                                         Py(                                             0x00007fa14cb9d1f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6630,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "axis",                         lookup_key: Simple {                             key: "axis",                             py_key: Py(                                 0x00007fa14b023e70,                             ),                             path: LookupPath(                                 [                                     S(                                         "axis",                                         Py(                                             0x00007fa14b023ed0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14c13dce0,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "center",                         lookup_key: Simple {                             key: "center",                             py_key: Py(                                 0x00007fa14b023750,                             ),                             path: LookupPath(                                 [                                     S(                                         "center",                                         Py(                                             0x00007fa14b0237e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ef08150,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14cb9fd30,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14d53efb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "num_repetitions",                         lookup_key: Simple {                             key: "num_repetitions",                             py_key: Py(                                 0x00007fa14d53e0f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "num_repetitions",                                         Py(                                             0x00007fa14cd14830,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6470,                         ),                         validator: Int(                             IntValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "rotate_duplicates",                         lookup_key: Simple {                             key: "rotate_duplicates",                             py_key: Py(                                 0x00007fa14c725d30,                             ),                             path: LookupPath(                                 [                                     S(                                         "rotate_duplicates",                                         Py(                                             0x00007fa14c725530,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff66f0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b023630,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b023660,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4d670,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_circular_pattern": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4d670,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_circular_pattern'",                                         name: "literal['entity_circular_pattern']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_circular_pattern']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityCircularPattern",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb0359c3c0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityCircularPattern",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fa14fa3e140), path: LookupPath([S("x", Py(0x7fa14fa3e140))]) }, name_py: Py(0x7fa14fa3e140), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fa14fa3e170), path: LookupPath([S("y", Py(0x7fa14fa3e170))]) }, name_py: Py(0x7fa14fa3e170), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fa14fa3e1a0), path: LookupPath([S("z", Py(0x7fa14fa3e1a0))]) }, name_py: Py(0x7fa14fa3e1a0), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb0330e750), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, arc_degrees: float, axis: kittycad.models.point3d.Point3d, center: kittycad.models.point3d.Point3d, entity_id: str, num_repetitions: int, rotate_duplicates: bool, type: Literal['entity_circular_pattern'] = 'entity_circular_pattern') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

arc_degrees: float

axis: Point3d

center: Point3d

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'arc_degrees': FieldInfo(annotation=float, required=True), 'axis': FieldInfo(annotation=Point3d, required=True), 'center': FieldInfo(annotation=Point3d, required=True), 'entity_id': FieldInfo(annotation=str, required=True), 'num_repetitions': FieldInfo(annotation=int, required=True), 'rotate_duplicates': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['entity_circular_pattern'], required=False, default='entity_circular_pattern')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

num_repetitions: int

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

rotate_duplicates: bool

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_circular_pattern']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityFade(**data)

Fade entity in or out.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'duration_seconds': <class 'float'>, 'entity_id': <class 'str'>, 'fade_in': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['entity_fade']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityFade'>, 'config': {'title': 'OptionEntityFade'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityFade'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityFade'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityFade:94467867582384', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'duration_seconds': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 0.4000000059604645, 'schema': {'type': 'float'}, 'type': 'default'}, 'type': 'model-field'}, 'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'fade_in': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_fade', 'schema': {'expected': ['entity_fade'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityFade', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b09fb0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "duration_seconds": SerField {                         key_py: Py(                             0x00007fa14b01dc30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14b0f4db0,                                         ),                                     ),                                     serializer: Float(                                         FloatSerializer {                                             inf_nan_mode: Null,                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "fade_in": SerField {                         key_py: Py(                             0x00007fa14b021ad0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4d730,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_fade",                                             },                                             expected_py: None,                                             name: "literal['entity_fade']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityFade",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityFade", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "duration_seconds",                         lookup_key: Simple {                             key: "duration_seconds",                             py_key: Py(                                 0x00007fa14b1dedb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "duration_seconds",                                         Py(                                             0x00007fa14ad4a2f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01dc30,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14b0f4db0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[float]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14ad4a370,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14ad4a330,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "fade_in",                         lookup_key: Simple {                             key: "fade_in",                             py_key: Py(                                 0x00007fa14ae756e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "fade_in",                                         Py(                                             0x00007fa14ae75680,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b021ad0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae757d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae75aa0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4d730,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_fade": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4d730,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_fade'",                                         name: "literal['entity_fade']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_fade']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityFade",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b09fb0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityFade",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, duration_seconds: float = 0.4000000059604645, entity_id: str, fade_in: bool, type: Literal['entity_fade'] = 'entity_fade') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

duration_seconds: float

entity_id: str

fade_in: bool

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'duration_seconds': FieldInfo(annotation=float, required=False, default=0.4000000059604645), 'entity_id': FieldInfo(annotation=str, required=True), 'fade_in': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['entity_fade'], required=False, default='entity_fade')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_fade']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityGetAllChildUuids(**data)

What are all UUIDs of this entity’s children?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_all_child_uuids']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityGetAllChildUuids'>, 'config': {'title': 'OptionEntityGetAllChildUuids'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityGetAllChildUuids'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityGetAllChildUuids'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityGetAllChildUuids:94467866903664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_get_all_child_uuids', 'schema': {'expected': ['entity_get_all_child_uuids'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetAllChildUuids', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a64470,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2a240,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_all_child_uuids",                                             },                                             expected_py: None,                                             name: "literal['entity_get_all_child_uuids']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetAllChildUuids",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetAllChildUuids", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14b09b1f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14aeb88b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b023360,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b023390,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2a240,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_all_child_uuids": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2a240,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_all_child_uuids'",                                         name: "literal['entity_get_all_child_uuids']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_all_child_uuids']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetAllChildUuids",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a64470,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityGetAllChildUuids",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_id: str, type: Literal['entity_get_all_child_uuids'] = 'entity_get_all_child_uuids') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['entity_get_all_child_uuids'], required=False, default='entity_get_all_child_uuids')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_all_child_uuids']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityGetChildUuid(**data)

What is the UUID of this entity’s n-th child?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'child_index': <class 'int'>, 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_child_uuid']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityGetChildUuid'>, 'config': {'title': 'OptionEntityGetChildUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityGetChildUuid'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityGetChildUuid'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityGetChildUuid:94467866895040', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'child_index': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_get_child_uuid', 'schema': {'expected': ['entity_get_child_uuid'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetChildUuid', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a622c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4d8b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_child_uuid",                                             },                                             expected_py: None,                                             name: "literal['entity_get_child_uuid']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "child_index": SerField {                         key_py: Py(                             0x00007fa14aff5db0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Int(                                 IntSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetChildUuid",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetChildUuid", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "child_index",                         lookup_key: Simple {                             key: "child_index",                             py_key: Py(                                 0x00007fa14af93870,                             ),                             path: LookupPath(                                 [                                     S(                                         "child_index",                                         Py(                                             0x00007fa14aeaf7f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff5db0,                         ),                         validator: Int(                             IntValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14aeaf870,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14aeaf830,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b022df0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b022e20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4d8b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_child_uuid": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4d8b0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_child_uuid'",                                         name: "literal['entity_get_child_uuid']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_child_uuid']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetChildUuid",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a622c0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityGetChildUuid",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, child_index: int, entity_id: str, type: Literal['entity_get_child_uuid'] = 'entity_get_child_uuid') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

child_index: int

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'child_index': FieldInfo(annotation=int, required=True), 'entity_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['entity_get_child_uuid'], required=False, default='entity_get_child_uuid')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_child_uuid']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityGetDistance(**data)

What is the distance between these two entities?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'distance_type': <class 'pydantic.root_model.RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'entity_id1': <class 'str'>, 'entity_id2': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_distance']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityGetDistance'>, 'config': {'title': 'OptionEntityGetDistance'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityGetDistance'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityGetDistance'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityGetDistance:94467866921600', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'distance_type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'pydantic.root_model.RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'config': {'title': "RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]"}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'pydantic.root_model.RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'pydantic.root_model.RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>>]}, 'ref': "pydantic.root_model.RootModel:94467864067568[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]:140330727444880]", 'root_model': True, 'schema': {'choices': {'euclidean': {'cls': <class 'kittycad.models.distance_type.OptionEuclidean'>, 'config': {'title': 'OptionEuclidean'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.distance_type.OptionEuclidean'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.distance_type.OptionEuclidean'>>]}, 'ref': 'kittycad.models.distance_type.OptionEuclidean:94467864444368', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'euclidean', 'schema': {'expected': ['euclidean'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEuclidean', 'type': 'model-fields'}, 'type': 'model'}, 'on_axis': {'cls': <class 'kittycad.models.distance_type.OptionOnAxis'>, 'config': {'title': 'OptionOnAxis'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.distance_type.OptionOnAxis'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.distance_type.OptionOnAxis'>>]}, 'ref': 'kittycad.models.distance_type.OptionOnAxis:94467864425568', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'GlobalAxis'>, 'members': [GlobalAxis.X, GlobalAxis.Y, GlobalAxis.Z], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.global_axis.GlobalAxis:94467864441808', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'on_axis', 'schema': {'expected': ['on_axis'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionOnAxis', 'type': 'model-fields'}, 'type': 'model'}}, 'discriminator': 'type', 'from_attributes': True, 'metadata': {}, 'strict': False, 'type': 'tagged-union'}, 'type': 'model'}, 'type': 'model-field'}, 'entity_id1': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'entity_id2': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_get_distance', 'schema': {'expected': ['entity_get_distance'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetDistance', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a68a80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4d9b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_distance",                                             },                                             expected_py: None,                                             name: "literal['entity_get_distance']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_id2": SerField {                         key_py: Py(                             0x00007fa14aff6270,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "entity_id1": SerField {                         key_py: Py(                             0x00007fa14aff6230,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "distance_type": SerField {                         key_py: Py(                             0x00007fa14beb6b70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0380ced0,                                     ),                                     serializer: TaggedUnion(                                         TaggedUnionSerializer {                                             discriminator: LookupKey(                                                 Simple {                                                     key: "type",                                                     py_key: Py(                                                         0x00007fa14fa3c5a0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "type",                                                                 Py(                                                                     0x00007fa14fa3c5a0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                             ),                                             lookup: {                                                 "on_axis": 1,                                                 "euclidean": 0,                                             },                                             choices: [                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb0380bdd0,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14b2158f0,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "euclidean",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['euclidean']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 1,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionEuclidean",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb03807460,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "axis": SerField {                                                                         key_py: Py(                                                                             0x00007fa14c13dce0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Enum(                                                                                 EnumSerializer {                                                                                     class: Py(                                                                                         0x000055eb0380b3d0,                                                                                     ),                                                                                     serializer: Some(                                                                                         Str(                                                                                             StrSerializer,                                                                                         ),                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14b18afa0,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "on_axis",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['on_axis']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 2,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionOnAxis",                                                     },                                                 ),                                             ],                                             name: "TaggedUnion[OptionEuclidean, OptionOnAxis]",                                         },                                     ),                                     has_extra: false,                                     root_model: true,                                     name: "RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetDistance",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetDistance", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "distance_type",                         lookup_key: Simple {                             key: "distance_type",                             py_key: Py(                                 0x00007fa14ae95730,                             ),                             path: LookupPath(                                 [                                     S(                                         "distance_type",                                         Py(                                             0x00007fa14ae94a70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14beb6b70,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: TaggedUnion(                                     TaggedUnionValidator {                                         discriminator: LookupKey(                                             Simple {                                                 key: "type",                                                 py_key: Py(                                                     0x00007fa14fa3c5a0,                                                 ),                                                 path: LookupPath(                                                     [                                                         S(                                                             "type",                                                             Py(                                                                 0x00007fa14fa3c5a0,                                                             ),                                                         ),                                                     ],                                                 ),                                             },                                         ),                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "euclidean": 0,                                                     "on_axis": 1,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14b022190,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14b022220,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14b2158f0,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "euclidean": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14b2158f0,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'euclidean'",                                                                                         name: "literal['euclidean']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['euclidean']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionEuclidean",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb0380bdd0,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionEuclidean",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "axis",                                                                         lookup_key: Simple {                                                                             key: "axis",                                                                             py_key: Py(                                                                                 0x00007fa14b022250,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "axis",                                                                                         Py(                                                                                             0x00007fa14b022070,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14c13dce0,                                                                         ),                                                                         validator: StrEnum(                                                                             EnumValidator {                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                 class: Py(                                                                                     0x000055eb0380b3d0,                                                                                 ),                                                                                 lookup: LiteralLookup {                                                                                     expected_bool: None,                                                                                     expected_int: None,                                                                                     expected_str: Some(                                                                                         {                                                                                             "z": 2,                                                                                             "y": 1,                                                                                             "x": 0,                                                                                         },                                                                                     ),                                                                                     expected_py_dict: None,                                                                                     expected_py_values: None,                                                                                     values: [                                                                                         Py(                                                                                             0x00007fa14b1a2e70,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b1a2ed0,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b1a2f30,                                                                                         ),                                                                                     ],                                                                                 },                                                                                 missing: None,                                                                                 expected_repr: "'x', 'y' or 'z'",                                                                                 strict: false,                                                                                 class_repr: "GlobalAxis",                                                                                 name: "str-enum[GlobalAxis]",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14b021fb0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14b021f80,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14b18afa0,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "on_axis": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14b18afa0,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'on_axis'",                                                                                         name: "literal['on_axis']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['on_axis']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionOnAxis",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb03807460,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionOnAxis",                                                     },                                                 ),                                             ],                                         },                                         from_attributes: true,                                         strict: false,                                         custom_error: None,                                         tags_repr: "'euclidean', 'on_axis'",                                         discriminator_repr: "'type'",                                         name: "tagged-union[OptionEuclidean,OptionOnAxis]",                                     },                                 ),                                 class: Py(                                     0x000055eb0380ced0,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: true,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "entity_id1",                         lookup_key: Simple {                             key: "entity_id1",                             py_key: Py(                                 0x00007fa14ae956b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id1",                                         Py(                                             0x00007fa14ae948b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6230,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "entity_id2",                         lookup_key: Simple {                             key: "entity_id2",                             py_key: Py(                                 0x00007fa14ae95130,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id2",                                         Py(                                             0x00007fa14ae952b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6270,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b021f50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b022040,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4d9b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_distance": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4d9b0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_distance'",                                         name: "literal['entity_get_distance']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_distance']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetDistance",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a68a80,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityGetDistance",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, distance_type: pydantic.root_model.RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], entity_id1: str, entity_id2: str, type: Literal['entity_get_distance'] = 'entity_get_distance') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

distance_type: RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]

entity_id1: str

entity_id2: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'distance_type': FieldInfo(annotation=RootModel[Annotated[Union[OptionEuclidean, OptionOnAxis], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], required=True), 'entity_id1': FieldInfo(annotation=str, required=True), 'entity_id2': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['entity_get_distance'], required=False, default='entity_get_distance')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_distance']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityGetNumChildren(**data)

How many children does the entity have?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_num_children']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityGetNumChildren'>, 'config': {'title': 'OptionEntityGetNumChildren'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityGetNumChildren'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityGetNumChildren'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityGetNumChildren:94467866886576', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_get_num_children', 'schema': {'expected': ['entity_get_num_children'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetNumChildren', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a601b0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4dab0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_num_children",                                             },                                             expected_py: None,                                             name: "literal['entity_get_num_children']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetNumChildren",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetNumChildren", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14aeae7b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14aeae670,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b022790,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b022850,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4dab0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_num_children": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4dab0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_num_children'",                                         name: "literal['entity_get_num_children']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_num_children']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetNumChildren",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a601b0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityGetNumChildren",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_id: str, type: Literal['entity_get_num_children'] = 'entity_get_num_children') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['entity_get_num_children'], required=False, default='entity_get_num_children')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_num_children']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityGetParentId(**data)

What is this entity’s parent?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_parent_id']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityGetParentId'>, 'config': {'title': 'OptionEntityGetParentId'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityGetParentId'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityGetParentId'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityGetParentId:94467866758656', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_get_parent_id', 'schema': {'expected': ['entity_get_parent_id'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetParentId', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a40e00,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4dbb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_parent_id",                                             },                                             expected_py: None,                                             name: "literal['entity_get_parent_id']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetParentId",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetParentId", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14ae95430,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14ae97b30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b0222b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b0222e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4dbb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_parent_id": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4dbb0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_parent_id'",                                         name: "literal['entity_get_parent_id']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_parent_id']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetParentId",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a40e00,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityGetParentId",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_id: str, type: Literal['entity_get_parent_id'] = 'entity_get_parent_id') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['entity_get_parent_id'], required=False, default='entity_get_parent_id')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_parent_id']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityGetSketchPaths(**data)

What are all UUIDs of all the paths sketched on top of this entity?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['entity_get_sketch_paths']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityGetSketchPaths'>, 'config': {'title': 'OptionEntityGetSketchPaths'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityGetSketchPaths'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityGetSketchPaths'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityGetSketchPaths:94467866912928', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_get_sketch_paths', 'schema': {'expected': ['entity_get_sketch_paths'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityGetSketchPaths', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a668a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4dcb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_get_sketch_paths",                                             },                                             expected_py: None,                                             name: "literal['entity_get_sketch_paths']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityGetSketchPaths",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityGetSketchPaths", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14aeaf530,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14aeafdb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b023090,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b022cd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4dcb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_get_sketch_paths": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4dcb0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_get_sketch_paths'",                                         name: "literal['entity_get_sketch_paths']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_get_sketch_paths']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityGetSketchPaths",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a668a0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityGetSketchPaths",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_id: str, type: Literal['entity_get_sketch_paths'] = 'entity_get_sketch_paths') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['entity_get_sketch_paths'], required=False, default='entity_get_sketch_paths')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_get_sketch_paths']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityLinearPattern(**data)

Create a linear pattern using this entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'axis': <class 'kittycad.models.point3d.Point3d'>, 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'num_repetitions': <class 'int'>, 'spacing': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['entity_linear_pattern']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityLinearPattern'>, 'config': {'title': 'OptionEntityLinearPattern'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityLinearPattern'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityLinearPattern'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityLinearPattern:94467866964880', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'num_repetitions': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'spacing': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_linear_pattern', 'schema': {'expected': ['entity_linear_pattern'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityLinearPattern', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a73390,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "axis": SerField {                         key_py: Py(                             0x00007fa14c13dce0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0330e750,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "z": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e1a0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 3,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point3d",                                 },                             ),                         ),                         required: true,                     },                     "spacing": SerField {                         key_py: Py(                             0x00007fa14e3a77b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "num_repetitions": SerField {                         key_py: Py(                             0x00007fa14aff6470,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Int(                                 IntSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4ddb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_linear_pattern",                                             },                                             expected_py: None,                                             name: "literal['entity_linear_pattern']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 5,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityLinearPattern",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityLinearPattern", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "axis",                         lookup_key: Simple {                             key: "axis",                             py_key: Py(                                 0x00007fa14c528720,                             ),                             path: LookupPath(                                 [                                     S(                                         "axis",                                         Py(                                             0x00007fa14b0605a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14c13dce0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "z",                                                 lookup_key: Simple {                                                     key: "z",                                                     py_key: Py(                                                         0x00007fa14fa3e1a0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "z",                                                                 Py(                                                                     0x00007fa14fa3e1a0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e1a0,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point3d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0330e750,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point3d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14ae385b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14af84bf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "num_repetitions",                         lookup_key: Simple {                             key: "num_repetitions",                             py_key: Py(                                 0x00007fa14ae34e70,                             ),                             path: LookupPath(                                 [                                     S(                                         "num_repetitions",                                         Py(                                             0x00007fa14ae34b30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6470,                         ),                         validator: Int(                             IntValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "spacing",                         lookup_key: Simple {                             key: "spacing",                             py_key: Py(                                 0x00007fa14b061740,                             ),                             path: LookupPath(                                 [                                     S(                                         "spacing",                                         Py(                                             0x00007fa14b1159b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e3a77b0,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14aec6780,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b1147b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b117c60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4ddb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_linear_pattern": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4ddb0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_linear_pattern'",                                         name: "literal['entity_linear_pattern']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_linear_pattern']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityLinearPattern",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a73390,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityLinearPattern",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, axis: kittycad.models.point3d.Point3d, entity_id: str, num_repetitions: int, spacing: kittycad.models.length_unit.LengthUnit, type: Literal['entity_linear_pattern'] = 'entity_linear_pattern') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

axis: Point3d

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'axis': FieldInfo(annotation=Point3d, required=True), 'entity_id': FieldInfo(annotation=str, required=True), 'num_repetitions': FieldInfo(annotation=int, required=True), 'spacing': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['entity_linear_pattern'], required=False, default='entity_linear_pattern')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

num_repetitions: int

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

spacing: LengthUnit

type: Literal['entity_linear_pattern']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityLinearPatternTransform(**data)

Create a pattern using this entity by specifying the transform for each desired repetition. Transformations are performed in the following order (first applied to last applied): scale, rotate, translate.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'transform': typing.List[kittycad.models.transform.Transform], 'type': typing.Literal['entity_linear_pattern_transform']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityLinearPatternTransform'>, 'config': {'title': 'OptionEntityLinearPatternTransform'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityLinearPatternTransform'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityLinearPatternTransform'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityLinearPatternTransform:94467866930128', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'transform': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.transform.Transform'>, 'config': {'title': 'Transform'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.transform.Transform'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.transform.Transform'>>]}, 'ref': 'kittycad.models.transform.Transform:94467866354592', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'replicate': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': True, 'schema': {'type': 'bool'}, 'type': 'default'}, 'type': 'model-field'}, 'rotation': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': {'angle': {'unit': 'degrees', 'value': 0.0}, 'axis': {'x': 0.0, 'y': 0.0, 'z': 1.0}, 'origin': {'type': 'local'}}, 'schema': {'cls': <class 'kittycad.models.rotation.Rotation'>, 'config': {'title': 'Rotation'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.rotation.Rotation'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.rotation.Rotation'>>]}, 'ref': 'kittycad.models.rotation.Rotation:94467866320864', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'angle': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.angle.Angle'>, 'config': {'title': 'Angle'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.angle.Angle'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.angle.Angle'>>]}, 'ref': 'kittycad.models.angle.Angle:94467862185984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitAngle'>, 'members': [UnitAngle.DEGREES, UnitAngle.RADIANS], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_angle.UnitAngle:94467859501968', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'value': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Angle', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'origin': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'pydantic.root_model.RootModel[Annotated[Union[OptionLocal, OptionGlobal, OptionCustom], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'config': {'title': "RootModel[Annotated[Union[OptionLocal, OptionGlobal, OptionCustom], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]"}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'pydantic.root_model.RootModel[Annotated[Union[OptionLocal, OptionGlobal, OptionCustom], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'pydantic.root_model.RootModel[Annotated[Union[OptionLocal, OptionGlobal, OptionCustom], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>>]}, 'ref': "pydantic.root_model.RootModel:94467864067568[Annotated[Union[OptionLocal, OptionGlobal, OptionCustom], FieldInfo(annotation=NoneType, required=True, discriminator='type')]:140330724571040]", 'root_model': True, 'schema': {'choices': {'custom': {'cls': <class 'kittycad.models.origin_type.OptionCustom'>, 'config': {'title': 'OptionCustom'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.origin_type.OptionCustom'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.origin_type.OptionCustom'>>]}, 'ref': 'kittycad.models.origin_type.OptionCustom:94467866280912', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'origin': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'custom', 'schema': {'expected': ['custom'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionCustom', 'type': 'model-fields'}, 'type': 'model'}, 'global': {'cls': <class 'kittycad.models.origin_type.OptionGlobal'>, 'config': {'title': 'OptionGlobal'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.origin_type.OptionGlobal'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.origin_type.OptionGlobal'>>]}, 'ref': 'kittycad.models.origin_type.OptionGlobal:94467866274192', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'global', 'schema': {'expected': ['global'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionGlobal', 'type': 'model-fields'}, 'type': 'model'}, 'local': {'cls': <class 'kittycad.models.origin_type.OptionLocal'>, 'config': {'title': 'OptionLocal'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.origin_type.OptionLocal'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.origin_type.OptionLocal'>>]}, 'ref': 'kittycad.models.origin_type.OptionLocal:94467864572976', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'local', 'schema': {'expected': ['local'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionLocal', 'type': 'model-fields'}, 'type': 'model'}}, 'discriminator': 'type', 'from_attributes': True, 'metadata': {}, 'strict': False, 'type': 'tagged-union'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'Rotation', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'default'}, 'type': 'model-field'}, 'scale': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': {'x': 1.0, 'y': 1.0, 'z': 1.0}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'default'}, 'type': 'model-field'}, 'translate': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': {'x': 0.0, 'y': 0.0, 'z': 0.0}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'Transform', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_linear_pattern_transform', 'schema': {'expected': ['entity_linear_pattern_transform'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityLinearPatternTransform', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a6abd0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "transform": SerField {                         key_py: Py(                             0x00007fa14e4f7db0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Model(                                         ModelSerializer {                                             class: Py(                                                 0x000055eb039de3a0,                                             ),                                             serializer: Fields(                                                 GeneralFieldsSerializer {                                                     fields: {                                                         "replicate": SerField {                                                             key_py: Py(                                                                 0x00007fa14d85ce30,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 WithDefault(                                                                     WithDefaultSerializer {                                                                         default: Default(                                                                             Py(                                                                                 0x00007fa14f930d00,                                                                             ),                                                                         ),                                                                         serializer: Bool(                                                                             BoolSerializer,                                                                         ),                                                                     },                                                                 ),                                                             ),                                                             required: true,                                                         },                                                         "rotation": SerField {                                                             key_py: Py(                                                                 0x00007fa14d68d8b0,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 WithDefault(                                                                     WithDefaultSerializer {                                                                         default: Default(                                                                             Py(                                                                                 0x00007fa14afd5580,                                                                             ),                                                                         ),                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb039d5fe0,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "origin": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3aa98,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Model(                                                                                                         ModelSerializer {                                                                                                             class: Py(                                                                                                                 0x000055eb039d04d0,                                                                                                             ),                                                                                                             serializer: TaggedUnion(                                                                                                                 TaggedUnionSerializer {                                                                                                                     discriminator: LookupKey(                                                                                                                         Simple {                                                                                                                             key: "type",                                                                                                                             py_key: Py(                                                                                                                                 0x00007fa14fa3c5a0,                                                                                                                             ),                                                                                                                             path: LookupPath(                                                                                                                                 [                                                                                                                                     S(                                                                                                                                         "type",                                                                                                                                         Py(                                                                                                                                             0x00007fa14fa3c5a0,                                                                                                                                         ),                                                                                                                                     ),                                                                                                                                 ],                                                                                                                             ),                                                                                                                         },                                                                                                                     ),                                                                                                                     lookup: {                                                                                                                         "global": 1,                                                                                                                         "local": 0,                                                                                                                         "custom": 2,                                                                                                                     },                                                                                                                     choices: [                                                                                                                         Model(                                                                                                                             ModelSerializer {                                                                                                                                 class: Py(                                                                                                                                     0x000055eb0382b430,                                                                                                                                 ),                                                                                                                                 serializer: Fields(                                                                                                                                     GeneralFieldsSerializer {                                                                                                                                         fields: {                                                                                                                                             "type": SerField {                                                                                                                                                 key_py: Py(                                                                                                                                                     0x00007fa14fa3c5a0,                                                                                                                                                 ),                                                                                                                                                 alias: None,                                                                                                                                                 alias_py: None,                                                                                                                                                 serializer: Some(                                                                                                                                                     WithDefault(                                                                                                                                                         WithDefaultSerializer {                                                                                                                                                             default: Default(                                                                                                                                                                 Py(                                                                                                                                                                     0x00007fa14e946dc0,                                                                                                                                                                 ),                                                                                                                                                             ),                                                                                                                                                             serializer: Literal(                                                                                                                                                                 LiteralSerializer {                                                                                                                                                                     expected_int: {},                                                                                                                                                                     expected_str: {                                                                                                                                                                         "local",                                                                                                                                                                     },                                                                                                                                                                     expected_py: None,                                                                                                                                                                     name: "literal['local']",                                                                                                                                                                 },                                                                                                                                                             ),                                                                                                                                                         },                                                                                                                                                     ),                                                                                                                                                 ),                                                                                                                                                 required: true,                                                                                                                                             },                                                                                                                                         },                                                                                                                                         computed_fields: Some(                                                                                                                                             ComputedFields(                                                                                                                                                 [],                                                                                                                                             ),                                                                                                                                         ),                                                                                                                                         mode: SimpleDict,                                                                                                                                         extra_serializer: None,                                                                                                                                         filter: SchemaFilter {                                                                                                                                             include: None,                                                                                                                                             exclude: None,                                                                                                                                         },                                                                                                                                         required_fields: 1,                                                                                                                                     },                                                                                                                                 ),                                                                                                                                 has_extra: false,                                                                                                                                 root_model: false,                                                                                                                                 name: "OptionLocal",                                                                                                                             },                                                                                                                         ),                                                                                                                         Model(                                                                                                                             ModelSerializer {                                                                                                                                 class: Py(                                                                                                                                     0x000055eb039ca990,                                                                                                                                 ),                                                                                                                                 serializer: Fields(                                                                                                                                     GeneralFieldsSerializer {                                                                                                                                         fields: {                                                                                                                                             "type": SerField {                                                                                                                                                 key_py: Py(                                                                                                                                                     0x00007fa14fa3c5a0,                                                                                                                                                 ),                                                                                                                                                 alias: None,                                                                                                                                                 alias_py: None,                                                                                                                                                 serializer: Some(                                                                                                                                                     WithDefault(                                                                                                                                                         WithDefaultSerializer {                                                                                                                                                             default: Default(                                                                                                                                                                 Py(                                                                                                                                                                     0x00007fa14eb89380,                                                                                                                                                                 ),                                                                                                                                                             ),                                                                                                                                                             serializer: Literal(                                                                                                                                                                 LiteralSerializer {                                                                                                                                                                     expected_int: {},                                                                                                                                                                     expected_str: {                                                                                                                                                                         "global",                                                                                                                                                                     },                                                                                                                                                                     expected_py: None,                                                                                                                                                                     name: "literal['global']",                                                                                                                                                                 },                                                                                                                                                             ),                                                                                                                                                         },                                                                                                                                                     ),                                                                                                                                                 ),                                                                                                                                                 required: true,                                                                                                                                             },                                                                                                                                         },                                                                                                                                         computed_fields: Some(                                                                                                                                             ComputedFields(                                                                                                                                                 [],                                                                                                                                             ),                                                                                                                                         ),                                                                                                                                         mode: SimpleDict,                                                                                                                                         extra_serializer: None,                                                                                                                                         filter: SchemaFilter {                                                                                                                                             include: None,                                                                                                                                             exclude: None,                                                                                                                                         },                                                                                                                                         required_fields: 1,                                                                                                                                     },                                                                                                                                 ),                                                                                                                                 has_extra: false,                                                                                                                                 root_model: false,                                                                                                                                 name: "OptionGlobal",                                                                                                                             },                                                                                                                         ),                                                                                                                         Model(                                                                                                                             ModelSerializer {                                                                                                                                 class: Py(                                                                                                                                     0x000055eb039cc3d0,                                                                                                                                 ),                                                                                                                                 serializer: Fields(                                                                                                                                     GeneralFieldsSerializer {                                                                                                                                         fields: {                                                                                                                                             "origin": SerField {                                                                                                                                                 key_py: Py(                                                                                                                                                     0x00007fa14fa3aa98,                                                                                                                                                 ),                                                                                                                                                 alias: None,                                                                                                                                                 alias_py: None,                                                                                                                                                 serializer: Some(                                                                                                                                                     Recursive(                                                                                                                                                         DefinitionRefSerializer {                                                                                                                                                             definition: "...",                                                                                                                                                             retry_with_lax_check: true,                                                                                                                                                         },                                                                                                                                                     ),                                                                                                                                                 ),                                                                                                                                                 required: true,                                                                                                                                             },                                                                                                                                             "type": SerField {                                                                                                                                                 key_py: Py(                                                                                                                                                     0x00007fa14fa3c5a0,                                                                                                                                                 ),                                                                                                                                                 alias: None,                                                                                                                                                 alias_py: None,                                                                                                                                                 serializer: Some(                                                                                                                                                     WithDefault(                                                                                                                                                         WithDefaultSerializer {                                                                                                                                                             default: Default(                                                                                                                                                                 Py(                                                                                                                                                                     0x00007fa14afd39c0,                                                                                                                                                                 ),                                                                                                                                                             ),                                                                                                                                                             serializer: Literal(                                                                                                                                                                 LiteralSerializer {                                                                                                                                                                     expected_int: {},                                                                                                                                                                     expected_str: {                                                                                                                                                                         "custom",                                                                                                                                                                     },                                                                                                                                                                     expected_py: None,                                                                                                                                                                     name: "literal['custom']",                                                                                                                                                                 },                                                                                                                                                             ),                                                                                                                                                         },                                                                                                                                                     ),                                                                                                                                                 ),                                                                                                                                                 required: true,                                                                                                                                             },                                                                                                                                         },                                                                                                                                         computed_fields: Some(                                                                                                                                             ComputedFields(                                                                                                                                                 [],                                                                                                                                             ),                                                                                                                                         ),                                                                                                                                         mode: SimpleDict,                                                                                                                                         extra_serializer: None,                                                                                                                                         filter: SchemaFilter {                                                                                                                                             include: None,                                                                                                                                             exclude: None,                                                                                                                                         },                                                                                                                                         required_fields: 2,                                                                                                                                     },                                                                                                                                 ),                                                                                                                                 has_extra: false,                                                                                                                                 root_model: false,                                                                                                                                 name: "OptionCustom",                                                                                                                             },                                                                                                                         ),                                                                                                                     ],                                                                                                                     name: "TaggedUnion[OptionLocal, OptionGlobal, OptionCustom]",                                                                                                                 },                                                                                                             ),                                                                                                             has_extra: false,                                                                                                             root_model: true,                                                                                                             name: "RootModel[Annotated[Union[OptionLocal, OptionGlobal, OptionCustom], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "angle": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14d9ed140,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Model(                                                                                                         ModelSerializer {                                                                                                             class: Py(                                                                                                                 0x000055eb035e4800,                                                                                                             ),                                                                                                             serializer: Fields(                                                                                                                 GeneralFieldsSerializer {                                                                                                                     fields: {                                                                                                                         "value": SerField {                                                                                                                             key_py: Py(                                                                                                                                 0x00007fa14fa3c768,                                                                                                                             ),                                                                                                                             alias: None,                                                                                                                             alias_py: None,                                                                                                                             serializer: Some(                                                                                                                                 Float(                                                                                                                                     FloatSerializer {                                                                                                                                         inf_nan_mode: Null,                                                                                                                                     },                                                                                                                                 ),                                                                                                                             ),                                                                                                                             required: true,                                                                                                                         },                                                                                                                         "unit": SerField {                                                                                                                             key_py: Py(                                                                                                                                 0x00007fa14e161380,                                                                                                                             ),                                                                                                                             alias: None,                                                                                                                             alias_py: None,                                                                                                                             serializer: Some(                                                                                                                                 Enum(                                                                                                                                     EnumSerializer {                                                                                                                                         class: Py(                                                                                                                                             0x000055eb03355390,                                                                                                                                         ),                                                                                                                                         serializer: Some(                                                                                                                                             Str(                                                                                                                                                 StrSerializer,                                                                                                                                             ),                                                                                                                                         ),                                                                                                                                     },                                                                                                                                 ),                                                                                                                             ),                                                                                                                             required: true,                                                                                                                         },                                                                                                                     },                                                                                                                     computed_fields: Some(                                                                                                                         ComputedFields(                                                                                                                             [],                                                                                                                         ),                                                                                                                     ),                                                                                                                     mode: SimpleDict,                                                                                                                     extra_serializer: None,                                                                                                                     filter: SchemaFilter {                                                                                                                         include: None,                                                                                                                         exclude: None,                                                                                                                     },                                                                                                                     required_fields: 2,                                                                                                                 },                                                                                                             ),                                                                                                             has_extra: false,                                                                                                             root_model: false,                                                                                                             name: "Angle",                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "axis": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14c13dce0,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Recursive(                                                                                                         DefinitionRefSerializer {                                                                                                             definition: "...",                                                                                                             retry_with_lax_check: true,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 3,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "Rotation",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             ),                                                             required: true,                                                         },                                                         "scale": SerField {                                                             key_py: Py(                                                                 0x00007fa14e088d20,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 WithDefault(                                                                     WithDefaultSerializer {                                                                         default: Default(                                                                             Py(                                                                                 0x00007fa14afe2440,                                                                             ),                                                                         ),                                                                         serializer: Recursive(                                                                             DefinitionRefSerializer {                                                                                 definition: "...",                                                                                 retry_with_lax_check: true,                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             ),                                                             required: true,                                                         },                                                         "translate": SerField {                                                             key_py: Py(                                                                 0x00007fa14fa3c4a0,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 WithDefault(                                                                     WithDefaultSerializer {                                                                         default: Default(                                                                             Py(                                                                                 0x00007fa14afd6b00,                                                                             ),                                                                         ),                                                                         serializer: Recursive(                                                                             DefinitionRefSerializer {                                                                                 definition: "...",                                                                                 retry_with_lax_check: true,                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             ),                                                             required: true,                                                         },                                                     },                                                     computed_fields: Some(                                                         ComputedFields(                                                             [],                                                         ),                                                     ),                                                     mode: SimpleDict,                                                     extra_serializer: None,                                                     filter: SchemaFilter {                                                         include: None,                                                         exclude: None,                                                     },                                                     required_fields: 4,                                                 },                                             ),                                             has_extra: false,                                             root_model: false,                                             name: "Transform",                                         },                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[Transform]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2a1f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_linear_pattern_transform",                                             },                                             expected_py: None,                                             name: "literal['entity_linear_pattern_transform']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityLinearPatternTransform",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55eb0330e750), serializer: Fields(GeneralFieldsSerializer { fields: {"z": SerField { key_py: Py(0x7fa14fa3e1a0), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7fa14fa3e140), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7fa14fa3e170), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityLinearPatternTransform", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14aec5270,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14aec5230,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "transform",                         lookup_key: Simple {                             key: "transform",                             py_key: Py(                                 0x00007fa14aec5430,                             ),                             path: LookupPath(                                 [                                     S(                                         "transform",                                         Py(                                             0x00007fa14aec5470,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e4f7db0,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Model(                                         ModelValidator {                                             revalidate: Never,                                             validator: ModelFields(                                                 ModelFieldsValidator {                                                     fields: [                                                         Field {                                                             name: "replicate",                                                             lookup_key: Simple {                                                                 key: "replicate",                                                                 py_key: Py(                                                                     0x00007fa14aec52f0,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "replicate",                                                                             Py(                                                                                 0x00007fa14aec52b0,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fa14d85ce30,                                                             ),                                                             validator: WithDefault(                                                                 WithDefaultValidator {                                                                     default: Default(                                                                         Py(                                                                             0x00007fa14f930d00,                                                                         ),                                                                     ),                                                                     on_error: Raise,                                                                     validator: Bool(                                                                         BoolValidator {                                                                             strict: false,                                                                         },                                                                     ),                                                                     validate_default: false,                                                                     copy_default: false,                                                                     name: "default[bool]",                                                                     undefined: Py(                                                                         0x00007fa14d802350,                                                                     ),                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                         Field {                                                             name: "rotation",                                                             lookup_key: Simple {                                                                 key: "rotation",                                                                 py_key: Py(                                                                     0x00007fa14aec5330,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "rotation",                                                                             Py(                                                                                 0x00007fa14aec5370,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fa14d68d8b0,                                                             ),                                                             validator: WithDefault(                                                                 WithDefaultValidator {                                                                     default: Default(                                                                         Py(                                                                             0x00007fa14afd5580,                                                                         ),                                                                     ),                                                                     on_error: Raise,                                                                     validator: Model(                                                                         ModelValidator {                                                                             revalidate: Never,                                                                             validator: ModelFields(                                                                                 ModelFieldsValidator {                                                                                     fields: [                                                                                         Field {                                                                                             name: "angle",                                                                                             lookup_key: Simple {                                                                                                 key: "angle",                                                                                                 py_key: Py(                                                                                                     0x00007fa14b023930,                                                                                                 ),                                                                                                 path: LookupPath(                                                                                                     [                                                                                                         S(                                                                                                             "angle",                                                                                                             Py(                                                                                                                 0x00007fa14b023960,                                                                                                             ),                                                                                                         ),                                                                                                     ],                                                                                                 ),                                                                                             },                                                                                             name_py: Py(                                                                                                 0x00007fa14d9ed140,                                                                                             ),                                                                                             validator: Model(                                                                                                 ModelValidator {                                                                                                     revalidate: Never,                                                                                                     validator: ModelFields(                                                                                                         ModelFieldsValidator {                                                                                                             fields: [                                                                                                                 Field {                                                                                                                     name: "unit",                                                                                                                     lookup_key: Simple {                                                                                                                         key: "unit",                                                                                                                         py_key: Py(                                                                                                                             0x00007fa14b023870,                                                                                                                         ),                                                                                                                         path: LookupPath(                                                                                                                             [                                                                                                                                 S(                                                                                                                                     "unit",                                                                                                                                     Py(                                                                                                                                         0x00007fa14b0238a0,                                                                                                                                     ),                                                                                                                                 ),                                                                                                                             ],                                                                                                                         ),                                                                                                                     },                                                                                                                     name_py: Py(                                                                                                                         0x00007fa14e161380,                                                                                                                     ),                                                                                                                     validator: StrEnum(                                                                                                                         EnumValidator {                                                                                                                             phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                                                             class: Py(                                                                                                                                 0x000055eb03355390,                                                                                                                             ),                                                                                                                             lookup: LiteralLookup {                                                                                                                                 expected_bool: None,                                                                                                                                 expected_int: None,                                                                                                                                 expected_str: Some(                                                                                                                                     {                                                                                                                                         "degrees": 0,                                                                                                                                         "radians": 1,                                                                                                                                     },                                                                                                                                 ),                                                                                                                                 expected_py_dict: None,                                                                                                                                 expected_py_values: None,                                                                                                                                 values: [                                                                                                                                     Py(                                                                                                                                         0x00007fa14b361850,                                                                                                                                     ),                                                                                                                                     Py(                                                                                                                                         0x00007fa14b3618b0,                                                                                                                                     ),                                                                                                                                 ],                                                                                                                             },                                                                                                                             missing: None,                                                                                                                             expected_repr: "'degrees' or 'radians'",                                                                                                                             strict: false,                                                                                                                             class_repr: "UnitAngle",                                                                                                                             name: "str-enum[UnitAngle]",                                                                                                                         },                                                                                                                     ),                                                                                                                     frozen: false,                                                                                                                 },                                                                                                                 Field {                                                                                                                     name: "value",                                                                                                                     lookup_key: Simple {                                                                                                                         key: "value",                                                                                                                         py_key: Py(                                                                                                                             0x00007fa14b0238d0,                                                                                                                         ),                                                                                                                         path: LookupPath(                                                                                                                             [                                                                                                                                 S(                                                                                                                                     "value",                                                                                                                                     Py(                                                                                                                                         0x00007fa14b023900,                                                                                                                                     ),                                                                                                                                 ),                                                                                                                             ],                                                                                                                         ),                                                                                                                     },                                                                                                                     name_py: Py(                                                                                                                         0x00007fa14fa3c768,                                                                                                                     ),                                                                                                                     validator: Float(                                                                                                                         FloatValidator {                                                                                                                             strict: false,                                                                                                                             allow_inf_nan: true,                                                                                                                         },                                                                                                                     ),                                                                                                                     frozen: false,                                                                                                                 },                                                                                                             ],                                                                                                             model_name: "Angle",                                                                                                             extra_behavior: Ignore,                                                                                                             extras_validator: None,                                                                                                             strict: false,                                                                                                             from_attributes: false,                                                                                                             loc_by_alias: true,                                                                                                         },                                                                                                     ),                                                                                                     class: Py(                                                                                                         0x000055eb035e4800,                                                                                                     ),                                                                                                     post_init: None,                                                                                                     frozen: false,                                                                                                     custom_init: false,                                                                                                     root_model: false,                                                                                                     undefined: Py(                                                                                                         0x00007fa14d802350,                                                                                                     ),                                                                                                     name: "Angle",                                                                                                 },                                                                                             ),                                                                                             frozen: false,                                                                                         },                                                                                         Field {                                                                                             name: "axis",                                                                                             lookup_key: Simple {                                                                                                 key: "axis",                                                                                                 py_key: Py(                                                                                                     0x00007fa14b023990,                                                                                                 ),                                                                                                 path: LookupPath(                                                                                                     [                                                                                                         S(                                                                                                             "axis",                                                                                                             Py(                                                                                                                 0x00007fa14b0239c0,                                                                                                             ),                                                                                                         ),                                                                                                     ],                                                                                                 ),                                                                                             },                                                                                             name_py: Py(                                                                                                 0x00007fa14c13dce0,                                                                                             ),                                                                                             validator: DefinitionRef(                                                                                                 DefinitionRefValidator {                                                                                                     definition: "Point3d",                                                                                                 },                                                                                             ),                                                                                             frozen: false,                                                                                         },                                                                                         Field {                                                                                             name: "origin",                                                                                             lookup_key: Simple {                                                                                                 key: "origin",                                                                                                 py_key: Py(                                                                                                     0x00007fa14b023b70,                                                                                                 ),                                                                                                 path: LookupPath(                                                                                                     [                                                                                                         S(                                                                                                             "origin",                                                                                                             Py(                                                                                                                 0x00007fa14b023ba0,                                                                                                             ),                                                                                                         ),                                                                                                     ],                                                                                                 ),                                                                                             },                                                                                             name_py: Py(                                                                                                 0x00007fa14fa3aa98,                                                                                             ),                                                                                             validator: Model(                                                                                                 ModelValidator {                                                                                                     revalidate: Never,                                                                                                     validator: TaggedUnion(                                                                                                         TaggedUnionValidator {                                                                                                             discriminator: LookupKey(                                                                                                                 Simple {                                                                                                                     key: "type",                                                                                                                     py_key: Py(                                                                                                                         0x00007fa14fa3c5a0,                                                                                                                     ),                                                                                                                     path: LookupPath(                                                                                                                         [                                                                                                                             S(                                                                                                                                 "type",                                                                                                                                 Py(                                                                                                                                     0x00007fa14fa3c5a0,                                                                                                                                 ),                                                                                                                             ),                                                                                                                         ],                                                                                                                     ),                                                                                                                 },                                                                                                             ),                                                                                                             lookup: LiteralLookup {                                                                                                                 expected_bool: None,                                                                                                                 expected_int: None,                                                                                                                 expected_str: Some(                                                                                                                     {                                                                                                                         "global": 1,                                                                                                                         "custom": 2,                                                                                                                         "local": 0,                                                                                                                     },                                                                                                                 ),                                                                                                                 expected_py_dict: None,                                                                                                                 expected_py_values: None,                                                                                                                 values: [                                                                                                                     Model(                                                                                                                         ModelValidator {                                                                                                                             revalidate: Never,                                                                                                                             validator: ModelFields(                                                                                                                                 ModelFieldsValidator {                                                                                                                                     fields: [                                                                                                                                         Field {                                                                                                                                             name: "type",                                                                                                                                             lookup_key: Simple {                                                                                                                                                 key: "type",                                                                                                                                                 py_key: Py(                                                                                                                                                     0x00007fa14b0239f0,                                                                                                                                                 ),                                                                                                                                                 path: LookupPath(                                                                                                                                                     [                                                                                                                                                         S(                                                                                                                                                             "type",                                                                                                                                                             Py(                                                                                                                                                                 0x00007fa14b023a20,                                                                                                                                                             ),                                                                                                                                                         ),                                                                                                                                                     ],                                                                                                                                                 ),                                                                                                                                             },                                                                                                                                             name_py: Py(                                                                                                                                                 0x00007fa14fa3c5a0,                                                                                                                                             ),                                                                                                                                             validator: WithDefault(                                                                                                                                                 WithDefaultValidator {                                                                                                                                                     default: Default(                                                                                                                                                         Py(                                                                                                                                                             0x00007fa14e946dc0,                                                                                                                                                         ),                                                                                                                                                     ),                                                                                                                                                     on_error: Raise,                                                                                                                                                     validator: Literal(                                                                                                                                                         LiteralValidator {                                                                                                                                                             lookup: LiteralLookup {                                                                                                                                                                 expected_bool: None,                                                                                                                                                                 expected_int: None,                                                                                                                                                                 expected_str: Some(                                                                                                                                                                     {                                                                                                                                                                         "local": 0,                                                                                                                                                                     },                                                                                                                                                                 ),                                                                                                                                                                 expected_py_dict: None,                                                                                                                                                                 expected_py_values: None,                                                                                                                                                                 values: [                                                                                                                                                                     Py(                                                                                                                                                                         0x00007fa14e946dc0,                                                                                                                                                                     ),                                                                                                                                                                 ],                                                                                                                                                             },                                                                                                                                                             expected_repr: "'local'",                                                                                                                                                             name: "literal['local']",                                                                                                                                                         },                                                                                                                                                     ),                                                                                                                                                     validate_default: false,                                                                                                                                                     copy_default: false,                                                                                                                                                     name: "default[literal['local']]",                                                                                                                                                     undefined: Py(                                                                                                                                                         0x00007fa14d802350,                                                                                                                                                     ),                                                                                                                                                 },                                                                                                                                             ),                                                                                                                                             frozen: false,                                                                                                                                         },                                                                                                                                     ],                                                                                                                                     model_name: "OptionLocal",                                                                                                                                     extra_behavior: Ignore,                                                                                                                                     extras_validator: None,                                                                                                                                     strict: false,                                                                                                                                     from_attributes: false,                                                                                                                                     loc_by_alias: true,                                                                                                                                 },                                                                                                                             ),                                                                                                                             class: Py(                                                                                                                                 0x000055eb0382b430,                                                                                                                             ),                                                                                                                             post_init: None,                                                                                                                             frozen: false,                                                                                                                             custom_init: false,                                                                                                                             root_model: false,                                                                                                                             undefined: Py(                                                                                                                                 0x00007fa14d802350,                                                                                                                             ),                                                                                                                             name: "OptionLocal",                                                                                                                         },                                                                                                                     ),                                                                                                                     Model(                                                                                                                         ModelValidator {                                                                                                                             revalidate: Never,                                                                                                                             validator: ModelFields(                                                                                                                                 ModelFieldsValidator {                                                                                                                                     fields: [                                                                                                                                         Field {                                                                                                                                             name: "type",                                                                                                                                             lookup_key: Simple {                                                                                                                                                 key: "type",                                                                                                                                                 py_key: Py(                                                                                                                                                     0x00007fa14b023a50,                                                                                                                                                 ),                                                                                                                                                 path: LookupPath(                                                                                                                                                     [                                                                                                                                                         S(                                                                                                                                                             "type",                                                                                                                                                             Py(                                                                                                                                                                 0x00007fa14b023a80,                                                                                                                                                             ),                                                                                                                                                         ),                                                                                                                                                     ],                                                                                                                                                 ),                                                                                                                                             },                                                                                                                                             name_py: Py(                                                                                                                                                 0x00007fa14fa3c5a0,                                                                                                                                             ),                                                                                                                                             validator: WithDefault(                                                                                                                                                 WithDefaultValidator {                                                                                                                                                     default: Default(                                                                                                                                                         Py(                                                                                                                                                             0x00007fa14eb89380,                                                                                                                                                         ),                                                                                                                                                     ),                                                                                                                                                     on_error: Raise,                                                                                                                                                     validator: Literal(                                                                                                                                                         LiteralValidator {                                                                                                                                                             lookup: LiteralLookup {                                                                                                                                                                 expected_bool: None,                                                                                                                                                                 expected_int: None,                                                                                                                                                                 expected_str: Some(                                                                                                                                                                     {                                                                                                                                                                         "global": 0,                                                                                                                                                                     },                                                                                                                                                                 ),                                                                                                                                                                 expected_py_dict: None,                                                                                                                                                                 expected_py_values: None,                                                                                                                                                                 values: [                                                                                                                                                                     Py(                                                                                                                                                                         0x00007fa14eb89380,                                                                                                                                                                     ),                                                                                                                                                                 ],                                                                                                                                                             },                                                                                                                                                             expected_repr: "'global'",                                                                                                                                                             name: "literal['global']",                                                                                                                                                         },                                                                                                                                                     ),                                                                                                                                                     validate_default: false,                                                                                                                                                     copy_default: false,                                                                                                                                                     name: "default[literal['global']]",                                                                                                                                                     undefined: Py(                                                                                                                                                         0x00007fa14d802350,                                                                                                                                                     ),                                                                                                                                                 },                                                                                                                                             ),                                                                                                                                             frozen: false,                                                                                                                                         },                                                                                                                                     ],                                                                                                                                     model_name: "OptionGlobal",                                                                                                                                     extra_behavior: Ignore,                                                                                                                                     extras_validator: None,                                                                                                                                     strict: false,                                                                                                                                     from_attributes: false,                                                                                                                                     loc_by_alias: true,                                                                                                                                 },                                                                                                                             ),                                                                                                                             class: Py(                                                                                                                                 0x000055eb039ca990,                                                                                                                             ),                                                                                                                             post_init: None,                                                                                                                             frozen: false,                                                                                                                             custom_init: false,                                                                                                                             root_model: false,                                                                                                                             undefined: Py(                                                                                                                                 0x00007fa14d802350,                                                                                                                             ),                                                                                                                             name: "OptionGlobal",                                                                                                                         },                                                                                                                     ),                                                                                                                     Model(                                                                                                                         ModelValidator {                                                                                                                             revalidate: Never,                                                                                                                             validator: ModelFields(                                                                                                                                 ModelFieldsValidator {                                                                                                                                     fields: [                                                                                                                                         Field {                                                                                                                                             name: "origin",                                                                                                                                             lookup_key: Simple {                                                                                                                                                 key: "origin",                                                                                                                                                 py_key: Py(                                                                                                                                                     0x00007fa14b023ab0,                                                                                                                                                 ),                                                                                                                                                 path: LookupPath(                                                                                                                                                     [                                                                                                                                                         S(                                                                                                                                                             "origin",                                                                                                                                                             Py(                                                                                                                                                                 0x00007fa14b023ae0,                                                                                                                                                             ),                                                                                                                                                         ),                                                                                                                                                     ],                                                                                                                                                 ),                                                                                                                                             },                                                                                                                                             name_py: Py(                                                                                                                                                 0x00007fa14fa3aa98,                                                                                                                                             ),                                                                                                                                             validator: DefinitionRef(                                                                                                                                                 DefinitionRefValidator {                                                                                                                                                     definition: "Point3d",                                                                                                                                                 },                                                                                                                                             ),                                                                                                                                             frozen: false,                                                                                                                                         },                                                                                                                                         Field {                                                                                                                                             name: "type",                                                                                                                                             lookup_key: Simple {                                                                                                                                                 key: "type",                                                                                                                                                 py_key: Py(                                                                                                                                                     0x00007fa14b023b10,                                                                                                                                                 ),                                                                                                                                                 path: LookupPath(                                                                                                                                                     [                                                                                                                                                         S(                                                                                                                                                             "type",                                                                                                                                                             Py(                                                                                                                                                                 0x00007fa14b023b40,                                                                                                                                                             ),                                                                                                                                                         ),                                                                                                                                                     ],                                                                                                                                                 ),                                                                                                                                             },                                                                                                                                             name_py: Py(                                                                                                                                                 0x00007fa14fa3c5a0,                                                                                                                                             ),                                                                                                                                             validator: WithDefault(                                                                                                                                                 WithDefaultValidator {                                                                                                                                                     default: Default(                                                                                                                                                         Py(                                                                                                                                                             0x00007fa14afd39c0,                                                                                                                                                         ),                                                                                                                                                     ),                                                                                                                                                     on_error: Raise,                                                                                                                                                     validator: Literal(                                                                                                                                                         LiteralValidator {                                                                                                                                                             lookup: LiteralLookup {                                                                                                                                                                 expected_bool: None,                                                                                                                                                                 expected_int: None,                                                                                                                                                                 expected_str: Some(                                                                                                                                                                     {                                                                                                                                                                         "custom": 0,                                                                                                                                                                     },                                                                                                                                                                 ),                                                                                                                                                                 expected_py_dict: None,                                                                                                                                                                 expected_py_values: None,                                                                                                                                                                 values: [                                                                                                                                                                     Py(                                                                                                                                                                         0x00007fa14afd39c0,                                                                                                                                                                     ),                                                                                                                                                                 ],                                                                                                                                                             },                                                                                                                                                             expected_repr: "'custom'",                                                                                                                                                             name: "literal['custom']",                                                                                                                                                         },                                                                                                                                                     ),                                                                                                                                                     validate_default: false,                                                                                                                                                     copy_default: false,                                                                                                                                                     name: "default[literal['custom']]",                                                                                                                                                     undefined: Py(                                                                                                                                                         0x00007fa14d802350,                                                                                                                                                     ),                                                                                                                                                 },                                                                                                                                             ),                                                                                                                                             frozen: false,                                                                                                                                         },                                                                                                                                     ],                                                                                                                                     model_name: "OptionCustom",                                                                                                                                     extra_behavior: Ignore,                                                                                                                                     extras_validator: None,                                                                                                                                     strict: false,                                                                                                                                     from_attributes: false,                                                                                                                                     loc_by_alias: true,                                                                                                                                 },                                                                                                                             ),                                                                                                                             class: Py(                                                                                                                                 0x000055eb039cc3d0,                                                                                                                             ),                                                                                                                             post_init: None,                                                                                                                             frozen: false,                                                                                                                             custom_init: false,                                                                                                                             root_model: false,                                                                                                                             undefined: Py(                                                                                                                                 0x00007fa14d802350,                                                                                                                             ),                                                                                                                             name: "OptionCustom",                                                                                                                         },                                                                                                                     ),                                                                                                                 ],                                                                                                             },                                                                                                             from_attributes: true,                                                                                                             strict: false,                                                                                                             custom_error: None,                                                                                                             tags_repr: "'local', 'global', 'custom'",                                                                                                             discriminator_repr: "'type'",                                                                                                             name: "tagged-union[OptionLocal,OptionGlobal,OptionCustom]",                                                                                                         },                                                                                                     ),                                                                                                     class: Py(                                                                                                         0x000055eb039d04d0,                                                                                                     ),                                                                                                     post_init: None,                                                                                                     frozen: false,                                                                                                     custom_init: false,                                                                                                     root_model: true,                                                                                                     undefined: Py(                                                                                                         0x00007fa14d802350,                                                                                                     ),                                                                                                     name: "RootModel[Annotated[Union[OptionLocal, OptionGlobal, OptionCustom], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                                                                                                 },                                                                                             ),                                                                                             frozen: false,                                                                                         },                                                                                     ],                                                                                     model_name: "Rotation",                                                                                     extra_behavior: Ignore,                                                                                     extras_validator: None,                                                                                     strict: false,                                                                                     from_attributes: false,                                                                                     loc_by_alias: true,                                                                                 },                                                                             ),                                                                             class: Py(                                                                                 0x000055eb039d5fe0,                                                                             ),                                                                             post_init: None,                                                                             frozen: false,                                                                             custom_init: false,                                                                             root_model: false,                                                                             undefined: Py(                                                                                 0x00007fa14d802350,                                                                             ),                                                                             name: "Rotation",                                                                         },                                                                     ),                                                                     validate_default: false,                                                                     copy_default: true,                                                                     name: "default[Rotation]",                                                                     undefined: Py(                                                                         0x00007fa14d802350,                                                                     ),                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                         Field {                                                             name: "scale",                                                             lookup_key: Simple {                                                                 key: "scale",                                                                 py_key: Py(                                                                     0x00007fa14b023bd0,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "scale",                                                                             Py(                                                                                 0x00007fa14b023c00,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fa14e088d20,                                                             ),                                                             validator: WithDefault(                                                                 WithDefaultValidator {                                                                     default: Default(                                                                         Py(                                                                             0x00007fa14afe2440,                                                                         ),                                                                     ),                                                                     on_error: Raise,                                                                     validator: DefinitionRef(                                                                         DefinitionRefValidator {                                                                             definition: "Point3d",                                                                         },                                                                     ),                                                                     validate_default: false,                                                                     copy_default: true,                                                                     name: "default[Point3d]",                                                                     undefined: Py(                                                                         0x00007fa14d802350,                                                                     ),                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                         Field {                                                             name: "translate",                                                             lookup_key: Simple {                                                                 key: "translate",                                                                 py_key: Py(                                                                     0x00007fa14aec53b0,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "translate",                                                                             Py(                                                                                 0x00007fa14aec53f0,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fa14fa3c4a0,                                                             ),                                                             validator: WithDefault(                                                                 WithDefaultValidator {                                                                     default: Default(                                                                         Py(                                                                             0x00007fa14afd6b00,                                                                         ),                                                                     ),                                                                     on_error: Raise,                                                                     validator: DefinitionRef(                                                                         DefinitionRefValidator {                                                                             definition: "Point3d",                                                                         },                                                                     ),                                                                     validate_default: false,                                                                     copy_default: true,                                                                     name: "default[Point3d]",                                                                     undefined: Py(                                                                         0x00007fa14d802350,                                                                     ),                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                     ],                                                     model_name: "Transform",                                                     extra_behavior: Ignore,                                                     extras_validator: None,                                                     strict: false,                                                     from_attributes: false,                                                     loc_by_alias: true,                                                 },                                             ),                                             class: Py(                                                 0x000055eb039de3a0,                                             ),                                             post_init: None,                                             frozen: false,                                             custom_init: false,                                             root_model: false,                                             undefined: Py(                                                 0x00007fa14d802350,                                             ),                                             name: "Transform",                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b023c30,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b023c60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2a1f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_linear_pattern_transform": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2a1f0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_linear_pattern_transform'",                                         name: "literal['entity_linear_pattern_transform']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_linear_pattern_transform']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityLinearPatternTransform",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a6abd0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityLinearPatternTransform",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fa14fa3e140), path: LookupPath([S("x", Py(0x7fa14fa3e140))]) }, name_py: Py(0x7fa14fa3e140), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fa14fa3e170), path: LookupPath([S("y", Py(0x7fa14fa3e170))]) }, name_py: Py(0x7fa14fa3e170), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fa14fa3e1a0), path: LookupPath([S("z", Py(0x7fa14fa3e1a0))]) }, name_py: Py(0x7fa14fa3e1a0), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb0330e750), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_id: str, transform: List[kittycad.models.transform.Transform], type: Literal['entity_linear_pattern_transform'] = 'entity_linear_pattern_transform') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_id': FieldInfo(annotation=str, required=True), 'transform': FieldInfo(annotation=List[Transform], required=True), 'type': FieldInfo(annotation=Literal['entity_linear_pattern_transform'], required=False, default='entity_linear_pattern_transform')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

transform: List[Transform]

type: Literal['entity_linear_pattern_transform']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityMakeHelix(**data)

Create a helix using the input cylinder and other specified parameters.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'cylinder_id': <class 'str'>, 'is_clockwise': <class 'bool'>, 'length': <class 'kittycad.models.length_unit.LengthUnit'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'revolutions': <class 'float'>, 'start_angle': <class 'kittycad.models.angle.Angle'>, 'type': typing.Literal['entity_make_helix']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityMakeHelix'>, 'config': {'title': 'OptionEntityMakeHelix'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityMakeHelix'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityMakeHelix'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityMakeHelix:94467866954016', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'cylinder_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'is_clockwise': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'length': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'revolutions': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'start_angle': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.angle.Angle'>, 'config': {'title': 'Angle'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.angle.Angle'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.angle.Angle'>>]}, 'ref': 'kittycad.models.angle.Angle:94467862185984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitAngle'>, 'members': [UnitAngle.DEGREES, UnitAngle.RADIANS], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_angle.UnitAngle:94467859501968', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'value': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Angle', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_make_helix', 'schema': {'expected': ['entity_make_helix'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityMakeHelix', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a70920,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "length": SerField {                         key_py: Py(                             0x00007fa14fa39ba8,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "start_angle": SerField {                         key_py: Py(                             0x00007fa14aff69b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb035e4800,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "value": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3c768,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "unit": SerField {                                                     key_py: Py(                                                         0x00007fa14e161380,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055eb03355390,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Angle",                                 },                             ),                         ),                         required: true,                     },                     "cylinder_id": SerField {                         key_py: Py(                             0x00007fa14aff68b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "is_clockwise": SerField {                         key_py: Py(                             0x00007fa14aff68f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "revolutions": SerField {                         key_py: Py(                             0x00007fa14aff6930,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4df30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_make_helix",                                             },                                             expected_py: None,                                             name: "literal['entity_make_helix']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 6,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityMakeHelix",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityMakeHelix", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "cylinder_id",                         lookup_key: Simple {                             key: "cylinder_id",                             py_key: Py(                                 0x00007fa14c2f2f30,                             ),                             path: LookupPath(                                 [                                     S(                                         "cylinder_id",                                         Py(                                             0x00007fa14c2f33b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff68b0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "is_clockwise",                         lookup_key: Simple {                             key: "is_clockwise",                             py_key: Py(                                 0x00007fa14c2f2e70,                             ),                             path: LookupPath(                                 [                                     S(                                         "is_clockwise",                                         Py(                                             0x00007fa14c2f30f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff68f0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "length",                         lookup_key: Simple {                             key: "length",                             py_key: Py(                                 0x00007fa14afe5680,                             ),                             path: LookupPath(                                 [                                     S(                                         "length",                                         Py(                                             0x00007fa14afe58f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa39ba8,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14c2f1c00,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "revolutions",                         lookup_key: Simple {                             key: "revolutions",                             py_key: Py(                                 0x00007fa14c2f2cf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "revolutions",                                         Py(                                             0x00007fa14c2f3170,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6930,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "start_angle",                         lookup_key: Simple {                             key: "start_angle",                             py_key: Py(                                 0x00007fa14c2f3370,                             ),                             path: LookupPath(                                 [                                     S(                                         "start_angle",                                         Py(                                             0x00007fa14c2f1530,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff69b0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "unit",                                                 lookup_key: Simple {                                                     key: "unit",                                                     py_key: Py(                                                         0x00007fa14afe6100,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "unit",                                                                 Py(                                                                     0x00007fa14afe6a00,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14e161380,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055eb03355390,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "degrees": 0,                                                                     "radians": 1,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             values: [                                                                 Py(                                                                     0x00007fa14b361850,                                                                 ),                                                                 Py(                                                                     0x00007fa14b3618b0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'degrees' or 'radians'",                                                         strict: false,                                                         class_repr: "UnitAngle",                                                         name: "str-enum[UnitAngle]",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "value",                                                 lookup_key: Simple {                                                     key: "value",                                                     py_key: Py(                                                         0x00007fa14afe5cb0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "value",                                                                 Py(                                                                     0x00007fa14afe70f0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3c768,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Angle",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb035e4800,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Angle",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe6670,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe6580,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4df30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_make_helix": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4df30,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_make_helix'",                                         name: "literal['entity_make_helix']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_make_helix']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityMakeHelix",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a70920,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityMakeHelix",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, cylinder_id: str, is_clockwise: bool, length: kittycad.models.length_unit.LengthUnit, revolutions: float, start_angle: kittycad.models.angle.Angle, type: Literal['entity_make_helix'] = 'entity_make_helix') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

cylinder_id: str

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

is_clockwise: bool

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

length: LengthUnit

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'cylinder_id': FieldInfo(annotation=str, required=True), 'is_clockwise': FieldInfo(annotation=bool, required=True), 'length': FieldInfo(annotation=LengthUnit, required=True), 'revolutions': FieldInfo(annotation=float, required=True), 'start_angle': FieldInfo(annotation=Angle, required=True), 'type': FieldInfo(annotation=Literal['entity_make_helix'], required=False, default='entity_make_helix')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

revolutions: float

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

start_angle: Angle

type: Literal['entity_make_helix']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityMirror(**data)

Mirror the input entities over the specified axis. (Currently only supports sketches)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'axis': <class 'kittycad.models.point3d.Point3d'>, 'ids': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'point': <class 'kittycad.models.point3d.Point3d'>, 'type': typing.Literal['entity_mirror']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityMirror'>, 'config': {'title': 'OptionEntityMirror'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityMirror'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityMirror'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityMirror:94467867042688', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'point': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_mirror', 'schema': {'expected': ['entity_mirror'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityMirror', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a86380,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "ids": SerField {                         key_py: Py(                             0x00007fa14e9d8c60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "point": SerField {                         key_py: Py(                             0x00007fa14d77f600,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4dfb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_mirror",                                             },                                             expected_py: None,                                             name: "literal['entity_mirror']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "axis": SerField {                         key_py: Py(                             0x00007fa14c13dce0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityMirror",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55eb0330e750), serializer: Fields(GeneralFieldsSerializer { fields: {"x": SerField { key_py: Py(0x7fa14fa3e140), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7fa14fa3e170), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7fa14fa3e1a0), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityMirror", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "axis",                         lookup_key: Simple {                             key: "axis",                             py_key: Py(                                 0x00007fa14c12bba0,                             ),                             path: LookupPath(                                 [                                     S(                                         "axis",                                         Py(                                             0x00007fa14c12bb70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14c13dce0,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "ids",                         lookup_key: Simple {                             key: "ids",                             py_key: Py(                                 0x00007fa14c12bb40,                             ),                             path: LookupPath(                                 [                                     S(                                         "ids",                                         Py(                                             0x00007fa14b024210,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e9d8c60,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "point",                         lookup_key: Simple {                             key: "point",                             py_key: Py(                                 0x00007fa14b0241e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "point",                                         Py(                                             0x00007fa14b024270,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d77f600,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b0240c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b024030,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4dfb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_mirror": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4dfb0,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_mirror'",                                         name: "literal['entity_mirror']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_mirror']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityMirror",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a86380,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityMirror",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fa14fa3e140), path: LookupPath([S("x", Py(0x7fa14fa3e140))]) }, name_py: Py(0x7fa14fa3e140), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fa14fa3e170), path: LookupPath([S("y", Py(0x7fa14fa3e170))]) }, name_py: Py(0x7fa14fa3e170), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fa14fa3e1a0), path: LookupPath([S("z", Py(0x7fa14fa3e1a0))]) }, name_py: Py(0x7fa14fa3e1a0), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb0330e750), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, axis: kittycad.models.point3d.Point3d, ids: List[str], point: kittycad.models.point3d.Point3d, type: Literal['entity_mirror'] = 'entity_mirror') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

axis: Point3d

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

ids: List[str]

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'axis': FieldInfo(annotation=Point3d, required=True), 'ids': FieldInfo(annotation=List[str], required=True), 'point': FieldInfo(annotation=Point3d, required=True), 'type': FieldInfo(annotation=Literal['entity_mirror'], required=False, default='entity_mirror')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

point: Point3d

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_mirror']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntityMirrorAcrossEdge(**data)

Mirror the input entities over the specified edge. (Currently only supports sketches)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'edge_id': <class 'str'>, 'ids': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['entity_mirror_across_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntityMirrorAcrossEdge'>, 'config': {'title': 'OptionEntityMirrorAcrossEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntityMirrorAcrossEdge'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntityMirrorAcrossEdge'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntityMirrorAcrossEdge:94467850108288', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_mirror_across_edge', 'schema': {'expected': ['entity_mirror_across_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntityMirrorAcrossEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb02a5fd80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "ids": SerField {                         key_py: Py(                             0x00007fa14e9d8c60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2a150,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_mirror_across_edge",                                             },                                             expected_py: None,                                             name: "literal['entity_mirror_across_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntityMirrorAcrossEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntityMirrorAcrossEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14b0234e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14b023db0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "ids",                         lookup_key: Simple {                             key: "ids",                             py_key: Py(                                 0x00007fa14b023f60,                             ),                             path: LookupPath(                                 [                                     S(                                         "ids",                                         Py(                                             0x00007fa14b022760,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e9d8c60,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b0224f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b0218f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2a150,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_mirror_across_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2a150,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_mirror_across_edge'",                                         name: "literal['entity_mirror_across_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_mirror_across_edge']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntityMirrorAcrossEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb02a5fd80,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntityMirrorAcrossEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, edge_id: str, ids: List[str], type: Literal['entity_mirror_across_edge'] = 'entity_mirror_across_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

classmethod from_orm(obj)

Return type:

Self

ids: List[str]

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'edge_id': FieldInfo(annotation=str, required=True), 'ids': FieldInfo(annotation=List[str], required=True), 'type': FieldInfo(annotation=Literal['entity_mirror_across_edge'], required=False, default='entity_mirror_across_edge')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_mirror_across_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionEntitySetOpacity(**data)

Set opacity of the entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'opacity': <class 'float'>, 'type': typing.Literal['entity_set_opacity']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionEntitySetOpacity'>, 'config': {'title': 'OptionEntitySetOpacity'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionEntitySetOpacity'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionEntitySetOpacity'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionEntitySetOpacity:94467867573008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'opacity': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'entity_set_opacity', 'schema': {'expected': ['entity_set_opacity'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionEntitySetOpacity', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b07b10,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4e130,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "entity_set_opacity",                                             },                                             expected_py: None,                                             name: "literal['entity_set_opacity']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "opacity": SerField {                         key_py: Py(                             0x00007fa14e088870,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionEntitySetOpacity",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionEntitySetOpacity", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14aebb370,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14ad3ebb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "opacity",                         lookup_key: Simple {                             key: "opacity",                             py_key: Py(                                 0x00007fa14ae76ac0,                             ),                             path: LookupPath(                                 [                                     S(                                         "opacity",                                         Py(                                             0x00007fa14ae76a60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e088870,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae745d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae745a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4e130,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "entity_set_opacity": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4e130,                                                 ),                                             ],                                         },                                         expected_repr: "'entity_set_opacity'",                                         name: "literal['entity_set_opacity']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['entity_set_opacity']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionEntitySetOpacity",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b07b10,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionEntitySetOpacity",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_id: str, opacity: float, type: Literal['entity_set_opacity'] = 'entity_set_opacity') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_id': FieldInfo(annotation=str, required=True), 'opacity': FieldInfo(annotation=float, required=True), 'type': FieldInfo(annotation=Literal['entity_set_opacity'], required=False, default='entity_set_opacity')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

opacity: float

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['entity_set_opacity']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionExport(**data)

Export the scene to a file.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_ids': typing.List[str], 'format': <class 'pydantic.root_model.RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['export']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.axis_direction_pair.AxisDirectionPair'>, 'config': {'title': 'AxisDirectionPair'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.axis_direction_pair.AxisDirectionPair'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.axis_direction_pair.AxisDirectionPair'>>]}, 'ref': 'kittycad.models.axis_direction_pair.AxisDirectionPair:94467855533120', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.axis.Axis:94467855528000', 'type': 'definition-ref'}, 'type': 'model-field'}, 'direction': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.direction.Direction:94467855530560', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'AxisDirectionPair', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <enum 'Axis'>, 'members': [Axis.Y, Axis.Z], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.axis.Axis:94467855528000', 'sub_type': 'str', 'type': 'enum'}, {'cls': <enum 'Direction'>, 'members': [Direction.POSITIVE, Direction.NEGATIVE], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.direction.Direction:94467855530560', 'sub_type': 'str', 'type': 'enum'}, {'cls': <class 'kittycad.models.system.System'>, 'config': {'title': 'System'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.system.System'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.system.System'>>]}, 'ref': 'kittycad.models.system.System:94467861035232', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'forward': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.axis_direction_pair.AxisDirectionPair:94467855533120', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.axis_direction_pair.AxisDirectionPair:94467855533120', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'System', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <enum 'UnitLength'>, 'members': [UnitLength.CM, UnitLength.FT, UnitLength.IN, UnitLength.M, UnitLength.MM, UnitLength.YD], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_length.UnitLength:94467861018320', 'sub_type': 'str', 'type': 'enum'}, {'cls': <class 'kittycad.models.selection.OptionDefaultScene'>, 'config': {'title': 'OptionDefaultScene'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.selection.OptionDefaultScene'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.selection.OptionDefaultScene'>>]}, 'ref': 'kittycad.models.selection.OptionDefaultScene:94467862099456', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'default_scene', 'schema': {'expected': ['default_scene'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionDefaultScene', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <class 'kittycad.models.selection.OptionSceneByIndex'>, 'config': {'title': 'OptionSceneByIndex'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.selection.OptionSceneByIndex'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.selection.OptionSceneByIndex'>>]}, 'ref': 'kittycad.models.selection.OptionSceneByIndex:94467862123456', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'index': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'scene_by_index', 'schema': {'expected': ['scene_by_index'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSceneByIndex', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <class 'kittycad.models.selection.OptionSceneByName'>, 'config': {'title': 'OptionSceneByName'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.selection.OptionSceneByName'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.selection.OptionSceneByName'>>]}, 'ref': 'kittycad.models.selection.OptionSceneByName:94467862131408', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'name': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'scene_by_name', 'schema': {'expected': ['scene_by_name'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSceneByName', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <class 'kittycad.models.selection.OptionMeshByIndex'>, 'config': {'title': 'OptionMeshByIndex'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.selection.OptionMeshByIndex'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.selection.OptionMeshByIndex'>>]}, 'ref': 'kittycad.models.selection.OptionMeshByIndex:94467862113408', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'index': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'mesh_by_index', 'schema': {'expected': ['mesh_by_index'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMeshByIndex', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <class 'kittycad.models.selection.OptionMeshByName'>, 'config': {'title': 'OptionMeshByName'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.selection.OptionMeshByName'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.selection.OptionMeshByName'>>]}, 'ref': 'kittycad.models.selection.OptionMeshByName:94467861678960', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'name': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'mesh_by_name', 'schema': {'expected': 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title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'pydantic.root_model.RootModel[Annotated[Union[OptionDefaultScene, OptionSceneByIndex, OptionSceneByName, OptionMeshByIndex, OptionMeshByName], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>>]}, 'ref': "pydantic.root_model.RootModel:94467864067568[Annotated[Union[OptionDefaultScene, OptionSceneByIndex, OptionSceneByName, OptionMeshByIndex, OptionMeshByName], FieldInfo(annotation=NoneType, required=True, discriminator='type')]:140330737852128]", 'root_model': True, 'schema': {'choices': {'default_scene': {'schema_ref': 'kittycad.models.selection.OptionDefaultScene:94467862099456', 'type': 'definition-ref'}, 'mesh_by_index': {'schema_ref': 'kittycad.models.selection.OptionMeshByIndex:94467862113408', 'type': 'definition-ref'}, 'mesh_by_name': {'schema_ref': 'kittycad.models.selection.OptionMeshByName:94467861678960', 'type': 'definition-ref'}, 'scene_by_index': {'schema_ref': 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'model_name': 'OptionFbx', 'type': 'model-fields'}, 'type': 'model'}, 'gltf': {'cls': <class 'kittycad.models.output_format.OptionGltf'>, 'config': {'title': 'OptionGltf'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.output_format.OptionGltf'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.output_format.OptionGltf'>>]}, 'ref': 'kittycad.models.output_format.OptionGltf:94467861737840', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'presentation': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'GltfPresentation'>, 'members': [GltfPresentation.COMPACT, GltfPresentation.PRETTY], 'metadata': {'pydantic_js_functions': [<function 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{'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.system.System:94467861035232', 'type': 'definition-ref'}, 'type': 'model-field'}, 'selection': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': "pydantic.root_model.RootModel:94467864067568[Annotated[Union[OptionDefaultScene, OptionSceneByIndex, OptionSceneByName, OptionMeshByIndex, OptionMeshByName], FieldInfo(annotation=NoneType, required=True, discriminator='type')]:140330737852128]", 'type': 'definition-ref'}, 'type': 'model-field'}, 'storage': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'StlStorage'>, 'members': [StlStorage.ASCII, StlStorage.BINARY], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.stl_storage.StlStorage:94467861712896', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'stl', 'schema': {'expected': ['stl'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'units': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.unit_length.UnitLength:94467861018320', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'OptionStl', 'type': 'model-fields'}, 'type': 'model'}}, 'discriminator': 'type', 'from_attributes': True, 'metadata': {}, 'strict': False, 'type': 'tagged-union'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'export', 'schema': {'expected': ['export'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExport', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a3ed70,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_ids": SerField {                         key_py: Py(                             0x00007fa14b038970,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14e164660,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "export",                                             },                                             expected_py: None,                                             name: "literal['export']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "format": SerField {                         key_py: Py(                             0x00007fa14fa38b50,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0365a4c0,                                     ),                                     serializer: TaggedUnion(                                         TaggedUnionSerializer {                                             discriminator: LookupKey(                                                 Simple {                                                     key: "type",                                                     py_key: Py(                                                         0x00007fa14fa3c5a0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "type",                                                                 Py(                                                                     0x00007fa14fa3c5a0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                             ),                                             lookup: {                                                 "step": 4,                                                 "fbx": 0,                                                 "obj": 2,                                                 "stl": 5,                                                 "ply": 3,                                                 "gltf": 1,                                             },                                             choices: [                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb03574d20,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "storage": SerField {                                                                         key_py: Py(                                                                             0x00007fa14d76d020,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Enum(                                                                                 EnumSerializer {                                                                                     class: Py(                                                                                         0x000055eb035cceb0,                                                                                     ),                                                                                     serializer: Some(                                                                                         Str(                                                                                             StrSerializer,                                                                                         ),                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd71170,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "fbx",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['fbx']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 2,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionFbx",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb03577170,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "storage": SerField {                                                                         key_py: Py(                                                                             0x00007fa14d76d020,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Enum(                                                                                 EnumSerializer {                                                                                     class: Py(                                                                                         0x000055eb035ce200,                                                                                     ),                                                                                     serializer: Some(                                                                                         Str(                                                                                             StrSerializer,                                                                                         ),                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd710e0,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "gltf",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['gltf']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "presentation": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bb506b0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Enum(                                                                                 EnumSerializer {                                                                                     class: Py(                                                                                         0x000055eb035cdb10,                                                                                     ),                                                                                     serializer: Some(                                                                                         Str(                                                                                             StrSerializer,                                                                                         ),                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 3,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionGltf",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb0357af90,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "coords": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14fa3a760,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "obj",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['obj']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "units": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: false,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 3,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionObj",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb02f373e0,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd71b00,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "ply",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['ply']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "units": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: false,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "storage": SerField {                                                                         key_py: Py(                                                                             0x00007fa14d76d020,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Enum(                                                                                 EnumSerializer {                                                                                     class: Py(                                                                                         0x000055eb035cec00,                                                                                     ),                                                                                     serializer: Some(                                                                                         Str(                                                                                             StrSerializer,                                                                                         ),                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "selection": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd7bbf0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "coords": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 5,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionPly",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb02f46690,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "coords": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14fa3be10,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "step",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['step']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 2,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionStep",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb02f4b6a0,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "selection": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd7bbf0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "coords": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "storage": SerField {                                                                         key_py: Py(                                                                             0x00007fa14d76d020,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Enum(                                                                                 EnumSerializer {                                                                                     class: Py(                                                                                         0x000055eb03571000,                                                                                     ),                                                                                     serializer: Some(                                                                                         Str(                                                                                             StrSerializer,                                                                                         ),                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "units": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: false,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd71ce0,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "stl",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['stl']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 5,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionStl",                                                     },                                                 ),                                             ],                                             name: "TaggedUnion[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionStep, OptionStl]",                                         },                                     ),                                     has_extra: false,                                     root_model: true,                                     name: "RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionExport",     }, ), definitions=[Enum(EnumSerializer { class: Py(0x55eb02f8b040), serializer: Some(Str(StrSerializer)) }), Model(ModelSerializer { class: Py(0x55eb035cf600), serializer: Fields(GeneralFieldsSerializer { fields: {"type": SerField { key_py: Py(0x7fa14fa3c5a0), alias: None, alias_py: None, serializer: Some(WithDefault(WithDefaultSerializer { default: Default(Py(0x7fa14bb4ecf0)), serializer: Literal(LiteralSerializer { expected_int: {}, expected_str: {"default_scene"}, expected_py: None, name: "literal['default_scene']" }) })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 1 }), has_extra: false, root_model: false, name: "OptionDefaultScene" }), Model(ModelSerializer { class: Py(0x55eb02f8c440), serializer: Fields(GeneralFieldsSerializer { fields: {"direction": SerField { key_py: Py(0x7fa14e41ef30), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: false })), required: true }, "axis": SerField { key_py: Py(0x7fa14c13dce0), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: false })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "AxisDirectionPair" }), Model(ModelSerializer { class: Py(0x55eb034cb8e0), serializer: Fields(GeneralFieldsSerializer { fields: {"up": SerField { key_py: Py(0x7fa14d9ed0b0), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true })), required: true }, "forward": SerField { key_py: Py(0x7fa14bd71cb0), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "System" }), Enum(EnumSerializer { class: Py(0x55eb034c76d0), serializer: Some(Str(StrSerializer)) }), Model(ModelSerializer { class: Py(0x55eb035d72d0), serializer: Fields(GeneralFieldsSerializer { fields: {"name": SerField { key_py: Py(0x7fa14fa3a388), alias: None, alias_py: None, serializer: Some(Str(StrSerializer)), required: true }, "type": SerField { key_py: Py(0x7fa14fa3c5a0), alias: None, alias_py: None, serializer: Some(WithDefault(WithDefaultSerializer { default: Default(Py(0x7fa14bb4cd70)), serializer: Literal(LiteralSerializer { expected_int: {}, expected_str: {"scene_by_name"}, expected_py: None, name: "literal['scene_by_name']" }) })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "OptionSceneByName" }), Model(ModelSerializer { class: Py(0x55eb035d2c80), serializer: Fields(GeneralFieldsSerializer { fields: {"type": SerField { key_py: Py(0x7fa14fa3c5a0), alias: None, alias_py: None, serializer: Some(WithDefault(WithDefaultSerializer { default: Default(Py(0x7fa14bb51570)), serializer: Literal(LiteralSerializer { expected_int: {}, expected_str: {"mesh_by_index"}, expected_py: None, name: "literal['mesh_by_index']" }) })), required: true }, "index": SerField { key_py: Py(0x7fa14f9faac0), alias: None, alias_py: None, serializer: Some(Int(IntSerializer)), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "OptionMeshByIndex" }), Model(ModelSerializer { class: Py(0x55eb033f6d30), serializer: TaggedUnion(TaggedUnionSerializer { discriminator: LookupKey(Simple { key: "type", py_key: Py(0x7fa14fa3c5a0), path: LookupPath([S("type", Py(0x7fa14fa3c5a0))]) }), lookup: {"default_scene": 0, "scene_by_name": 2, "scene_by_index": 1, "mesh_by_index": 3, "mesh_by_name": 4}, choices: [Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true }), Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true }), Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true }), Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true }), Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true })], name: "TaggedUnion[definition-ref, definition-ref, definition-ref, definition-ref, definition-ref]" }), has_extra: false, root_model: true, name: "RootModel[Annotated[Union[OptionDefaultScene, OptionSceneByIndex, OptionSceneByName, OptionMeshByIndex, OptionMeshByName], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]" }), Model(ModelSerializer { class: Py(0x55eb035d53c0), serializer: Fields(GeneralFieldsSerializer { fields: {"type": SerField { key_py: Py(0x7fa14fa3c5a0), alias: None, alias_py: None, serializer: Some(WithDefault(WithDefaultSerializer { default: Default(Py(0x7fa14bb4caf0)), serializer: Literal(LiteralSerializer { expected_int: {}, expected_str: {"scene_by_index"}, expected_py: None, name: "literal['scene_by_index']" }) })), required: true }, "index": SerField { key_py: Py(0x7fa14f9faac0), alias: None, alias_py: None, serializer: Some(Int(IntSerializer)), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "OptionSceneByIndex" }), Enum(EnumSerializer { class: Py(0x55eb02f8ba40), serializer: Some(Str(StrSerializer)) }), Model(ModelSerializer { class: Py(0x55eb03568b70), serializer: Fields(GeneralFieldsSerializer { fields: {"name": SerField { key_py: Py(0x7fa14fa3a388), alias: None, alias_py: None, serializer: Some(Str(StrSerializer)), required: true }, "type": SerField { key_py: Py(0x7fa14fa3c5a0), alias: None, alias_py: None, serializer: Some(WithDefault(WithDefaultSerializer { default: Default(Py(0x7fa14bb516f0)), serializer: Literal(LiteralSerializer { expected_int: {}, expected_str: {"mesh_by_name"}, expected_py: None, name: "literal['mesh_by_name']" }) })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "OptionMeshByName" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExport", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_ids",                         lookup_key: Simple {                             key: "entity_ids",                             py_key: Py(                                 0x00007fa14b09ae70,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_ids",                                         Py(                                             0x00007fa14b100730,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b038970,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "format",                         lookup_key: Simple {                             key: "format",                             py_key: Py(                                 0x00007fa14b021d40,                             ),                             path: LookupPath(                                 [                                     S(                                         "format",                                         Py(                                             0x00007fa14b021c50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa38b50,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: TaggedUnion(                                     TaggedUnionValidator {                                         discriminator: LookupKey(                                             Simple {                                                 key: "type",                                                 py_key: Py(                                                     0x00007fa14fa3c5a0,                                                 ),                                                 path: LookupPath(                                                     [                                                         S(                                                             "type",                                                             Py(                                                                 0x00007fa14fa3c5a0,                                                             ),                                                         ),                                                     ],                                                 ),                                             },                                         ),                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "ply": 3,                                                     "obj": 2,                                                     "fbx": 0,                                                     "gltf": 1,                                                     "step": 4,                                                     "stl": 5,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "storage",                                                                         lookup_key: Simple {                                                                             key: "storage",                                                                             py_key: Py(                                                                                 0x00007fa14b0206f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "storage",                                                                                         Py(                                                                                             0x00007fa14b0205d0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14d76d020,                                                                         ),                                                                         validator: StrEnum(                                                                             EnumValidator {                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                 class: Py(                                                                                     0x000055eb035cceb0,                                                                                 ),                                                                                 lookup: LiteralLookup {                                                                                     expected_bool: None,                                                                                     expected_int: None,                                                                                     expected_str: Some(                                                                                         {                                                                                             "binary": 1,                                                                                             "ascii": 0,                                                                                         },                                                                                     ),                                                                                     expected_py_dict: None,                                                                                     expected_py_values: None,                                                                                     values: [                                                                                         Py(                                                                                             0x00007fa14b3c5f10,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b3c6090,                                                                                         ),                                                                                     ],                                                                                 },                                                                                 missing: None,                                                                                 expected_repr: "'ascii' or 'binary'",                                                                                 strict: false,                                                                                 class_repr: "FbxStorage",                                                                                 name: "str-enum[FbxStorage]",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14b020b70,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14b020990,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd71170,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "fbx": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd71170,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'fbx'",                                                                                         name: "literal['fbx']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['fbx']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionFbx",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb03574d20,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionFbx",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "presentation",                                                                         lookup_key: Simple {                                                                             key: "presentation",                                                                             py_key: Py(                                                                                 0x00007fa14ae3b2f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "presentation",                                                                                         Py(                                                                                             0x00007fa14ae38730,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bb506b0,                                                                         ),                                                                         validator: StrEnum(                                                                             EnumValidator {                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                 class: Py(                                                                                     0x000055eb035cdb10,                                                                                 ),                                                                                 lookup: LiteralLookup {                                                                                     expected_bool: None,                                                                                     expected_int: None,                                                                                     expected_str: Some(                                                                                         {                                                                                             "compact": 0,                                                                                             "pretty": 1,                                                                                         },                                                                                     ),                                                                                     expected_py_dict: None,                                                                                     expected_py_values: None,                                                                                     values: [                                                                                         Py(                                                                                             0x00007fa14b3c6150,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b3c6210,                                                                                         ),                                                                                     ],                                                                                 },                                                                                 missing: None,                                                                                 expected_repr: "'compact' or 'pretty'",                                                                                 strict: false,                                                                                 class_repr: "GltfPresentation",                                                                                 name: "str-enum[GltfPresentation]",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "storage",                                                                         lookup_key: Simple {                                                                             key: "storage",                                                                             py_key: Py(                                                                                 0x00007fa14b0208a0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "storage",                                                                                         Py(                                                                                             0x00007fa14b0208d0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14d76d020,                                                                         ),                                                                         validator: StrEnum(                                                                             EnumValidator {                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                 class: Py(                                                                                     0x000055eb035ce200,                                                                                 ),                                                                                 lookup: LiteralLookup {                                                                                     expected_bool: None,                                                                                     expected_int: None,                                                                                     expected_str: Some(                                                                                         {                                                                                             "embedded": 2,                                                                                             "binary": 0,                                                                                             "standard": 1,                                                                                         },                                                                                     ),                                                                                     expected_py_dict: None,                                                                                     expected_py_values: None,                                                                                     values: [                                                                                         Py(                                                                                             0x00007fa14b3c62d0,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b3c6390,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b3c6450,                                                                                         ),                                                                                     ],                                                                                 },                                                                                 missing: None,                                                                                 expected_repr: "'binary', 'standard' or 'embedded'",                                                                                 strict: false,                                                                                 class_repr: "GltfStorage",                                                                                 name: "str-enum[GltfStorage]",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14b0206c0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14b0205a0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd710e0,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "gltf": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd710e0,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'gltf'",                                                                                         name: "literal['gltf']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['gltf']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionGltf",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb03577170,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionGltf",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "coords",                                                                         lookup_key: Simple {                                                                             key: "coords",                                                                             py_key: Py(                                                                                 0x00007fa14b020a20,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "coords",                                                                                         Py(                                                                                             0x00007fa14b020a50,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14b020a80,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14b021bf0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14fa3a760,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "obj": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14fa3a760,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'obj'",                                                                                         name: "literal['obj']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['obj']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "units",                                                                         lookup_key: Simple {                                                                             key: "units",                                                                             py_key: Py(                                                                                 0x00007fa14b0217d0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "units",                                                                                         Py(                                                                                             0x00007fa14b0217a0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionObj",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb0357af90,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionObj",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "coords",                                                                         lookup_key: Simple {                                                                             key: "coords",                                                                             py_key: Py(                                                                                 0x00007fa14b0218c0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "coords",                                                                                         Py(                                                                                             0x00007fa14b021980,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "selection",                                                                         lookup_key: Simple {                                                                             key: "selection",                                                                             py_key: Py(                                                                                 0x00007fa14ae2d830,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "selection",                                                                                         Py(                                                                                             0x00007fa14ae73230,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd7bbf0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "storage",                                                                         lookup_key: Simple {                                                                             key: "storage",                                                                             py_key: Py(                                                                                 0x00007fa14b021920,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "storage",                                                                                         Py(                                                                                             0x00007fa14b021a70,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14d76d020,                                                                         ),                                                                         validator: StrEnum(                                                                             EnumValidator {                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                 class: Py(                                                                                     0x000055eb035cec00,                                                                                 ),                                                                                 lookup: LiteralLookup {                                                                                     expected_bool: None,                                                                                     expected_int: None,                                                                                     expected_str: Some(                                                                                         {                                                                                             "ascii": 0,                                                                                             "binary_little_endian": 1,                                                                                             "binary_big_endian": 2,                                                                                         },                                                                                     ),                                                                                     expected_py_dict: None,                                                                                     expected_py_values: None,                                                                                     values: [                                                                                         Py(                                                                                             0x00007fa14b3c64b0,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b3c6510,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b3c6570,                                                                                         ),                                                                                     ],                                                                                 },                                                                                 missing: None,                                                                                 expected_repr: "'ascii', 'binary_little_endian' or 'binary_big_endian'",                                                                                 strict: false,                                                                                 class_repr: "PlyStorage",                                                                                 name: "str-enum[PlyStorage]",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14b021a40,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14b0219b0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd71b00,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "ply": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd71b00,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'ply'",                                                                                         name: "literal['ply']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['ply']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "units",                                                                         lookup_key: Simple {                                                                             key: "units",                                                                             py_key: Py(                                                                                 0x00007fa14b021950,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "units",                                                                                         Py(                                                                                             0x00007fa14b0219e0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionPly",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb02f373e0,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionPly",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "coords",                                                                         lookup_key: Simple {                                                                             key: "coords",                                                                             py_key: Py(                                                                                 0x00007fa14b021a10,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "coords",                                                                                         Py(                                                                                             0x00007fa14b021b00,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14b021aa0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14b021c20,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14fa3be10,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "step": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14fa3be10,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'step'",                                                                                         name: "literal['step']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['step']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionStep",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb02f46690,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionStep",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "coords",                                                                         lookup_key: Simple {                                                                             key: "coords",                                                                             py_key: Py(                                                                                 0x00007fa14b021b60,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "coords",                                                                                         Py(                                                                                             0x00007fa14b021b90,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "selection",                                                                         lookup_key: Simple {                                                                             key: "selection",                                                                             py_key: Py(                                                                                 0x00007fa14ae735b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "selection",                                                                                         Py(                                                                                             0x00007fa14ae71730,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd7bbf0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "storage",                                                                         lookup_key: Simple {                                                                             key: "storage",                                                                             py_key: Py(                                                                                 0x00007fa14b021bc0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "storage",                                                                                         Py(                                                                                             0x00007fa14b021e60,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14d76d020,                                                                         ),                                                                         validator: StrEnum(                                                                             EnumValidator {                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                 class: Py(                                                                                     0x000055eb03571000,                                                                                 ),                                                                                 lookup: LiteralLookup {                                                                                     expected_bool: None,                                                                                     expected_int: None,                                                                                     expected_str: Some(                                                                                         {                                                                                             "ascii": 0,                                                                                             "binary": 1,                                                                                         },                                                                                     ),                                                                                     expected_py_dict: None,                                                                                     expected_py_values: None,                                                                                     values: [                                                                                         Py(                                                                                             0x00007fa14b3c6ab0,                                                                                         ),                                                                                         Py(                                                                                             0x00007fa14b3c6b10,                                                                                         ),                                                                                     ],                                                                                 },                                                                                 missing: None,                                                                                 expected_repr: "'ascii' or 'binary'",                                                                                 strict: false,                                                                                 class_repr: "StlStorage",                                                                                 name: "str-enum[StlStorage]",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14b021e90,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14b021dd0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd71ce0,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "stl": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd71ce0,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'stl'",                                                                                         name: "literal['stl']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['stl']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "units",                                                                         lookup_key: Simple {                                                                             key: "units",                                                                             py_key: Py(                                                                                 0x00007fa14b021da0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "units",                                                                                         Py(                                                                                             0x00007fa14b021cb0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionStl",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb02f4b6a0,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionStl",                                                     },                                                 ),                                             ],                                         },                                         from_attributes: true,                                         strict: false,                                         custom_error: None,                                         tags_repr: "'fbx', 'gltf', 'obj', 'ply', 'step', 'stl'",                                         discriminator_repr: "'type'",                                         name: "tagged-union[OptionFbx,OptionGltf,OptionObj,OptionPly,OptionStep,OptionStl]",                                     },                                 ),                                 class: Py(                                     0x000055eb0365a4c0,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: true,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b021c80,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b021ce0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14e164660,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "export": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14e164660,                                                 ),                                             ],                                         },                                         expected_repr: "'export'",                                         name: "literal['export']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['export']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExport",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a3ed70,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionExport",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "type", lookup_key: Simple { key: "type", py_key: Py(0x7fa14b021710), path: LookupPath([S("type", Py(0x7fa14b0212c0))]) }, name_py: Py(0x7fa14fa3c5a0), validator: WithDefault(WithDefaultValidator { default: Default(Py(0x7fa14bb4ecf0)), on_error: Raise, validator: Literal(LiteralValidator { lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"default_scene": 0}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14bb4ecf0)] }, expected_repr: "'default_scene'", name: "literal['default_scene']" }), validate_default: false, copy_default: false, name: "default[literal['default_scene']]", undefined: Py(0x7fa14d802350) }), frozen: false }], model_name: "OptionDefaultScene", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb035cf600), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "OptionDefaultScene" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "index", lookup_key: Simple { key: "index", py_key: Py(0x7fa14b021170), path: LookupPath([S("index", Py(0x7fa14b021110))]) }, name_py: Py(0x7fa14f9faac0), validator: Int(IntValidator { strict: false }), frozen: false }, Field { name: "type", lookup_key: Simple { key: "type", py_key: Py(0x7fa14b0210b0), path: LookupPath([S("type", Py(0x7fa14b021080))]) }, name_py: Py(0x7fa14fa3c5a0), validator: WithDefault(WithDefaultValidator { default: Default(Py(0x7fa14bb51570)), on_error: Raise, validator: Literal(LiteralValidator { lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"mesh_by_index": 0}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14bb51570)] }, expected_repr: "'mesh_by_index'", name: "literal['mesh_by_index']" }), validate_default: false, copy_default: false, name: "default[literal['mesh_by_index']]", undefined: Py(0x7fa14d802350) }), frozen: false }], model_name: "OptionMeshByIndex", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb035d2c80), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "OptionMeshByIndex" }), StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb02f8b040), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"z": 1, "y": 0}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b3c4e90), Py(0x7fa14b3c4ef0)] }, missing: None, expected_repr: "'y' or 'z'", strict: false, class_repr: "Axis", name: "str-enum[Axis]" }), StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb034c76d0), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"in": 2, "mm": 4, "m": 3, "cm": 0, "yd": 5, "ft": 1}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b3c4c50), Py(0x7fa14b3c51f0), Py(0x7fa14b3c52b0), Py(0x7fa14b3c5310), Py(0x7fa14b3c5370), Py(0x7fa14b3c53d0)] }, missing: None, expected_repr: "'cm', 'ft', 'in', 'm', 'mm' or 'yd'", strict: false, class_repr: "UnitLength", name: "str-enum[UnitLength]" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "axis", lookup_key: Simple { key: "axis", py_key: Py(0x7fa14afe7d50), path: LookupPath([S("axis", Py(0x7fa14afe7300))]) }, name_py: Py(0x7fa14c13dce0), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }, Field { name: "direction", lookup_key: Simple { key: "direction", py_key: Py(0x7fa14ae40630), path: LookupPath([S("direction", Py(0x7fa14b287330))]) }, name_py: Py(0x7fa14e41ef30), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }], model_name: "AxisDirectionPair", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb02f8c440), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "AxisDirectionPair" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "forward", lookup_key: Simple { key: "forward", py_key: Py(0x7fa14afe7120), path: LookupPath([S("forward", Py(0x7fa14afe7e70))]) }, name_py: Py(0x7fa14bd71cb0), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }, Field { name: "up", lookup_key: Simple { key: "up", py_key: Py(0x7fa14afe72d0), path: LookupPath([S("up", Py(0x7fa14afe7ea0))]) }, name_py: Py(0x7fa14d9ed0b0), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }], model_name: "System", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb034cb8e0), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "System" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "name", lookup_key: Simple { key: "name", py_key: Py(0x7fa14b021380), path: LookupPath([S("name", Py(0x7fa14b020fc0))]) }, name_py: Py(0x7fa14fa3a388), validator: Str(StrValidator { strict: false, coerce_numbers_to_str: false }), frozen: false }, Field { name: "type", lookup_key: Simple { key: "type", py_key: Py(0x7fa14b021020), path: LookupPath([S("type", Py(0x7fa14b020ff0))]) }, name_py: Py(0x7fa14fa3c5a0), validator: WithDefault(WithDefaultValidator { default: Default(Py(0x7fa14bb4cd70)), on_error: Raise, validator: Literal(LiteralValidator { lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"scene_by_name": 0}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14bb4cd70)] }, expected_repr: "'scene_by_name'", name: "literal['scene_by_name']" }), validate_default: false, copy_default: false, name: "default[literal['scene_by_name']]", undefined: Py(0x7fa14d802350) }), frozen: false }], model_name: "OptionSceneByName", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb035d72d0), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "OptionSceneByName" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "name", lookup_key: Simple { key: "name", py_key: Py(0x7fa14b0210e0), path: LookupPath([S("name", Py(0x7fa14b020480))]) }, name_py: Py(0x7fa14fa3a388), validator: Str(StrValidator { strict: false, coerce_numbers_to_str: false }), frozen: false }, Field { name: "type", lookup_key: Simple { key: "type", py_key: Py(0x7fa14b020ba0), path: LookupPath([S("type", Py(0x7fa14b020540))]) }, name_py: Py(0x7fa14fa3c5a0), validator: WithDefault(WithDefaultValidator { default: Default(Py(0x7fa14bb516f0)), on_error: Raise, validator: Literal(LiteralValidator { lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"mesh_by_name": 0}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14bb516f0)] }, expected_repr: "'mesh_by_name'", name: "literal['mesh_by_name']" }), validate_default: false, copy_default: false, name: "default[literal['mesh_by_name']]", undefined: Py(0x7fa14d802350) }), frozen: false }], model_name: "OptionMeshByName", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb03568b70), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "OptionMeshByName" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "index", lookup_key: Simple { key: "index", py_key: Py(0x7fa14b021350), path: LookupPath([S("index", Py(0x7fa14b021200))]) }, name_py: Py(0x7fa14f9faac0), validator: Int(IntValidator { strict: false }), frozen: false }, Field { name: "type", lookup_key: Simple { key: "type", py_key: Py(0x7fa14b021230), path: LookupPath([S("type", Py(0x7fa14b0211a0))]) }, name_py: Py(0x7fa14fa3c5a0), validator: WithDefault(WithDefaultValidator { default: Default(Py(0x7fa14bb4caf0)), on_error: Raise, validator: Literal(LiteralValidator { lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"scene_by_index": 0}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14bb4caf0)] }, expected_repr: "'scene_by_index'", name: "literal['scene_by_index']" }), validate_default: false, copy_default: false, name: "default[literal['scene_by_index']]", undefined: Py(0x7fa14d802350) }), frozen: false }], model_name: "OptionSceneByIndex", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb035d53c0), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "OptionSceneByIndex" }), StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb02f8ba40), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"negative": 1, "positive": 0}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b3c5010), Py(0x7fa14b3c5070)] }, missing: None, expected_repr: "'positive' or 'negative'", strict: false, class_repr: "Direction", name: "str-enum[Direction]" }), Model(ModelValidator { revalidate: Never, validator: TaggedUnion(TaggedUnionValidator { discriminator: LookupKey(Simple { key: "type", py_key: Py(0x7fa14fa3c5a0), path: LookupPath([S("type", Py(0x7fa14fa3c5a0))]) }), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"scene_by_name": 2, "mesh_by_index": 3, "scene_by_index": 1, "mesh_by_name": 4, "default_scene": 0}), expected_py_dict: None, expected_py_values: None, values: [DefinitionRef(DefinitionRefValidator { definition: "OptionDefaultScene" }), DefinitionRef(DefinitionRefValidator { definition: "OptionSceneByIndex" }), DefinitionRef(DefinitionRefValidator { definition: "OptionSceneByName" }), DefinitionRef(DefinitionRefValidator { definition: "OptionMeshByIndex" }), DefinitionRef(DefinitionRefValidator { definition: "OptionMeshByName" })] }, from_attributes: true, strict: false, custom_error: None, tags_repr: "'default_scene', 'scene_by_index', 'scene_by_name', 'mesh_by_index', 'mesh_by_name'", discriminator_repr: "'type'", name: "tagged-union[OptionDefaultScene,OptionSceneByIndex,OptionSceneByName,OptionMeshByIndex,OptionMeshByName]" }), class: Py(0x55eb033f6d30), post_init: None, frozen: false, custom_init: false, root_model: true, undefined: Py(0x7fa14d802350), name: "RootModel[Annotated[Union[OptionDefaultScene, OptionSceneByIndex, OptionSceneByName, OptionMeshByIndex, OptionMeshByName], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_ids: List[str], format: pydantic.root_model.RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], type: Literal['export'] = 'export') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_ids: List[str]

format: RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_ids': FieldInfo(annotation=List[str], required=True), 'format': FieldInfo(annotation=RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], required=True), 'type': FieldInfo(annotation=Literal['export'], required=False, default='export')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['export']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionExtendPath(**data)

Extend a path by adding a new segment which starts at the path’s “pen”. If no “pen” location has been set before (via MovePen), then the pen is at the origin.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'segment': <class 'pydantic.root_model.RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'type': typing.Literal['extend_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <class 'kittycad.models.angle.Angle'>, 'config': {'title': 'Angle'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.angle.Angle'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.angle.Angle'>>]}, 'ref': 'kittycad.models.angle.Angle:94467862185984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.unit_angle.UnitAngle:94467859501968', 'type': 'definition-ref'}, 'type': 'model-field'}, 'value': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Angle', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <enum 'UnitAngle'>, 'members': [UnitAngle.DEGREES, UnitAngle.RADIANS], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_angle.UnitAngle:94467859501968', 'sub_type': 'str', 'type': 'enum'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionExtendPath'>, 'config': {'title': 'OptionExtendPath'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionExtendPath'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionExtendPath'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionExtendPath:94467866450288', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'path': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'type': 'no-info'}, 'schema': {'type': 'str'}, 'type': 'function-after'}, 'type': 'model-field'}, 'segment': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'pydantic.root_model.RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'config': {'title': "RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]"}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'pydantic.root_model.RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'pydantic.root_model.RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>>]}, 'ref': "pydantic.root_model.RootModel:94467864067568[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]:140330724558272]", 'root_model': True, 'schema': {'choices': {'arc': {'cls': <class 'kittycad.models.path_segment.OptionArc'>, 'config': {'title': 'OptionArc'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.path_segment.OptionArc'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionArc'>>]}, 'ref': 'kittycad.models.path_segment.OptionArc:94467866394144', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'end': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.angle.Angle:94467862185984', 'type': 'definition-ref'}, 'type': 'model-field'}, 'radius': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'relative': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'start': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.angle.Angle:94467862185984', 'type': 'definition-ref'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'arc', 'schema': {'expected': ['arc'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionArc', 'type': 'model-fields'}, 'type': 'model'}, 'arc_to': {'cls': <class 'kittycad.models.path_segment.OptionArcTo'>, 'config': {'title': 'OptionArcTo'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.path_segment.OptionArcTo'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionArcTo'>>]}, 'ref': 'kittycad.models.path_segment.OptionArcTo:94467866154896', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'end': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'interior': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'relative': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'arc_to', 'schema': {'expected': ['arc_to'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionArcTo', 'type': 'model-fields'}, 'type': 'model'}, 'bezier': {'cls': <class 'kittycad.models.path_segment.OptionBezier'>, 'config': {'title': 'OptionBezier'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.path_segment.OptionBezier'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionBezier'>>]}, 'ref': 'kittycad.models.path_segment.OptionBezier:94467866101312', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'control1': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'control2': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'end': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'relative': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'bezier', 'schema': {'expected': ['bezier'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionBezier', 'type': 'model-fields'}, 'type': 'model'}, 'line': {'cls': <class 'kittycad.models.path_segment.OptionLine'>, 'config': {'title': 'OptionLine'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.path_segment.OptionLine'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionLine'>>]}, 'ref': 'kittycad.models.path_segment.OptionLine:94467866382016', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'end': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'relative': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'line', 'schema': {'expected': ['line'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionLine', 'type': 'model-fields'}, 'type': 'model'}, 'tangential_arc': {'cls': <class 'kittycad.models.path_segment.OptionTangentialArc'>, 'config': {'title': 'OptionTangentialArc'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.path_segment.OptionTangentialArc'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionTangentialArc'>>]}, 'ref': 'kittycad.models.path_segment.OptionTangentialArc:94467866120720', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'offset': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.angle.Angle:94467862185984', 'type': 'definition-ref'}, 'type': 'model-field'}, 'radius': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'tangential_arc', 'schema': {'expected': ['tangential_arc'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionTangentialArc', 'type': 'model-fields'}, 'type': 'model'}, 'tangential_arc_to': {'cls': <class 'kittycad.models.path_segment.OptionTangentialArcTo'>, 'config': {'title': 'OptionTangentialArcTo'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.path_segment.OptionTangentialArcTo'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionTangentialArcTo'>>]}, 'ref': 'kittycad.models.path_segment.OptionTangentialArcTo:94467866134800', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'angle_snap_increment': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'schema_ref': 'kittycad.models.angle.Angle:94467862185984', 'type': 'definition-ref'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'to': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'tangential_arc_to', 'schema': {'expected': ['tangential_arc_to'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionTangentialArcTo', 'type': 'model-fields'}, 'type': 'model'}}, 'discriminator': 'type', 'from_attributes': True, 'metadata': {}, 'strict': False, 'type': 'tagged-union'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'extend_path', 'schema': {'expected': ['extend_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExtendPath', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb039f5970,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "path": SerField {                         key_py: Py(                             0x00007fa14fa3ac30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bf7e630,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "extend_path",                                             },                                             expected_py: None,                                             name: "literal['extend_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "segment": SerField {                         key_py: Py(                             0x00007fa14e9da1f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb039b2310,                                     ),                                     serializer: TaggedUnion(                                         TaggedUnionSerializer {                                             discriminator: LookupKey(                                                 Simple {                                                     key: "type",                                                     py_key: Py(                                                         0x00007fa14fa3c5a0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "type",                                                                 Py(                                                                     0x00007fa14fa3c5a0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                             ),                                             lookup: {                                                 "arc_to": 5,                                                 "line": 0,                                                 "bezier": 2,                                                 "arc": 1,                                                 "tangential_arc": 3,                                                 "tangential_arc_to": 4,                                             },                                             choices: [                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb039e4ec0,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "end": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa38368,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14fa39c38,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "line",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['line']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "relative": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e010bf0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Bool(                                                                                 BoolSerializer,                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 3,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionLine",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb039e7e20,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "start": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3bce8,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "center": SerField {                                                                         key_py: Py(                                                                             0x00007fa14ef08150,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Model(                                                                                 ModelSerializer {                                                                                     class: Py(                                                                                         0x000055eb0399c230,                                                                                     ),                                                                                     serializer: Fields(                                                                                         GeneralFieldsSerializer {                                                                                             fields: {                                                                                                 "x": SerField {                                                                                                     key_py: Py(                                                                                                         0x00007fa14fa3e140,                                                                                                     ),                                                                                                     alias: None,                                                                                                     alias_py: None,                                                                                                     serializer: Some(                                                                                                         Float(                                                                                                             FloatSerializer {                                                                                                                 inf_nan_mode: Null,                                                                                                             },                                                                                                         ),                                                                                                     ),                                                                                                     required: true,                                                                                                 },                                                                                                 "y": SerField {                                                                                                     key_py: Py(                                                                                                         0x00007fa14fa3e170,                                                                                                     ),                                                                                                     alias: None,                                                                                                     alias_py: None,                                                                                                     serializer: Some(                                                                                                         Float(                                                                                                             FloatSerializer {                                                                                                                 inf_nan_mode: Null,                                                                                                             },                                                                                                         ),                                                                                                     ),                                                                                                     required: true,                                                                                                 },                                                                                             },                                                                                             computed_fields: Some(                                                                                                 ComputedFields(                                                                                                     [],                                                                                                 ),                                                                                             ),                                                                                             mode: SimpleDict,                                                                                             extra_serializer: None,                                                                                             filter: SchemaFilter {                                                                                                 include: None,                                                                                                 exclude: None,                                                                                             },                                                                                             required_fields: 2,                                                                                         },                                                                                     ),                                                                                     has_extra: false,                                                                                     root_model: false,                                                                                     name: "Point2d",                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "relative": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e010bf0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Bool(                                                                                 BoolSerializer,                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "end": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa38368,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14cf81350,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "arc",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['arc']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "radius": SerField {                                                                         key_py: Py(                                                                             0x00007fa14b020cf0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Float(                                                                                 FloatSerializer {                                                                                     inf_nan_mode: Null,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 6,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionArc",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb039a0640,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "control1": SerField {                                                                         key_py: Py(                                                                             0x00007fa14afff3f0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "end": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa38368,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "relative": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e010bf0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Bool(                                                                                 BoolSerializer,                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "control2": SerField {                                                                         key_py: Py(                                                                             0x00007fa14b01dff0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14d8e7330,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "bezier",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['bezier']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 5,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionBezier",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb039a5210,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "radius": SerField {                                                                         key_py: Py(                                                                             0x00007fa14b020cf0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Float(                                                                                 FloatSerializer {                                                                                     inf_nan_mode: Null,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14b01e230,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "tangential_arc",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['tangential_arc']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "offset": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3a7c0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 3,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionTangentialArc",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb039a8910,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "angle_snap_increment": SerField {                                                                         key_py: Py(                                                                             0x00007fa14b01e3f0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14f947100,                                                                                         ),                                                                                     ),                                                                                     serializer: Nullable(                                                                                         NullableSerializer {                                                                                             serializer: Recursive(                                                                                                 DefinitionRefSerializer {                                                                                                     definition: "...",                                                                                                     retry_with_lax_check: true,                                                                                                 },                                                                                             ),                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "to": SerField {                                                                         key_py: Py(                                                                             0x00007fa14eb8b120,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14ae2e6f0,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "tangential_arc_to",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['tangential_arc_to']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 3,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionTangentialArcTo",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb039ad790,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "interior": SerField {                                                                         key_py: Py(                                                                             0x00007fa14ae2e7b0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14afd1740,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "arc_to",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['arc_to']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "relative": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e010bf0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Bool(                                                                                 BoolSerializer,                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "end": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa38368,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 4,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionArcTo",                                                     },                                                 ),                                             ],                                             name: "TaggedUnion[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo]",                                         },                                     ),                                     has_extra: false,                                     root_model: true,                                     name: "RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionExtendPath",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55eb0330e750), serializer: Fields(GeneralFieldsSerializer { fields: {"x": SerField { key_py: Py(0x7fa14fa3e140), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7fa14fa3e170), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7fa14fa3e1a0), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" }), Enum(EnumSerializer { class: Py(0x55eb03355390), serializer: Some(Str(StrSerializer)) }), Model(ModelSerializer { class: Py(0x55eb035e4800), serializer: Fields(GeneralFieldsSerializer { fields: {"unit": SerField { key_py: Py(0x7fa14e161380), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: false })), required: true }, "value": SerField { key_py: Py(0x7fa14fa3c768), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "Angle" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExtendPath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "path",                         lookup_key: Simple {                             key: "path",                             py_key: Py(                                 0x00007fa14afd37b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "path",                                         Py(                                             0x00007fa14afd3e40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3ac30,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Str(                                     StrValidator {                                         strict: false,                                         coerce_numbers_to_str: false,                                     },                                 ),                                 func: Py(                                     0x000055eb039991a0,                                 ),                                 config: Py(                                     0x00007fa14ae41940,                                 ),                                 name: "function-after[ModelingCmdId(), str]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "segment",                         lookup_key: Simple {                             key: "segment",                             py_key: Py(                                 0x00007fa14afe41e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "segment",                                         Py(                                             0x00007fa14afe4360,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e9da1f0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: TaggedUnion(                                     TaggedUnionValidator {                                         discriminator: LookupKey(                                             Simple {                                                 key: "type",                                                 py_key: Py(                                                     0x00007fa14fa3c5a0,                                                 ),                                                 path: LookupPath(                                                     [                                                         S(                                                             "type",                                                             Py(                                                                 0x00007fa14fa3c5a0,                                                             ),                                                         ),                                                     ],                                                 ),                                             },                                         ),                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "line": 0,                                                     "arc_to": 5,                                                     "bezier": 2,                                                     "tangential_arc_to": 4,                                                     "tangential_arc": 3,                                                     "arc": 1,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "end",                                                                         lookup_key: Simple {                                                                             key: "end",                                                                             py_key: Py(                                                                                 0x00007fa14afd3720,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "end",                                                                                         Py(                                                                                             0x00007fa14afd2bb0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa38368,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "relative",                                                                         lookup_key: Simple {                                                                             key: "relative",                                                                             py_key: Py(                                                                                 0x00007fa14afd5bf0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "relative",                                                                                         Py(                                                                                             0x00007fa14afbfc70,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e010bf0,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14afd3690,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14afd3f00,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14fa39c38,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "line": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14fa39c38,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'line'",                                                                                         name: "literal['line']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['line']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionLine",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb039e4ec0,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionLine",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "center",                                                                         lookup_key: Simple {                                                                             key: "center",                                                                             py_key: Py(                                                                                 0x00007fa14afd36f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "center",                                                                                         Py(                                                                                             0x00007fa14afd3360,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14ef08150,                                                                         ),                                                                         validator: Model(                                                                             ModelValidator {                                                                                 revalidate: Never,                                                                                 validator: ModelFields(                                                                                     ModelFieldsValidator {                                                                                         fields: [                                                                                             Field {                                                                                                 name: "x",                                                                                                 lookup_key: Simple {                                                                                                     key: "x",                                                                                                     py_key: Py(                                                                                                         0x00007fa14fa3e140,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "x",                                                                                                                 Py(                                                                                                                     0x00007fa14fa3e140,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007fa14fa3e140,                                                                                                 ),                                                                                                 validator: FunctionAfter(                                                                                                     FunctionAfterValidator {                                                                                                         validator: Float(                                                                                                             FloatValidator {                                                                                                                 strict: false,                                                                                                                 allow_inf_nan: true,                                                                                                             },                                                                                                         ),                                                                                                         func: Py(                                                                                                             0x000055eb03768720,                                                                                                         ),                                                                                                         config: Py(                                                                                                             0x00007fa14ae434c0,                                                                                                         ),                                                                                                         name: "function-after[LengthUnit(), float]",                                                                                                         field_name: None,                                                                                                         info_arg: false,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                             Field {                                                                                                 name: "y",                                                                                                 lookup_key: Simple {                                                                                                     key: "y",                                                                                                     py_key: Py(                                                                                                         0x00007fa14fa3e170,                                                                                                     ),                                                                                                     path: LookupPath(                                                                                                         [                                                                                                             S(                                                                                                                 "y",                                                                                                                 Py(                                                                                                                     0x00007fa14fa3e170,                                                                                                                 ),                                                                                                             ),                                                                                                         ],                                                                                                     ),                                                                                                 },                                                                                                 name_py: Py(                                                                                                     0x00007fa14fa3e170,                                                                                                 ),                                                                                                 validator: FunctionAfter(                                                                                                     FunctionAfterValidator {                                                                                                         validator: Float(                                                                                                             FloatValidator {                                                                                                                 strict: false,                                                                                                                 allow_inf_nan: true,                                                                                                             },                                                                                                         ),                                                                                                         func: Py(                                                                                                             0x000055eb03768720,                                                                                                         ),                                                                                                         config: Py(                                                                                                             0x00007fa14ae434c0,                                                                                                         ),                                                                                                         name: "function-after[LengthUnit(), float]",                                                                                                         field_name: None,                                                                                                         info_arg: false,                                                                                                     },                                                                                                 ),                                                                                                 frozen: false,                                                                                             },                                                                                         ],                                                                                         model_name: "Point2d",                                                                                         extra_behavior: Ignore,                                                                                         extras_validator: None,                                                                                         strict: false,                                                                                         from_attributes: false,                                                                                         loc_by_alias: true,                                                                                     },                                                                                 ),                                                                                 class: Py(                                                                                     0x000055eb0399c230,                                                                                 ),                                                                                 post_init: None,                                                                                 frozen: false,                                                                                 custom_init: false,                                                                                 root_model: false,                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                                 name: "Point2d",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "end",                                                                         lookup_key: Simple {                                                                             key: "end",                                                                             py_key: Py(                                                                                 0x00007fa14afd3480,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "end",                                                                                         Py(                                                                                             0x00007fa14afd3060,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa38368,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "Angle",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "radius",                                                                         lookup_key: Simple {                                                                             key: "radius",                                                                             py_key: Py(                                                                                 0x00007fa14afd3660,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "radius",                                                                                         Py(                                                                                             0x00007fa14afd3570,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14b020cf0,                                                                         ),                                                                         validator: FunctionAfter(                                                                             FunctionAfterValidator {                                                                                 validator: Float(                                                                                     FloatValidator {                                                                                         strict: false,                                                                                         allow_inf_nan: true,                                                                                     },                                                                                 ),                                                                                 func: Py(                                                                                     0x000055eb03768720,                                                                                 ),                                                                                 config: Py(                                                                                     0x00007fa14ae42f80,                                                                                 ),                                                                                 name: "function-after[LengthUnit(), float]",                                                                                 field_name: None,                                                                                 info_arg: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "relative",                                                                         lookup_key: Simple {                                                                             key: "relative",                                                                             py_key: Py(                                                                                 0x00007fa14afbf9f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "relative",                                                                                         Py(                                                                                             0x00007fa14afbfbb0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e010bf0,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "start",                                                                         lookup_key: Simple {                                                                             key: "start",                                                                             py_key: Py(                                                                                 0x00007fa14afd0450,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "start",                                                                                         Py(                                                                                             0x00007fa14afd2c70,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3bce8,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "Angle",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14afe5650,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14afe5710,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14cf81350,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "arc": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14cf81350,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'arc'",                                                                                         name: "literal['arc']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['arc']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionArc",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb039e7e20,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionArc",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "control1",                                                                         lookup_key: Simple {                                                                             key: "control1",                                                                             py_key: Py(                                                                                 0x00007fa14afbfcf0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "control1",                                                                                         Py(                                                                                             0x00007fa14afbf670,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14afff3f0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "control2",                                                                         lookup_key: Simple {                                                                             key: "control2",                                                                             py_key: Py(                                                                                 0x00007fa14af91670,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "control2",                                                                                         Py(                                                                                             0x00007fa14af90130,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14b01dff0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "end",                                                                         lookup_key: Simple {                                                                             key: "end",                                                                             py_key: Py(                                                                                 0x00007fa14afe5530,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "end",                                                                                         Py(                                                                                             0x00007fa14afe5560,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa38368,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "relative",                                                                         lookup_key: Simple {                                                                             key: "relative",                                                                             py_key: Py(                                                                                 0x00007fa14af911f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "relative",                                                                                         Py(                                                                                             0x00007fa14af929f0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e010bf0,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14afe54a0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14afe5950,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14d8e7330,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "bezier": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14d8e7330,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'bezier'",                                                                                         name: "literal['bezier']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['bezier']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionBezier",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb039a0640,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionBezier",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "offset",                                                                         lookup_key: Simple {                                                                             key: "offset",                                                                             py_key: Py(                                                                                 0x00007fa14afe5380,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "offset",                                                                                         Py(                                                                                             0x00007fa14afe53e0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3a7c0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "Angle",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "radius",                                                                         lookup_key: Simple {                                                                             key: "radius",                                                                             py_key: Py(                                                                                 0x00007fa14afe53b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "radius",                                                                                         Py(                                                                                             0x00007fa14afe54d0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14b020cf0,                                                                         ),                                                                         validator: FunctionAfter(                                                                             FunctionAfterValidator {                                                                                 validator: Float(                                                                                     FloatValidator {                                                                                         strict: false,                                                                                         allow_inf_nan: true,                                                                                     },                                                                                 ),                                                                                 func: Py(                                                                                     0x000055eb03768720,                                                                                 ),                                                                                 config: Py(                                                                                     0x00007fa14ae42600,                                                                                 ),                                                                                 name: "function-after[LengthUnit(), float]",                                                                                 field_name: None,                                                                                 info_arg: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14afe5470,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14afe5410,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14b01e230,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "tangential_arc": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14b01e230,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'tangential_arc'",                                                                                         name: "literal['tangential_arc']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['tangential_arc']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionTangentialArc",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb039a5210,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionTangentialArc",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "angle_snap_increment",                                                                         lookup_key: Simple {                                                                             key: "angle_snap_increment",                                                                             py_key: Py(                                                                                 0x00007fa14af92ab0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "angle_snap_increment",                                                                                         Py(                                                                                             0x00007fa14ae70c70,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14b01e3f0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14f947100,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Nullable(                                                                                     NullableValidator {                                                                                         validator: DefinitionRef(                                                                                             DefinitionRefValidator {                                                                                                 definition: "Angle",                                                                                             },                                                                                         ),                                                                                         name: "nullable[Angle]",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[nullable[Angle]]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "to",                                                                         lookup_key: Simple {                                                                             key: "to",                                                                             py_key: Py(                                                                                 0x00007fa14afe5350,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "to",                                                                                         Py(                                                                                             0x00007fa14afe5440,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14eb8b120,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14afe5020,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14afe50b0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14ae2e6f0,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "tangential_arc_to": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14ae2e6f0,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'tangential_arc_to'",                                                                                         name: "literal['tangential_arc_to']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['tangential_arc_to']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionTangentialArcTo",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb039a8910,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionTangentialArcTo",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "end",                                                                         lookup_key: Simple {                                                                             key: "end",                                                                             py_key: Py(                                                                                 0x00007fa14afe4f00,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "end",                                                                                         Py(                                                                                             0x00007fa14afe4f30,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa38368,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "interior",                                                                         lookup_key: Simple {                                                                             key: "interior",                                                                             py_key: Py(                                                                                 0x00007fa14ae70a30,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "interior",                                                                                         Py(                                                                                             0x00007fa14ae70630,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14ae2e7b0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "relative",                                                                         lookup_key: Simple {                                                                             key: "relative",                                                                             py_key: Py(                                                                                 0x00007fa14ae701b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "relative",                                                                                         Py(                                                                                             0x00007fa14ae70270,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e010bf0,                                                                         ),                                                                         validator: Bool(                                                                             BoolValidator {                                                                                 strict: false,                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14afe4390,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14afe50e0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14afd1740,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "arc_to": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14afd1740,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'arc_to'",                                                                                         name: "literal['arc_to']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['arc_to']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionArcTo",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb039ad790,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionArcTo",                                                     },                                                 ),                                             ],                                         },                                         from_attributes: true,                                         strict: false,                                         custom_error: None,                                         tags_repr: "'line', 'arc', 'bezier', 'tangential_arc', 'tangential_arc_to', 'arc_to'",                                         discriminator_repr: "'type'",                                         name: "tagged-union[OptionLine,OptionArc,OptionBezier,OptionTangentialArc,OptionTangentialArcTo,OptionArcTo]",                                     },                                 ),                                 class: Py(                                     0x000055eb039b2310,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: true,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe4240,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe42a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bf7e630,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "extend_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bf7e630,                                                 ),                                             ],                                         },                                         expected_repr: "'extend_path'",                                         name: "literal['extend_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['extend_path']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExtendPath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb039f5970,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionExtendPath",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "unit", lookup_key: Simple { key: "unit", py_key: Py(0x7fa14afd3d80), path: LookupPath([S("unit", Py(0x7fa14afd3c30))]) }, name_py: Py(0x7fa14e161380), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }, Field { name: "value", lookup_key: Simple { key: "value", py_key: Py(0x7fa14afd38d0), path: LookupPath([S("value", Py(0x7fa14afd3f60))]) }, name_py: Py(0x7fa14fa3c768), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Angle", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb035e4800), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Angle" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fa14fa3e140), path: LookupPath([S("x", Py(0x7fa14fa3e140))]) }, name_py: Py(0x7fa14fa3e140), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fa14fa3e170), path: LookupPath([S("y", Py(0x7fa14fa3e170))]) }, name_py: Py(0x7fa14fa3e170), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fa14fa3e1a0), path: LookupPath([S("z", Py(0x7fa14fa3e1a0))]) }, name_py: Py(0x7fa14fa3e1a0), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb0330e750), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Point3d" }), StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb03355390), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"degrees": 0, "radians": 1}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b361850), Py(0x7fa14b3618b0)] }, missing: None, expected_repr: "'degrees' or 'radians'", strict: false, class_repr: "UnitAngle", name: "str-enum[UnitAngle]" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, path: kittycad.models.modeling_cmd_id.ModelingCmdId, segment: pydantic.root_model.RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], type: Literal['extend_path'] = 'extend_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'path': FieldInfo(annotation=ModelingCmdId, required=True), 'segment': FieldInfo(annotation=RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], required=True), 'type': FieldInfo(annotation=Literal['extend_path'], required=False, default='extend_path')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path: ModelingCmdId

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

segment: RootModel[Annotated[Union[OptionLine, OptionArc, OptionBezier, OptionTangentialArc, OptionTangentialArcTo, OptionArcTo], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]

type: Literal['extend_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionExtrude(**data)

Command for extruding a solid 2d.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'distance': <class 'kittycad.models.length_unit.LengthUnit'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'target': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'type': typing.Literal['extrude']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionExtrude'>, 'config': {'title': 'OptionExtrude'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionExtrude'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionExtrude'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionExtrude:94467866464800', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'distance': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'target': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'type': 'no-info'}, 'schema': {'type': 'str'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'extrude', 'schema': {'expected': ['extrude'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionExtrude', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb039f9220,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "target": SerField {                         key_py: Py(                             0x00007fa14fa3c088,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14c15c990,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "extrude",                                             },                                             expected_py: None,                                             name: "literal['extrude']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "distance": SerField {                         key_py: Py(                             0x00007fa14e8a9730,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionExtrude",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionExtrude", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "distance",                         lookup_key: Simple {                             key: "distance",                             py_key: Py(                                 0x00007fa14b123570,                             ),                             path: LookupPath(                                 [                                     S(                                         "distance",                                         Py(                                             0x00007fa14b099ff0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e8a9730,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14afd69c0,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "target",                         lookup_key: Simple {                             key: "target",                             py_key: Py(                                 0x00007fa14afe5b00,                             ),                             path: LookupPath(                                 [                                     S(                                         "target",                                         Py(                                             0x00007fa14afe5a10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c088,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Str(                                     StrValidator {                                         strict: false,                                         coerce_numbers_to_str: false,                                     },                                 ),                                 func: Py(                                     0x000055eb039991a0,                                 ),                                 config: Py(                                     0x00007fa14afd69c0,                                 ),                                 name: "function-after[ModelingCmdId(), str]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe5aa0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe59b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14c15c990,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "extrude": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14c15c990,                                                 ),                                             ],                                         },                                         expected_repr: "'extrude'",                                         name: "literal['extrude']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['extrude']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionExtrude",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb039f9220,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionExtrude",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, distance: kittycad.models.length_unit.LengthUnit, target: kittycad.models.modeling_cmd_id.ModelingCmdId, type: Literal['extrude'] = 'extrude') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

distance: LengthUnit

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'distance': FieldInfo(annotation=LengthUnit, required=True), 'target': FieldInfo(annotation=ModelingCmdId, required=True), 'type': FieldInfo(annotation=Literal['extrude'], required=False, default='extrude')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

target: ModelingCmdId

type: Literal['extrude']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionFaceGetCenter(**data)

Obtains the surface “center of mass”

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['face_get_center']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionFaceGetCenter'>, 'config': {'title': 'OptionFaceGetCenter'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionFaceGetCenter'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionFaceGetCenter'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionFaceGetCenter:94467867535552', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'face_get_center', 'schema': {'expected': ['face_get_center'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionFaceGetCenter', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03afe8c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4e7b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "face_get_center",                                             },                                             expected_py: None,                                             name: "literal['face_get_center']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionFaceGetCenter",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionFaceGetCenter", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ad3e1f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ad3e170,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae74390,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae743c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4e7b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "face_get_center": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4e7b0,                                                 ),                                             ],                                         },                                         expected_repr: "'face_get_center'",                                         name: "literal['face_get_center']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['face_get_center']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionFaceGetCenter",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03afe8c0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionFaceGetCenter",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, object_id: str, type: Literal['face_get_center'] = 'face_get_center') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['face_get_center'], required=False, default='face_get_center')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['face_get_center']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionFaceGetGradient(**data)

Determines the gradient (dFdu, dFdv) + normal vector on a brep face evaluated by parameters u,v

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['face_get_gradient'], 'uv': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionFaceGetGradient'>, 'config': {'title': 'OptionFaceGetGradient'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionFaceGetGradient'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionFaceGetGradient'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionFaceGetGradient:94467867550000', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'face_get_gradient', 'schema': {'expected': ['face_get_gradient'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'uv': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionFaceGetGradient', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b02130,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4e870,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "face_get_gradient",                                             },                                             expected_py: None,                                             name: "literal['face_get_gradient']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "uv": SerField {                         key_py: Py(                             0x00007fa14b021140,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionFaceGetGradient",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionFaceGetGradient", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ad3fdb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ad3fd70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae76d60,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae76d90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4e870,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "face_get_gradient": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4e870,                                                 ),                                             ],                                         },                                         expected_repr: "'face_get_gradient'",                                         name: "literal['face_get_gradient']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['face_get_gradient']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "uv",                         lookup_key: Simple {                             key: "uv",                             py_key: Py(                                 0x00007fa14ae76dc0,                             ),                             path: LookupPath(                                 [                                     S(                                         "uv",                                         Py(                                             0x00007fa14ae76df0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b021140,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad3fc40,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad3fc40,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionFaceGetGradient",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b02130,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionFaceGetGradient",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, object_id: str, type: Literal['face_get_gradient'] = 'face_get_gradient', uv: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['face_get_gradient'], required=False, default='face_get_gradient'), 'uv': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['face_get_gradient']

classmethod update_forward_refs(**localns)

Return type:

None

uv: Point2d

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionFaceGetPosition(**data)

Determines a position on a brep face evaluated by parameters u,v

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['face_get_position'], 'uv': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionFaceGetPosition'>, 'config': {'title': 'OptionFaceGetPosition'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionFaceGetPosition'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionFaceGetPosition'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionFaceGetPosition:94467867526848', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'face_get_position', 'schema': {'expected': ['face_get_position'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'uv': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionFaceGetPosition', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03afc6c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "uv": SerField {                         key_py: Py(                             0x00007fa14b021140,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4e930,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "face_get_position",                                             },                                             expected_py: None,                                             name: "literal['face_get_position']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionFaceGetPosition",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionFaceGetPosition", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ad3d3f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ad3d3b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae76760,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae76940,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4e930,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "face_get_position": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4e930,                                                 ),                                             ],                                         },                                         expected_repr: "'face_get_position'",                                         name: "literal['face_get_position']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['face_get_position']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "uv",                         lookup_key: Simple {                             key: "uv",                             py_key: Py(                                 0x00007fa14ae769a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "uv",                                         Py(                                             0x00007fa14ae76730,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b021140,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad3d280,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad3d280,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionFaceGetPosition",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03afc6c0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionFaceGetPosition",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, object_id: str, type: Literal['face_get_position'] = 'face_get_position', uv: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['face_get_position'], required=False, default='face_get_position'), 'uv': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['face_get_position']

classmethod update_forward_refs(**localns)

Return type:

None

uv: Point2d

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionFaceIsPlanar(**data)

Determines whether a brep face is planar and returns its surface-local planar axes if so

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['face_is_planar']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionFaceIsPlanar'>, 'config': {'title': 'OptionFaceIsPlanar'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionFaceIsPlanar'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionFaceIsPlanar'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionFaceIsPlanar:94467867492016', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'face_is_planar', 'schema': {'expected': ['face_is_planar'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionFaceIsPlanar', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03af3eb0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4e9b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "face_is_planar",                                             },                                             expected_py: None,                                             name: "literal['face_is_planar']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionFaceIsPlanar",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionFaceIsPlanar", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ad2ff30,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ad2feb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae751d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae75200,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4e9b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "face_is_planar": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4e9b0,                                                 ),                                             ],                                         },                                         expected_repr: "'face_is_planar'",                                         name: "literal['face_is_planar']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['face_is_planar']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionFaceIsPlanar",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03af3eb0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionFaceIsPlanar",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, object_id: str, type: Literal['face_is_planar'] = 'face_is_planar') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['face_is_planar'], required=False, default='face_is_planar')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['face_is_planar']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionGetEntityType(**data)

What type of entity is this?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['get_entity_type']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionGetEntityType'>, 'config': {'title': 'OptionGetEntityType'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionGetEntityType'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionGetEntityType'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionGetEntityType:94467867382160', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'get_entity_type', 'schema': {'expected': ['get_entity_type'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionGetEntityType', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ad9190,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_id": SerField {                         key_py: Py(                             0x00007fa14b0459f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4f870,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "get_entity_type",                                             },                                             expected_py: None,                                             name: "literal['get_entity_type']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionGetEntityType",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionGetEntityType", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_id",                         lookup_key: Simple {                             key: "entity_id",                             py_key: Py(                                 0x00007fa14af103b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_id",                                         Py(                                             0x00007fa14af10370,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0459f0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b027750,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b027780,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4f870,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "get_entity_type": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4f870,                                                 ),                                             ],                                         },                                         expected_repr: "'get_entity_type'",                                         name: "literal['get_entity_type']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['get_entity_type']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionGetEntityType",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ad9190,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionGetEntityType",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_id: str, type: Literal['get_entity_type'] = 'get_entity_type') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['get_entity_type'], required=False, default='get_entity_type')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['get_entity_type']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionGetNumObjects(**data)

Get the number of objects in the scene

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['get_num_objects']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionGetNumObjects'>, 'config': {'title': 'OptionGetNumObjects'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionGetNumObjects'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionGetNumObjects'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionGetNumObjects:94467868279568', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'get_num_objects', 'schema': {'expected': ['get_num_objects'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionGetNumObjects', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03bb4310,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4f8f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "get_num_objects",                                             },                                             expected_py: None,                                             name: "literal['get_num_objects']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionGetNumObjects",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionGetNumObjects", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae022e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae02310,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4f8f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "get_num_objects": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4f8f0,                                                 ),                                             ],                                         },                                         expected_repr: "'get_num_objects'",                                         name: "literal['get_num_objects']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['get_num_objects']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionGetNumObjects",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03bb4310,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionGetNumObjects",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['get_num_objects'] = 'get_num_objects') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['get_num_objects'], required=False, default='get_num_objects')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['get_num_objects']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionGetSketchModePlane(**data)

Get the plane for sketch mode.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['get_sketch_mode_plane']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionGetSketchModePlane'>, 'config': {'title': 'OptionGetSketchModePlane'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionGetSketchModePlane'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionGetSketchModePlane'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionGetSketchModePlane:94467867681216', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'get_sketch_mode_plane', 'schema': {'expected': ['get_sketch_mode_plane'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionGetSketchModePlane', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b221c0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4f9b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "get_sketch_mode_plane",                                             },                                             expected_py: None,                                             name: "literal['get_sketch_mode_plane']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionGetSketchModePlane",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionGetSketchModePlane", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad54cf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad54d20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4f9b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "get_sketch_mode_plane": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4f9b0,                                                 ),                                             ],                                         },                                         expected_repr: "'get_sketch_mode_plane'",                                         name: "literal['get_sketch_mode_plane']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['get_sketch_mode_plane']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionGetSketchModePlane",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b221c0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionGetSketchModePlane",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['get_sketch_mode_plane'] = 'get_sketch_mode_plane') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['get_sketch_mode_plane'], required=False, default='get_sketch_mode_plane')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['get_sketch_mode_plane']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionHandleMouseDragEnd(**data)

Stop dragging the mouse.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['handle_mouse_drag_end'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionHandleMouseDragEnd'>, 'config': {'title': 'OptionHandleMouseDragEnd'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionHandleMouseDragEnd'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionHandleMouseDragEnd'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionHandleMouseDragEnd:94467867884448', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'handle_mouse_drag_end', 'schema': {'expected': ['handle_mouse_drag_end'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionHandleMouseDragEnd', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b53ba0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4ff70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "handle_mouse_drag_end",                                             },                                             expected_py: None,                                             name: "literal['handle_mouse_drag_end']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionHandleMouseDragEnd",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHandleMouseDragEnd", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad56b80,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad56bb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4ff70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "handle_mouse_drag_end": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4ff70,                                                 ),                                             ],                                         },                                         expected_repr: "'handle_mouse_drag_end'",                                         name: "literal['handle_mouse_drag_end']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['handle_mouse_drag_end']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14ad564f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14ad571b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad9e340,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad9e340,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHandleMouseDragEnd",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b53ba0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionHandleMouseDragEnd",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['handle_mouse_drag_end'] = 'handle_mouse_drag_end', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['handle_mouse_drag_end'], required=False, default='handle_mouse_drag_end'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['handle_mouse_drag_end']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionHandleMouseDragMove(**data)

Continue dragging the mouse.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'sequence': typing.Optional[int], 'type': typing.Literal['handle_mouse_drag_move'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionHandleMouseDragMove'>, 'config': {'title': 'OptionHandleMouseDragMove'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionHandleMouseDragMove'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionHandleMouseDragMove'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionHandleMouseDragMove:94467867870672', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'sequence': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'handle_mouse_drag_move', 'schema': {'expected': ['handle_mouse_drag_move'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionHandleMouseDragMove', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b505d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "sequence": SerField {                         key_py: Py(                             0x00007fa14fa3b790,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Int(                                                 IntSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4fe30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "handle_mouse_drag_move",                                             },                                             expected_py: None,                                             name: "literal['handle_mouse_drag_move']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionHandleMouseDragMove",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHandleMouseDragMove", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "sequence",                         lookup_key: Simple {                             key: "sequence",                             py_key: Py(                                 0x00007fa14ad646f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "sequence",                                         Py(                                             0x00007fa14ad9dd30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3b790,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Int(                                             IntValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[int]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[int]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad57f90,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad57f60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4fe30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "handle_mouse_drag_move": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4fe30,                                                 ),                                             ],                                         },                                         expected_repr: "'handle_mouse_drag_move'",                                         name: "literal['handle_mouse_drag_move']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['handle_mouse_drag_move']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14ad57f30,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14ad57c90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14adca600,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14adca600,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHandleMouseDragMove",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b505d0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionHandleMouseDragMove",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, sequence: Optional[int] = None, type: Literal['handle_mouse_drag_move'] = 'handle_mouse_drag_move', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'sequence': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['handle_mouse_drag_move'], required=False, default='handle_mouse_drag_move'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

sequence: Optional[int]

type: Literal['handle_mouse_drag_move']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionHandleMouseDragStart(**data)

Start dragging the mouse.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['handle_mouse_drag_start'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionHandleMouseDragStart'>, 'config': {'title': 'OptionHandleMouseDragStart'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionHandleMouseDragStart'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionHandleMouseDragStart'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionHandleMouseDragStart:94467867862048', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'handle_mouse_drag_start', 'schema': {'expected': ['handle_mouse_drag_start'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionHandleMouseDragStart', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b4e420,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be4fc70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "handle_mouse_drag_start",                                             },                                             expected_py: None,                                             name: "literal['handle_mouse_drag_start']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionHandleMouseDragStart",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHandleMouseDragStart", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc4360,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc4390,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be4fc70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "handle_mouse_drag_start": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be4fc70,                                                 ),                                             ],                                         },                                         expected_repr: "'handle_mouse_drag_start'",                                         name: "literal['handle_mouse_drag_start']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['handle_mouse_drag_start']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14adc43c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14adc43f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14adc8940,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14adc8940,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHandleMouseDragStart",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b4e420,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionHandleMouseDragStart",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['handle_mouse_drag_start'] = 'handle_mouse_drag_start', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['handle_mouse_drag_start'], required=False, default='handle_mouse_drag_start'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['handle_mouse_drag_start']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionHighlightSetEntities(**data)

Changes the current highlighted entity to these entities.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entities': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['highlight_set_entities']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionHighlightSetEntities'>, 'config': {'title': 'OptionHighlightSetEntities'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionHighlightSetEntities'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionHighlightSetEntities'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionHighlightSetEntities:94467867216432', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entities': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'highlight_set_entities', 'schema': {'expected': ['highlight_set_entities'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionHighlightSetEntities', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ab0a30,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be3a9b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "highlight_set_entities",                                             },                                             expected_py: None,                                             name: "literal['highlight_set_entities']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entities": SerField {                         key_py: Py(                             0x00007fa14d502070,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionHighlightSetEntities",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHighlightSetEntities", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entities",                         lookup_key: Simple {                             key: "entities",                             py_key: Py(                                 0x00007fa14aee72f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entities",                                         Py(                                             0x00007fa14aee7770,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d502070,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b0256e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b0256b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be3a9b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "highlight_set_entities": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be3a9b0,                                                 ),                                             ],                                         },                                         expected_repr: "'highlight_set_entities'",                                         name: "literal['highlight_set_entities']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['highlight_set_entities']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHighlightSetEntities",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ab0a30,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionHighlightSetEntities",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entities: List[str], type: Literal['highlight_set_entities'] = 'highlight_set_entities') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entities: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entities': FieldInfo(annotation=List[str], required=True), 'type': FieldInfo(annotation=Literal['highlight_set_entities'], required=False, default='highlight_set_entities')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['highlight_set_entities']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionHighlightSetEntity(**data)

Changes the current highlighted entity to whichever one is at the given window coordinate. If there’s no entity at this location, clears the highlight.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'selected_at_window': <class 'kittycad.models.point2d.Point2d'>, 'sequence': typing.Optional[int], 'type': typing.Literal['highlight_set_entity']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionHighlightSetEntity'>, 'config': {'title': 'OptionHighlightSetEntity'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionHighlightSetEntity'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionHighlightSetEntity'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionHighlightSetEntity:94467867207200', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'selected_at_window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'sequence': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'highlight_set_entity', 'schema': {'expected': ['highlight_set_entity'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionHighlightSetEntity', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03aae620,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14be3a3b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "highlight_set_entity",                                             },                                             expected_py: None,                                             name: "literal['highlight_set_entity']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "selected_at_window": SerField {                         key_py: Py(                             0x00007fa14aff6df0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                     "sequence": SerField {                         key_py: Py(                             0x00007fa14fa3b790,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Int(                                                 IntSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionHighlightSetEntity",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionHighlightSetEntity", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "selected_at_window",                         lookup_key: Simple {                             key: "selected_at_window",                             py_key: Py(                                 0x00007fa14aef02b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "selected_at_window",                                         Py(                                             0x00007fa14aef0270,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6df0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14aee7ec0,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14aee7ec0,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "sequence",                         lookup_key: Simple {                             key: "sequence",                             py_key: Py(                                 0x00007fa14aef0330,                             ),                             path: LookupPath(                                 [                                     S(                                         "sequence",                                         Py(                                             0x00007fa14aef02f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3b790,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Int(                                             IntValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[int]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[int]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b025ec0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b025ef0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14be3a3b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "highlight_set_entity": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14be3a3b0,                                                 ),                                             ],                                         },                                         expected_repr: "'highlight_set_entity'",                                         name: "literal['highlight_set_entity']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['highlight_set_entity']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionHighlightSetEntity",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03aae620,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionHighlightSetEntity",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, selected_at_window: kittycad.models.point2d.Point2d, sequence: Optional[int] = None, type: Literal['highlight_set_entity'] = 'highlight_set_entity') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'selected_at_window': FieldInfo(annotation=Point2d, required=True), 'sequence': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['highlight_set_entity'], required=False, default='highlight_set_entity')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

selected_at_window: Point2d

sequence: Optional[int]

type: Literal['highlight_set_entity']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionImportFiles(**data)

Import files to the current model.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'files': typing.List[kittycad.models.import_file.ImportFile], 'format': <class 'pydantic.root_model.RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['import_files']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.axis_direction_pair.AxisDirectionPair'>, 'config': {'title': 'AxisDirectionPair'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.axis_direction_pair.AxisDirectionPair'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.axis_direction_pair.AxisDirectionPair'>>]}, 'ref': 'kittycad.models.axis_direction_pair.AxisDirectionPair:94467855533120', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.axis.Axis:94467855528000', 'type': 'definition-ref'}, 'type': 'model-field'}, 'direction': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.direction.Direction:94467855530560', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'AxisDirectionPair', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <enum 'Axis'>, 'members': [Axis.Y, Axis.Z], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.axis.Axis:94467855528000', 'sub_type': 'str', 'type': 'enum'}, {'cls': <enum 'Direction'>, 'members': [Direction.POSITIVE, Direction.NEGATIVE], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.direction.Direction:94467855530560', 'sub_type': 'str', 'type': 'enum'}, {'cls': <class 'kittycad.models.system.System'>, 'config': {'title': 'System'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.system.System'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.system.System'>>]}, 'ref': 'kittycad.models.system.System:94467861035232', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'forward': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.axis_direction_pair.AxisDirectionPair:94467855533120', 'type': 'definition-ref'}, 'type': 'model-field'}, 'up': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.axis_direction_pair.AxisDirectionPair:94467855533120', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'System', 'type': 'model-fields'}, 'type': 'model'}, {'cls': <enum 'UnitLength'>, 'members': [UnitLength.CM, UnitLength.FT, UnitLength.IN, UnitLength.M, UnitLength.MM, UnitLength.YD], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_length.UnitLength:94467861018320', 'sub_type': 'str', 'type': 'enum'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionImportFiles'>, 'config': {'title': 'OptionImportFiles'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionImportFiles'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionImportFiles'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionImportFiles:94467867946048', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'files': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'cls': <class 'kittycad.models.import_file.ImportFile'>, 'config': {'title': 'ImportFile'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.import_file.ImportFile'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.import_file.ImportFile'>>]}, 'ref': 'kittycad.models.import_file.ImportFile:94467850099936', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'data': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bytes'}, 'type': 'model-field'}, 'path': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}}, 'model_name': 'ImportFile', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'list'}, 'type': 'model-field'}, 'format': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'pydantic.root_model.RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, 'config': {'title': "RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]"}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'pydantic.root_model.RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'pydantic.root_model.RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]'>>]}, 'ref': "pydantic.root_model.RootModel:94467864067568[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]:140330738859808]", 'root_model': True, 'schema': {'choices': {'fbx': {'cls': <class 'kittycad.models.input_format.OptionFbx'>, 'config': {'title': 'OptionFbx'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.input_format.OptionFbx'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.input_format.OptionFbx'>>]}, 'ref': 'kittycad.models.input_format.OptionFbx:94467861021664', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'fbx', 'schema': {'expected': ['fbx'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionFbx', 'type': 'model-fields'}, 'type': 'model'}, 'gltf': {'cls': <class 'kittycad.models.input_format.OptionGltf'>, 'config': {'title': 'OptionGltf'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.input_format.OptionGltf'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.input_format.OptionGltf'>>]}, 'ref': 'kittycad.models.input_format.OptionGltf:94467862042928', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'gltf', 'schema': {'expected': ['gltf'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionGltf', 'type': 'model-fields'}, 'type': 'model'}, 'obj': {'cls': <class 'kittycad.models.input_format.OptionObj'>, 'config': {'title': 'OptionObj'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.input_format.OptionObj'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.input_format.OptionObj'>>]}, 'ref': 'kittycad.models.input_format.OptionObj:94467862048624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'coords': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.system.System:94467861035232', 'type': 'definition-ref'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'obj', 'schema': {'expected': ['obj'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'units': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.unit_length.UnitLength:94467861018320', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'OptionObj', 'type': 'model-fields'}, 'type': 'model'}, 'ply': {'cls': <class 'kittycad.models.input_format.OptionPly'>, 'config': {'title': 'OptionPly'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.input_format.OptionPly'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.input_format.OptionPly'>>]}, 'ref': 'kittycad.models.input_format.OptionPly:94467855604016', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'coords': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.system.System:94467861035232', 'type': 'definition-ref'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'ply', 'schema': {'expected': ['ply'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'units': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.unit_length.UnitLength:94467861018320', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'OptionPly', 'type': 'model-fields'}, 'type': 'model'}, 'sldprt': {'cls': <class 'kittycad.models.input_format.OptionSldprt'>, 'config': {'title': 'OptionSldprt'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.input_format.OptionSldprt'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.input_format.OptionSldprt'>>]}, 'ref': 'kittycad.models.input_format.OptionSldprt:94467860978304', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'split_closed_faces': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': False, 'schema': {'type': 'bool'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'sldprt', 'schema': {'expected': ['sldprt'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSldprt', 'type': 'model-fields'}, 'type': 'model'}, 'step': {'cls': <class 'kittycad.models.input_format.OptionStep'>, 'config': {'title': 'OptionStep'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.input_format.OptionStep'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.input_format.OptionStep'>>]}, 'ref': 'kittycad.models.input_format.OptionStep:94467860988128', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'split_closed_faces': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': False, 'schema': {'type': 'bool'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'step', 'schema': {'expected': ['step'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionStep', 'type': 'model-fields'}, 'type': 'model'}, 'stl': {'cls': <class 'kittycad.models.input_format.OptionStl'>, 'config': {'title': 'OptionStl'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.input_format.OptionStl'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.input_format.OptionStl'>>]}, 'ref': 'kittycad.models.input_format.OptionStl:94467860998144', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'coords': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.system.System:94467861035232', 'type': 'definition-ref'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'stl', 'schema': {'expected': ['stl'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'units': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.unit_length.UnitLength:94467861018320', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'OptionStl', 'type': 'model-fields'}, 'type': 'model'}}, 'discriminator': 'type', 'from_attributes': True, 'metadata': {}, 'strict': False, 'type': 'tagged-union'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'import_files', 'schema': {'expected': ['import_files'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionImportFiles', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b62c40,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "format": SerField {                         key_py: Py(                             0x00007fa14fa38b50,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb02f8f8e0,                                     ),                                     serializer: TaggedUnion(                                         TaggedUnionSerializer {                                             discriminator: LookupKey(                                                 Simple {                                                     key: "type",                                                     py_key: Py(                                                         0x00007fa14fa3c5a0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "type",                                                                 Py(                                                                     0x00007fa14fa3c5a0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                             ),                                             lookup: {                                                 "stl": 6,                                                 "sldprt": 4,                                                 "fbx": 0,                                                 "gltf": 1,                                                 "obj": 2,                                                 "ply": 3,                                                 "step": 5,                                             },                                             choices: [                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb034c83e0,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd71170,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "fbx",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['fbx']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 1,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionFbx",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb035c1930,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd710e0,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "gltf",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['gltf']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 1,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionGltf",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb035c2f70,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14fa3a760,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "obj",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['obj']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "units": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: false,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "coords": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 3,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionObj",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb02f9d930,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd71b00,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "ply",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['ply']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "coords": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "units": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: false,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 3,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionPly",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb034bda80,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd71da0,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "sldprt",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['sldprt']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "split_closed_faces": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bb052b0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14f930d20,                                                                                         ),                                                                                     ),                                                                                     serializer: Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 2,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionSldprt",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb034c00e0,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "split_closed_faces": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bb052b0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14f930d20,                                                                                         ),                                                                                     ),                                                                                     serializer: Bool(                                                                                         BoolSerializer,                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14fa3be10,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "step",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['step']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 2,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionStep",                                                     },                                                 ),                                                 Model(                                                     ModelSerializer {                                                         class: Py(                                                             0x000055eb034c2800,                                                         ),                                                         serializer: Fields(                                                             GeneralFieldsSerializer {                                                                 fields: {                                                                     "coords": SerField {                                                                         key_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: true,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "type": SerField {                                                                         key_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             WithDefault(                                                                                 WithDefaultSerializer {                                                                                     default: Default(                                                                                         Py(                                                                                             0x00007fa14bd71ce0,                                                                                         ),                                                                                     ),                                                                                     serializer: Literal(                                                                                         LiteralSerializer {                                                                                             expected_int: {},                                                                                             expected_str: {                                                                                                 "stl",                                                                                             },                                                                                             expected_py: None,                                                                                             name: "literal['stl']",                                                                                         },                                                                                     ),                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                     "units": SerField {                                                                         key_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         alias: None,                                                                         alias_py: None,                                                                         serializer: Some(                                                                             Recursive(                                                                                 DefinitionRefSerializer {                                                                                     definition: "...",                                                                                     retry_with_lax_check: false,                                                                                 },                                                                             ),                                                                         ),                                                                         required: true,                                                                     },                                                                 },                                                                 computed_fields: Some(                                                                     ComputedFields(                                                                         [],                                                                     ),                                                                 ),                                                                 mode: SimpleDict,                                                                 extra_serializer: None,                                                                 filter: SchemaFilter {                                                                     include: None,                                                                     exclude: None,                                                                 },                                                                 required_fields: 3,                                                             },                                                         ),                                                         has_extra: false,                                                         root_model: false,                                                         name: "OptionStl",                                                     },                                                 ),                                             ],                                             name: "TaggedUnion[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl]",                                         },                                     ),                                     has_extra: false,                                     root_model: true,                                     name: "RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc6b870,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "import_files",                                             },                                             expected_py: None,                                             name: "literal['import_files']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "files": SerField {                         key_py: Py(                             0x00007fa14f9f0980,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Model(                                         ModelSerializer {                                             class: Py(                                                 0x000055eb02a5dce0,                                             ),                                             serializer: Fields(                                                 GeneralFieldsSerializer {                                                     fields: {                                                         "data": SerField {                                                             key_py: Py(                                                                 0x00007fa14fa37cd8,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 Bytes(                                                                     BytesSerializer {                                                                         bytes_mode: Utf8,                                                                     },                                                                 ),                                                             ),                                                             required: true,                                                         },                                                         "path": SerField {                                                             key_py: Py(                                                                 0x00007fa14fa3ac30,                                                             ),                                                             alias: None,                                                             alias_py: None,                                                             serializer: Some(                                                                 Str(                                                                     StrSerializer,                                                                 ),                                                             ),                                                             required: true,                                                         },                                                     },                                                     computed_fields: Some(                                                         ComputedFields(                                                             [],                                                         ),                                                     ),                                                     mode: SimpleDict,                                                     extra_serializer: None,                                                     filter: SchemaFilter {                                                         include: None,                                                         exclude: None,                                                     },                                                     required_fields: 2,                                                 },                                             ),                                             has_extra: false,                                             root_model: false,                                             name: "ImportFile",                                         },                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[ImportFile]",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionImportFiles",     }, ), definitions=[Enum(EnumSerializer { class: Py(0x55eb02f8b040), serializer: Some(Str(StrSerializer)) }), Model(ModelSerializer { class: Py(0x55eb034cb8e0), serializer: Fields(GeneralFieldsSerializer { fields: {"forward": SerField { key_py: Py(0x7fa14bd71cb0), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true })), required: true }, "up": SerField { key_py: Py(0x7fa14d9ed0b0), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: true })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "System" }), Enum(EnumSerializer { class: Py(0x55eb034c76d0), serializer: Some(Str(StrSerializer)) }), Enum(EnumSerializer { class: Py(0x55eb02f8ba40), serializer: Some(Str(StrSerializer)) }), Model(ModelSerializer { class: Py(0x55eb02f8c440), serializer: Fields(GeneralFieldsSerializer { fields: {"axis": SerField { key_py: Py(0x7fa14c13dce0), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: false })), required: true }, "direction": SerField { key_py: Py(0x7fa14e41ef30), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: false })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 2 }), has_extra: false, root_model: false, name: "AxisDirectionPair" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionImportFiles", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "files",                         lookup_key: Simple {                             key: "files",                             py_key: Py(                                 0x00007fa14adc4930,                             ),                             path: LookupPath(                                 [                                     S(                                         "files",                                         Py(                                             0x00007fa14adc4a50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14f9f0980,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Model(                                         ModelValidator {                                             revalidate: Never,                                             validator: ModelFields(                                                 ModelFieldsValidator {                                                     fields: [                                                         Field {                                                             name: "data",                                                             lookup_key: Simple {                                                                 key: "data",                                                                 py_key: Py(                                                                     0x00007fa14adc4ea0,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "data",                                                                             Py(                                                                                 0x00007fa14adc5290,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fa14fa37cd8,                                                             ),                                                             validator: Bytes(                                                                 BytesValidator {                                                                     strict: false,                                                                     bytes_mode: ValBytesMode {                                                                         ser: Utf8,                                                                     },                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                         Field {                                                             name: "path",                                                             lookup_key: Simple {                                                                 key: "path",                                                                 py_key: Py(                                                                     0x00007fa14adc52f0,                                                                 ),                                                                 path: LookupPath(                                                                     [                                                                         S(                                                                             "path",                                                                             Py(                                                                                 0x00007fa14adc4f60,                                                                             ),                                                                         ),                                                                     ],                                                                 ),                                                             },                                                             name_py: Py(                                                                 0x00007fa14fa3ac30,                                                             ),                                                             validator: Str(                                                                 StrValidator {                                                                     strict: false,                                                                     coerce_numbers_to_str: false,                                                                 },                                                             ),                                                             frozen: false,                                                         },                                                     ],                                                     model_name: "ImportFile",                                                     extra_behavior: Ignore,                                                     extras_validator: None,                                                     strict: false,                                                     from_attributes: false,                                                     loc_by_alias: true,                                                 },                                             ),                                             class: Py(                                                 0x000055eb02a5dce0,                                             ),                                             post_init: None,                                             frozen: false,                                             custom_init: false,                                             root_model: false,                                             undefined: Py(                                                 0x00007fa14d802350,                                             ),                                             name: "ImportFile",                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "format",                         lookup_key: Simple {                             key: "format",                             py_key: Py(                                 0x00007fa14adc4720,                             ),                             path: LookupPath(                                 [                                     S(                                         "format",                                         Py(                                             0x00007fa14adc5950,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa38b50,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: TaggedUnion(                                     TaggedUnionValidator {                                         discriminator: LookupKey(                                             Simple {                                                 key: "type",                                                 py_key: Py(                                                     0x00007fa14fa3c5a0,                                                 ),                                                 path: LookupPath(                                                     [                                                         S(                                                             "type",                                                             Py(                                                                 0x00007fa14fa3c5a0,                                                             ),                                                         ),                                                     ],                                                 ),                                             },                                         ),                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "step": 5,                                                     "obj": 2,                                                     "gltf": 1,                                                     "fbx": 0,                                                     "stl": 6,                                                     "ply": 3,                                                     "sldprt": 4,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14adc4d80,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14adc4de0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd71170,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "fbx": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd71170,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'fbx'",                                                                                         name: "literal['fbx']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['fbx']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionFbx",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb034c83e0,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionFbx",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14adc5020,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14adc4cc0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd710e0,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "gltf": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd710e0,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'gltf'",                                                                                         name: "literal['gltf']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['gltf']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionGltf",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb035c1930,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionGltf",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "coords",                                                                         lookup_key: Simple {                                                                             key: "coords",                                                                             py_key: Py(                                                                                 0x00007fa14adc4ed0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "coords",                                                                                         Py(                                                                                             0x00007fa14adc4e40,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14adc4c90,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14adc4db0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14fa3a760,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "obj": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14fa3a760,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'obj'",                                                                                         name: "literal['obj']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['obj']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "units",                                                                         lookup_key: Simple {                                                                             key: "units",                                                                             py_key: Py(                                                                                 0x00007fa14adc4d50,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "units",                                                                                         Py(                                                                                             0x00007fa14adc4e10,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionObj",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb035c2f70,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionObj",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "coords",                                                                         lookup_key: Simple {                                                                             key: "coords",                                                                             py_key: Py(                                                                                 0x00007fa14adc4cf0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "coords",                                                                                         Py(                                                                                             0x00007fa14adc4060,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14adc40f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14adc4120,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd71b00,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "ply": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd71b00,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'ply'",                                                                                         name: "literal['ply']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['ply']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "units",                                                                         lookup_key: Simple {                                                                             key: "units",                                                                             py_key: Py(                                                                                 0x00007fa14adc4990,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "units",                                                                                         Py(                                                                                             0x00007fa14adc4660,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionPly",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb02f9d930,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionPly",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "split_closed_faces",                                                                         lookup_key: Simple {                                                                             key: "split_closed_faces",                                                                             py_key: Py(                                                                                 0x00007fa14af843b0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "split_closed_faces",                                                                                         Py(                                                                                             0x00007fa14ad2e970,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bb052b0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14f930d20,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Bool(                                                                                     BoolValidator {                                                                                         strict: false,                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[bool]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14adc45d0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14adc4600,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd71da0,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "sldprt": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd71da0,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'sldprt'",                                                                                         name: "literal['sldprt']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['sldprt']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionSldprt",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb034bda80,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionSldprt",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "split_closed_faces",                                                                         lookup_key: Simple {                                                                             key: "split_closed_faces",                                                                             py_key: Py(                                                                                 0x00007fa14ad6e4f0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "split_closed_faces",                                                                                         Py(                                                                                             0x00007fa14add0a30,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bb052b0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14f930d20,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Bool(                                                                                     BoolValidator {                                                                                         strict: false,                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[bool]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14adc4240,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14adc41b0,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14fa3be10,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "step": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14fa3be10,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'step'",                                                                                         name: "literal['step']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['step']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionStep",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb034c00e0,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionStep",                                                     },                                                 ),                                                 Model(                                                     ModelValidator {                                                         revalidate: Never,                                                         validator: ModelFields(                                                             ModelFieldsValidator {                                                                 fields: [                                                                     Field {                                                                         name: "coords",                                                                         lookup_key: Simple {                                                                             key: "coords",                                                                             py_key: Py(                                                                                 0x00007fa14adc4300,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "coords",                                                                                         Py(                                                                                             0x00007fa14adc4150,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14bd723a0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "type",                                                                         lookup_key: Simple {                                                                             key: "type",                                                                             py_key: Py(                                                                                 0x00007fa14adc4180,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "type",                                                                                         Py(                                                                                             0x00007fa14adc4480,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14fa3c5a0,                                                                         ),                                                                         validator: WithDefault(                                                                             WithDefaultValidator {                                                                                 default: Default(                                                                                     Py(                                                                                         0x00007fa14bd71ce0,                                                                                     ),                                                                                 ),                                                                                 on_error: Raise,                                                                                 validator: Literal(                                                                                     LiteralValidator {                                                                                         lookup: LiteralLookup {                                                                                             expected_bool: None,                                                                                             expected_int: None,                                                                                             expected_str: Some(                                                                                                 {                                                                                                     "stl": 0,                                                                                                 },                                                                                             ),                                                                                             expected_py_dict: None,                                                                                             expected_py_values: None,                                                                                             values: [                                                                                                 Py(                                                                                                     0x00007fa14bd71ce0,                                                                                                 ),                                                                                             ],                                                                                         },                                                                                         expected_repr: "'stl'",                                                                                         name: "literal['stl']",                                                                                     },                                                                                 ),                                                                                 validate_default: false,                                                                                 copy_default: false,                                                                                 name: "default[literal['stl']]",                                                                                 undefined: Py(                                                                                     0x00007fa14d802350,                                                                                 ),                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                     Field {                                                                         name: "units",                                                                         lookup_key: Simple {                                                                             key: "units",                                                                             py_key: Py(                                                                                 0x00007fa14adc47e0,                                                                             ),                                                                             path: LookupPath(                                                                                 [                                                                                     S(                                                                                         "units",                                                                                         Py(                                                                                             0x00007fa14adc4900,                                                                                         ),                                                                                     ),                                                                                 ],                                                                             ),                                                                         },                                                                         name_py: Py(                                                                             0x00007fa14e6aeac0,                                                                         ),                                                                         validator: DefinitionRef(                                                                             DefinitionRefValidator {                                                                                 definition: "...",                                                                             },                                                                         ),                                                                         frozen: false,                                                                     },                                                                 ],                                                                 model_name: "OptionStl",                                                                 extra_behavior: Ignore,                                                                 extras_validator: None,                                                                 strict: false,                                                                 from_attributes: false,                                                                 loc_by_alias: true,                                                             },                                                         ),                                                         class: Py(                                                             0x000055eb034c2800,                                                         ),                                                         post_init: None,                                                         frozen: false,                                                         custom_init: false,                                                         root_model: false,                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                         name: "OptionStl",                                                     },                                                 ),                                             ],                                         },                                         from_attributes: true,                                         strict: false,                                         custom_error: None,                                         tags_repr: "'fbx', 'gltf', 'obj', 'ply', 'sldprt', 'step', 'stl'",                                         discriminator_repr: "'type'",                                         name: "tagged-union[OptionFbx,OptionGltf,OptionObj,OptionPly,OptionSldprt,OptionStep,OptionStl]",                                     },                                 ),                                 class: Py(                                     0x000055eb02f8f8e0,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: true,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc5980,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc59b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc6b870,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "import_files": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc6b870,                                                 ),                                             ],                                         },                                         expected_repr: "'import_files'",                                         name: "literal['import_files']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['import_files']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionImportFiles",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b62c40,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionImportFiles",     }, ), definitions=[StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb034c76d0), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"ft": 1, "m": 3, "mm": 4, "yd": 5, "cm": 0, "in": 2}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b3c4c50), Py(0x7fa14b3c51f0), Py(0x7fa14b3c52b0), Py(0x7fa14b3c5310), Py(0x7fa14b3c5370), Py(0x7fa14b3c53d0)] }, missing: None, expected_repr: "'cm', 'ft', 'in', 'm', 'mm' or 'yd'", strict: false, class_repr: "UnitLength", name: "str-enum[UnitLength]" }), StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb02f8b040), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"y": 0, "z": 1}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b3c4e90), Py(0x7fa14b3c4ef0)] }, missing: None, expected_repr: "'y' or 'z'", strict: false, class_repr: "Axis", name: "str-enum[Axis]" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "forward", lookup_key: Simple { key: "forward", py_key: Py(0x7fa14adc55c0), path: LookupPath([S("forward", Py(0x7fa14adc51d0))]) }, name_py: Py(0x7fa14bd71cb0), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }, Field { name: "up", lookup_key: Simple { key: "up", py_key: Py(0x7fa14adc5320), path: LookupPath([S("up", Py(0x7fa14adc5380))]) }, name_py: Py(0x7fa14d9ed0b0), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }], model_name: "System", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb034cb8e0), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "System" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "axis", lookup_key: Simple { key: "axis", py_key: Py(0x7fa14adc5350), path: LookupPath([S("axis", Py(0x7fa14adc53e0))]) }, name_py: Py(0x7fa14c13dce0), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }, Field { name: "direction", lookup_key: Simple { key: "direction", py_key: Py(0x7fa14add22f0), path: LookupPath([S("direction", Py(0x7fa14add3c30))]) }, name_py: Py(0x7fa14e41ef30), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }], model_name: "AxisDirectionPair", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb02f8c440), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "AxisDirectionPair" }), StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb02f8ba40), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"positive": 0, "negative": 1}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b3c5010), Py(0x7fa14b3c5070)] }, missing: None, expected_repr: "'positive' or 'negative'", strict: false, class_repr: "Direction", name: "str-enum[Direction]" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, files: List[kittycad.models.import_file.ImportFile], format: pydantic.root_model.RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], type: Literal['import_files'] = 'import_files') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

files: List[ImportFile]

format: RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'files': FieldInfo(annotation=List[ImportFile], required=True), 'format': FieldInfo(annotation=RootModel[Annotated[Union[OptionFbx, OptionGltf, OptionObj, OptionPly, OptionSldprt, OptionStep, OptionStl], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], required=True), 'type': FieldInfo(annotation=Literal['import_files'], required=False, default='import_files')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['import_files']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionLoft(**data)

Command for lofting sections to create a solid

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'base_curve_index': typing.Optional[int], 'bez_approximate_rational': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'section_ids': typing.List[str], 'tolerance': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['loft'], 'v_degree': <class 'int'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionLoft'>, 'config': {'title': 'OptionLoft'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionLoft'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionLoft'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionLoft:94467866601168', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'base_curve_index': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'bez_approximate_rational': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'section_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'tolerance': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'loft', 'schema': {'expected': ['loft'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'v_degree': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}}, 'model_name': 'OptionLoft', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a1a6d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "section_ids": SerField {                         key_py: Py(                             0x00007fa14d6a0bf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14c15eee0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "loft",                                             },                                             expected_py: None,                                             name: "literal['loft']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "base_curve_index": SerField {                         key_py: Py(                             0x00007fa14afe0ab0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Int(                                                 IntSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "tolerance": SerField {                         key_py: Py(                             0x00007fa14afd8570,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "bez_approximate_rational": SerField {                         key_py: Py(                             0x00007fa14afb79b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "v_degree": SerField {                         key_py: Py(                             0x00007fa14afe0b70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Int(                                 IntSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 6,             },         ),         has_extra: false,         root_model: false,         name: "OptionLoft",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionLoft", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "base_curve_index",                         lookup_key: Simple {                             key: "base_curve_index",                             py_key: Py(                                 0x00007fa14ae3a6f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "base_curve_index",                                         Py(                                             0x00007fa14ae3a5f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe0ab0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Int(                                             IntValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[int]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[int]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "bez_approximate_rational",                         lookup_key: Simple {                             key: "bez_approximate_rational",                             py_key: Py(                                 0x00007fa14b009020,                             ),                             path: LookupPath(                                 [                                     S(                                         "bez_approximate_rational",                                         Py(                                             0x00007fa14b00a150,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afb79b0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "section_ids",                         lookup_key: Simple {                             key: "section_ids",                             py_key: Py(                                 0x00007fa14ae3a530,                             ),                             path: LookupPath(                                 [                                     S(                                         "section_ids",                                         Py(                                             0x00007fa14ae3a5b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d6a0bf0,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "tolerance",                         lookup_key: Simple {                             key: "tolerance",                             py_key: Py(                                 0x00007fa14ae3acb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "tolerance",                                         Py(                                             0x00007fa14ae3b130,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd8570,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14ae3a080,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe4b70,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe4cc0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14c15eee0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "loft": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14c15eee0,                                                 ),                                             ],                                         },                                         expected_repr: "'loft'",                                         name: "literal['loft']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['loft']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "v_degree",                         lookup_key: Simple {                             key: "v_degree",                             py_key: Py(                                 0x00007fa14ae3a1f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "v_degree",                                         Py(                                             0x00007fa14ae3a1b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe0b70,                         ),                         validator: Int(                             IntValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionLoft",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a1a6d0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionLoft",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, base_curve_index: Optional[int] = None, bez_approximate_rational: bool, section_ids: List[str], tolerance: kittycad.models.length_unit.LengthUnit, type: Literal['loft'] = 'loft', v_degree: int) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

base_curve_index: Optional[int]

bez_approximate_rational: bool

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'base_curve_index': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'bez_approximate_rational': FieldInfo(annotation=bool, required=True), 'section_ids': FieldInfo(annotation=List[str], required=True), 'tolerance': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['loft'], required=False, default='loft'), 'v_degree': FieldInfo(annotation=int, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

section_ids: List[str]

tolerance: LengthUnit

type: Literal['loft']

classmethod update_forward_refs(**localns)

Return type:

None

v_degree: int

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionMakeAxesGizmo(**data)

Add a gizmo showing the axes.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'clobber': <class 'bool'>, 'gizmo_mode': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['make_axes_gizmo']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionMakeAxesGizmo'>, 'config': {'title': 'OptionMakeAxesGizmo'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionMakeAxesGizmo'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionMakeAxesGizmo'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionMakeAxesGizmo:94467867809456', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'clobber': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'gizmo_mode': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'make_axes_gizmo', 'schema': {'expected': ['make_axes_gizmo'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMakeAxesGizmo', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b416b0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc69c30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "make_axes_gizmo",                                             },                                             expected_py: None,                                             name: "literal['make_axes_gizmo']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "clobber": SerField {                         key_py: Py(                             0x00007fa14afe6e20,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "gizmo_mode": SerField {                         key_py: Py(                             0x00007fa14b01f930,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionMakeAxesGizmo",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMakeAxesGizmo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "clobber",                         lookup_key: Simple {                             key: "clobber",                             py_key: Py(                                 0x00007fa14ad54120,                             ),                             path: LookupPath(                                 [                                     S(                                         "clobber",                                         Py(                                             0x00007fa14ad556b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe6e20,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "gizmo_mode",                         lookup_key: Simple {                             key: "gizmo_mode",                             py_key: Py(                                 0x00007fa14adaacf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "gizmo_mode",                                         Py(                                             0x00007fa14adaab70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01f930,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad55290,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad55680,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc69c30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "make_axes_gizmo": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc69c30,                                                 ),                                             ],                                         },                                         expected_repr: "'make_axes_gizmo'",                                         name: "literal['make_axes_gizmo']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['make_axes_gizmo']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMakeAxesGizmo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b416b0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionMakeAxesGizmo",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, clobber: bool, gizmo_mode: bool, type: Literal['make_axes_gizmo'] = 'make_axes_gizmo') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

clobber: bool

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

gizmo_mode: bool

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'clobber': FieldInfo(annotation=bool, required=True), 'gizmo_mode': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['make_axes_gizmo'], required=False, default='make_axes_gizmo')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['make_axes_gizmo']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionMakeOffsetPath(**data)

Make a new path by offsetting an object by a given distance. The new path’s ID will be the ID of this command.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'face_id': typing.Optional[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'offset': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['make_offset_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionMakeOffsetPath'>, 'config': {'title': 'OptionMakeOffsetPath'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionMakeOffsetPath'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionMakeOffsetPath'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionMakeOffsetPath:94467868287136', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'face_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'offset': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'make_offset_path', 'schema': {'expected': ['make_offset_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMakeOffsetPath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03bb60a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "face_id": SerField {                         key_py: Py(                             0x00007fa14b32c8a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Str(                                                 StrSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "offset": SerField {                         key_py: Py(                             0x00007fa14fa3a7c0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc69f30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "make_offset_path",                                             },                                             expected_py: None,                                             name: "literal['make_offset_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionMakeOffsetPath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMakeOffsetPath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "face_id",                         lookup_key: Simple {                             key: "face_id",                             py_key: Py(                                 0x00007fa14ae028e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "face_id",                                         Py(                                             0x00007fa14ae02910,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b32c8a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Str(                                             StrValidator {                                                 strict: false,                                                 coerce_numbers_to_str: false,                                             },                                         ),                                         name: "nullable[str]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[str]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af1dbb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ae25f30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "offset",                         lookup_key: Simple {                             key: "offset",                             py_key: Py(                                 0x00007fa14ae02940,                             ),                             path: LookupPath(                                 [                                     S(                                         "offset",                                         Py(                                             0x00007fa14ae02970,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3a7c0,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14ae25ec0,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae029a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae029d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc69f30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "make_offset_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc69f30,                                                 ),                                             ],                                         },                                         expected_repr: "'make_offset_path'",                                         name: "literal['make_offset_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['make_offset_path']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMakeOffsetPath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03bb60a0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionMakeOffsetPath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, face_id: Optional[str] = None, object_id: str, offset: kittycad.models.length_unit.LengthUnit, type: Literal['make_offset_path'] = 'make_offset_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

face_id: Optional[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'face_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'object_id': FieldInfo(annotation=str, required=True), 'offset': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['make_offset_path'], required=False, default='make_offset_path')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

offset: LengthUnit

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['make_offset_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionMakePlane(**data)

Make a new plane

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'clobber': <class 'bool'>, 'hide': typing.Optional[bool], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'origin': <class 'kittycad.models.point3d.Point3d'>, 'size': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['make_plane'], 'x_axis': <class 'kittycad.models.point3d.Point3d'>, 'y_axis': <class 'kittycad.models.point3d.Point3d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionMakePlane'>, 'config': {'title': 'OptionMakePlane'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionMakePlane'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionMakePlane'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionMakePlane:94467867591680', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'clobber': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'hide': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'bool'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'origin': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'size': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'make_plane', 'schema': {'expected': ['make_plane'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'x_axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'y_axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'OptionMakePlane', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b0c400,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "clobber": SerField {                         key_py: Py(                             0x00007fa14afe6e20,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "origin": SerField {                         key_py: Py(                             0x00007fa14fa3aa98,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "hide": SerField {                         key_py: Py(                             0x00007fa14e246f10,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Bool(                                                 BoolSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bc68d30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "make_plane",                                             },                                             expected_py: None,                                             name: "literal['make_plane']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "y_axis": SerField {                         key_py: Py(                             0x00007fa14b063030,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "size": SerField {                         key_py: Py(                             0x00007fa14fa3ba40,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "x_axis": SerField {                         key_py: Py(                             0x00007fa14b062f40,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 7,             },         ),         has_extra: false,         root_model: false,         name: "OptionMakePlane",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55eb0330e750), serializer: Fields(GeneralFieldsSerializer { fields: {"x": SerField { key_py: Py(0x7fa14fa3e140), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7fa14fa3e1a0), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7fa14fa3e170), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMakePlane", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "clobber",                         lookup_key: Simple {                             key: "clobber",                             py_key: Py(                                 0x00007fa14ae779c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "clobber",                                         Py(                                             0x00007fa14ae779f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe6e20,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "hide",                         lookup_key: Simple {                             key: "hide",                             py_key: Py(                                 0x00007fa14ae77a20,                             ),                             path: LookupPath(                                 [                                     S(                                         "hide",                                         Py(                                             0x00007fa14ae77a50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e246f10,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Bool(                                             BoolValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[bool]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[bool]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "origin",                         lookup_key: Simple {                             key: "origin",                             py_key: Py(                                 0x00007fa14ae77a80,                             ),                             path: LookupPath(                                 [                                     S(                                         "origin",                                         Py(                                             0x00007fa14ae77ab0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3aa98,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "size",                         lookup_key: Simple {                             key: "size",                             py_key: Py(                                 0x00007fa14ae77ae0,                             ),                             path: LookupPath(                                 [                                     S(                                         "size",                                         Py(                                             0x00007fa14ae77b10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3ba40,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14ad50c80,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae77b40,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae77b70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bc68d30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "make_plane": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bc68d30,                                                 ),                                             ],                                         },                                         expected_repr: "'make_plane'",                                         name: "literal['make_plane']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['make_plane']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "x_axis",                         lookup_key: Simple {                             key: "x_axis",                             py_key: Py(                                 0x00007fa14ae77ba0,                             ),                             path: LookupPath(                                 [                                     S(                                         "x_axis",                                         Py(                                             0x00007fa14ae77bd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b062f40,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "y_axis",                         lookup_key: Simple {                             key: "y_axis",                             py_key: Py(                                 0x00007fa14ae77c00,                             ),                             path: LookupPath(                                 [                                     S(                                         "y_axis",                                         Py(                                             0x00007fa14ae77c30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b063030,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMakePlane",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b0c400,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionMakePlane",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fa14fa3e140), path: LookupPath([S("x", Py(0x7fa14fa3e140))]) }, name_py: Py(0x7fa14fa3e140), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fa14fa3e170), path: LookupPath([S("y", Py(0x7fa14fa3e170))]) }, name_py: Py(0x7fa14fa3e170), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fa14fa3e1a0), path: LookupPath([S("z", Py(0x7fa14fa3e1a0))]) }, name_py: Py(0x7fa14fa3e1a0), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb0330e750), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, clobber: bool, hide: Optional[bool] = None, origin: kittycad.models.point3d.Point3d, size: kittycad.models.length_unit.LengthUnit, type: Literal['make_plane'] = 'make_plane', x_axis: kittycad.models.point3d.Point3d, y_axis: kittycad.models.point3d.Point3d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

clobber: bool

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

hide: Optional[bool]

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'clobber': FieldInfo(annotation=bool, required=True), 'hide': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'origin': FieldInfo(annotation=Point3d, required=True), 'size': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['make_plane'], required=False, default='make_plane'), 'x_axis': FieldInfo(annotation=Point3d, required=True), 'y_axis': FieldInfo(annotation=Point3d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

origin: Point3d

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

size: LengthUnit

type: Literal['make_plane']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

x_axis: Point3d

y_axis: Point3d

class kittycad.models.modeling_cmd.OptionMass(**data)

Get the mass of entities in the scene or the default scene.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_ids': typing.List[str], 'material_density': <class 'float'>, 'material_density_unit': <enum 'UnitDensity'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'output_unit': <enum 'UnitMass'>, 'type': typing.Literal['mass']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionMass'>, 'config': {'title': 'OptionMass'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionMass'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionMass'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionMass:94467868035824', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'material_density': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'material_density_unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitDensity'>, 'members': [UnitDensity.LB_FT3, UnitDensity.KG_M3], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_density.UnitDensity:94467863217504', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'output_unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitMass'>, 'members': [UnitMass.G, UnitMass.KG, UnitMass.LB], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_mass.UnitMass:94467863219280', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'mass', 'schema': {'expected': ['mass'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMass', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b78af0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_ids": SerField {                         key_py: Py(                             0x00007fa14b038970,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "material_density_unit": SerField {                         key_py: Py(                             0x00007fa14bb4f8f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb036e0560,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14c15f240,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "mass",                                             },                                             expected_py: None,                                             name: "literal['mass']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "material_density": SerField {                         key_py: Py(                             0x00007fa14bb4f870,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "output_unit": SerField {                         key_py: Py(                             0x00007fa14bb4f470,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb036e0c50,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 5,             },         ),         has_extra: false,         root_model: false,         name: "OptionMass",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMass", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_ids",                         lookup_key: Simple {                             key: "entity_ids",                             py_key: Py(                                 0x00007fa14ade8df0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_ids",                                         Py(                                             0x00007fa14ade8db0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b038970,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "material_density",                         lookup_key: Simple {                             key: "material_density",                             py_key: Py(                                 0x00007fa14ade8e70,                             ),                             path: LookupPath(                                 [                                     S(                                         "material_density",                                         Py(                                             0x00007fa14ade8e30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bb4f870,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "material_density_unit",                         lookup_key: Simple {                             key: "material_density_unit",                             py_key: Py(                                 0x00007fa14ade8eb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "material_density_unit",                                         Py(                                             0x00007fa14ade8ef0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bb4f8f0,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb036e0560,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "lb:ft3": 0,                                             "kg:m3": 1,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b3c7cb0,                                         ),                                         Py(                                             0x00007fa14b3c7d10,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'lb:ft3' or 'kg:m3'",                                 strict: false,                                 class_repr: "UnitDensity",                                 name: "str-enum[UnitDensity]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "output_unit",                         lookup_key: Simple {                             key: "output_unit",                             py_key: Py(                                 0x00007fa14bd84070,                             ),                             path: LookupPath(                                 [                                     S(                                         "output_unit",                                         Py(                                             0x00007fa14ade8f30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bb4f470,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb036e0c50,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "g": 0,                                             "kg": 1,                                             "lb": 2,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b3c7dd0,                                         ),                                         Py(                                             0x00007fa14b3c7e30,                                         ),                                         Py(                                             0x00007fa14b3c7e90,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'g', 'kg' or 'lb'",                                 strict: false,                                 class_repr: "UnitMass",                                 name: "str-enum[UnitMass]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc6670,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc66d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14c15f240,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "mass": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14c15f240,                                                 ),                                             ],                                         },                                         expected_repr: "'mass'",                                         name: "literal['mass']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['mass']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMass",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b78af0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionMass",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_ids: List[str], material_density: float, material_density_unit: kittycad.models.unit_density.UnitDensity, output_unit: kittycad.models.unit_mass.UnitMass, type: Literal['mass'] = 'mass') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_ids: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

material_density: float

material_density_unit: UnitDensity

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_ids': FieldInfo(annotation=List[str], required=True), 'material_density': FieldInfo(annotation=float, required=True), 'material_density_unit': FieldInfo(annotation=UnitDensity, required=True), 'output_unit': FieldInfo(annotation=UnitMass, required=True), 'type': FieldInfo(annotation=Literal['mass'], required=False, default='mass')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

output_unit: UnitMass

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['mass']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionMouseClick(**data)

Send a mouse click event Updates modified/selected entities.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['mouse_click'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionMouseClick'>, 'config': {'title': 'OptionMouseClick'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionMouseClick'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionMouseClick'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionMouseClick:94467867651552', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'mouse_click', 'schema': {'expected': ['mouse_click'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionMouseClick', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b1ade0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd79670,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "mouse_click",                                             },                                             expected_py: None,                                             name: "literal['mouse_click']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionMouseClick",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMouseClick", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae74810,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae74750,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd79670,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "mouse_click": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd79670,                                                 ),                                             ],                                         },                                         expected_repr: "'mouse_click'",                                         name: "literal['mouse_click']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['mouse_click']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14ae762e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14ad542d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad53280,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad53280,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMouseClick",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b1ade0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionMouseClick",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['mouse_click'] = 'mouse_click', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['mouse_click'], required=False, default='mouse_click'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['mouse_click']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionMouseMove(**data)

Send a mouse move event

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'sequence': typing.Optional[int], 'type': typing.Literal['mouse_move'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionMouseMove'>, 'config': {'title': 'OptionMouseMove'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionMouseMove'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionMouseMove'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionMouseMove:94467867642240', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'sequence': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'mouse_move', 'schema': {'expected': ['mouse_move'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionMouseMove', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b18980,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "sequence": SerField {                         key_py: Py(                             0x00007fa14fa3b790,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Int(                                                 IntSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd796f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "mouse_move",                                             },                                             expected_py: None,                                             name: "literal['mouse_move']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionMouseMove",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMouseMove", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "sequence",                         lookup_key: Simple {                             key: "sequence",                             py_key: Py(                                 0x00007fa14ad65870,                             ),                             path: LookupPath(                                 [                                     S(                                         "sequence",                                         Py(                                             0x00007fa14ad65830,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3b790,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Int(                                             IntValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[int]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[int]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad54390,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad54450,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd796f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "mouse_move": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd796f0,                                                 ),                                             ],                                         },                                         expected_repr: "'mouse_move'",                                         name: "literal['mouse_move']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['mouse_move']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14ad54480,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14ad54420,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad65700,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14ad65700,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMouseMove",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b18980,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionMouseMove",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, sequence: Optional[int] = None, type: Literal['mouse_move'] = 'mouse_move', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'sequence': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['mouse_move'], required=False, default='mouse_move'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

sequence: Optional[int]

type: Literal['mouse_move']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionMovePathPen(**data)

Move the path’s “pen”. If you’re in sketch mode, these coordinates are in the local coordinate system, not the world’s coordinate system. For example, say you’re sketching on the plane {x: (1,0,0), y: (0,1,0), origin: (0, 0, 50)}. In other words, the plane 50 units above the default XY plane. Then, moving the pen to (1, 1, 0) with this command uses local coordinates. So, it would move the pen to (1, 1, 50) in global coordinates.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'to': <class 'kittycad.models.point3d.Point3d'>, 'type': typing.Literal['move_path_pen']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionMovePathPen'>, 'config': {'title': 'OptionMovePathPen'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionMovePathPen'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionMovePathPen'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionMovePathPen:94467866442672', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'path': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'type': 'no-info'}, 'schema': {'type': 'str'}, 'type': 'function-after'}, 'type': 'model-field'}, 'to': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'move_path_pen', 'schema': {'expected': ['move_path_pen'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionMovePathPen', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb039f3bb0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "path": SerField {                         key_py: Py(                             0x00007fa14fa3ac30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd79770,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "move_path_pen",                                             },                                             expected_py: None,                                             name: "literal['move_path_pen']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "to": SerField {                         key_py: Py(                             0x00007fa14eb8b120,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0330e750,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "z": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e1a0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 3,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point3d",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionMovePathPen",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionMovePathPen", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "path",                         lookup_key: Simple {                             key: "path",                             py_key: Py(                                 0x00007fa14afe5140,                             ),                             path: LookupPath(                                 [                                     S(                                         "path",                                         Py(                                             0x00007fa14afe5170,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3ac30,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Str(                                     StrValidator {                                         strict: false,                                         coerce_numbers_to_str: false,                                     },                                 ),                                 func: Py(                                     0x000055eb039991a0,                                 ),                                 config: Py(                                     0x00007fa14afe1a80,                                 ),                                 name: "function-after[ModelingCmdId(), str]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "to",                         lookup_key: Simple {                             key: "to",                             py_key: Py(                                 0x00007fa14afe51a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "to",                                         Py(                                             0x00007fa14afe51d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14eb8b120,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "z",                                                 lookup_key: Simple {                                                     key: "z",                                                     py_key: Py(                                                         0x00007fa14fa3e1a0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "z",                                                                 Py(                                                                     0x00007fa14fa3e1a0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e1a0,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point3d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0330e750,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point3d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe5200,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe5230,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd79770,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "move_path_pen": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd79770,                                                 ),                                             ],                                         },                                         expected_repr: "'move_path_pen'",                                         name: "literal['move_path_pen']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['move_path_pen']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionMovePathPen",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb039f3bb0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionMovePathPen",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, path: kittycad.models.modeling_cmd_id.ModelingCmdId, to: kittycad.models.point3d.Point3d, type: Literal['move_path_pen'] = 'move_path_pen') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'path': FieldInfo(annotation=ModelingCmdId, required=True), 'to': FieldInfo(annotation=Point3d, required=True), 'type': FieldInfo(annotation=Literal['move_path_pen'], required=False, default='move_path_pen')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path: ModelingCmdId

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

to: Point3d

type: Literal['move_path_pen']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionNewAnnotation(**data)

Create a new annotation

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'annotation_type': <enum 'AnnotationType'>, 'clobber': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'options': <class 'kittycad.models.annotation_options.AnnotationOptions'>, 'type': typing.Literal['new_annotation']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <enum 'AnnotationLineEnd'>, 'members': [AnnotationLineEnd.NONE, AnnotationLineEnd.ARROW], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.annotation_line_end.AnnotationLineEnd:94467860848624', 'sub_type': 'str', 'type': 'enum'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionNewAnnotation'>, 'config': {'title': 'OptionNewAnnotation'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionNewAnnotation'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionNewAnnotation'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionNewAnnotation:94467867232592', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'annotation_type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'AnnotationType'>, 'members': [AnnotationType.T2D, AnnotationType.T3D], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.annotation_type.AnnotationType:94467862345408', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'clobber': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'options': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.annotation_options.AnnotationOptions'>, 'config': {'title': 'AnnotationOptions'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.annotation_options.AnnotationOptions'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.annotation_options.AnnotationOptions'>>]}, 'ref': 'kittycad.models.annotation_options.AnnotationOptions:94467859218624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'color': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.color.Color'>, 'config': {'title': 'Color'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.color.Color'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.color.Color'>>]}, 'ref': 'kittycad.models.color.Color:94467859422064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'a': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'b': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'g': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'r': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Color', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'line_ends': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.annotation_line_end_options.AnnotationLineEndOptions'>, 'config': {'title': 'AnnotationLineEndOptions'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.annotation_line_end_options.AnnotationLineEndOptions'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.annotation_line_end_options.AnnotationLineEndOptions'>>]}, 'ref': 'kittycad.models.annotation_line_end_options.AnnotationLineEndOptions:94467862299104', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'end': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.annotation_line_end.AnnotationLineEnd:94467860848624', 'type': 'definition-ref'}, 'type': 'model-field'}, 'start': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.annotation_line_end.AnnotationLineEnd:94467860848624', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'AnnotationLineEndOptions', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'line_width': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'position': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'text': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.annotation_text_options.AnnotationTextOptions'>, 'config': {'title': 'AnnotationTextOptions'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.annotation_text_options.AnnotationTextOptions'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.annotation_text_options.AnnotationTextOptions'>>]}, 'ref': 'kittycad.models.annotation_text_options.AnnotationTextOptions:94467859412128', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'point_size': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'text': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'AnnotationTextAlignmentX'>, 'members': [AnnotationTextAlignmentX.LEFT, AnnotationTextAlignmentX.CENTER, AnnotationTextAlignmentX.RIGHT], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.annotation_text_alignment_x.AnnotationTextAlignmentX:94467862308832', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'AnnotationTextAlignmentY'>, 'members': [AnnotationTextAlignmentY.BOTTOM, AnnotationTextAlignmentY.CENTER, AnnotationTextAlignmentY.TOP], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.annotation_text_alignment_y.AnnotationTextAlignmentY:94467859410352', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'AnnotationTextOptions', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'AnnotationOptions', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'new_annotation', 'schema': {'expected': ['new_annotation'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionNewAnnotation', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ab4950,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "options": SerField {                         key_py: Py(                             0x00007fa14fa3aa38,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb033100c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "line_ends": SerField {                                                     key_py: Py(                                                         0x00007fa14b1d3770,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb036001e0,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "start": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3bce8,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Recursive(                                                                                                         DefinitionRefSerializer {                                                                                                             definition: "...",                                                                                                             retry_with_lax_check: false,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "end": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa38368,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Recursive(                                                                                                         DefinitionRefSerializer {                                                                                                             definition: "...",                                                                                                             retry_with_lax_check: false,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 2,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "AnnotationLineEndOptions",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "position": SerField {                                                     key_py: Py(                                                         0x00007fa14e255bf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb0330e750,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "x": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e140,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "y": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e170,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "z": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e1a0,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 3,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "Point3d",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "color": SerField {                                                     key_py: Py(                                                         0x00007fa14ea1a040,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb03341b70,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "g": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3de10,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "r": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e020,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "a": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3dcf0,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "b": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3dd20,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 4,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "Color",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "text": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3c298,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb0333f4a0,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "text": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3c298,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Str(                                                                                                         StrSerializer,                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "y": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e170,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Enum(                                                                                                         EnumSerializer {                                                                                                             class: Py(                                                                                                                 0x000055eb0333edb0,                                                                                                             ),                                                                                                             serializer: Some(                                                                                                                 Str(                                                                                                                     StrSerializer,                                                                                                                 ),                                                                                                             ),                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "point_size": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14b2a67b0,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Int(                                                                                                         IntSerializer,                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "x": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e140,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Enum(                                                                                                         EnumSerializer {                                                                                                             class: Py(                                                                                                                 0x000055eb036027e0,                                                                                                             ),                                                                                                             serializer: Some(                                                                                                                 Str(                                                                                                                     StrSerializer,                                                                                                                 ),                                                                                                             ),                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 4,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "AnnotationTextOptions",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "line_width": SerField {                                                     key_py: Py(                                                         0x00007fa14b1d37f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 5,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "AnnotationOptions",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd797f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "new_annotation",                                             },                                             expected_py: None,                                             name: "literal['new_annotation']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "annotation_type": SerField {                         key_py: Py(                             0x00007fa14e8602f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb0360b6c0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "clobber": SerField {                         key_py: Py(                             0x00007fa14afe6e20,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionNewAnnotation",     }, ), definitions=[Enum(EnumSerializer { class: Py(0x55eb0349dff0), serializer: Some(Str(StrSerializer)) })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionNewAnnotation", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "annotation_type",                         lookup_key: Simple {                             key: "annotation_type",                             py_key: Py(                                 0x00007fa14aefdd30,                             ),                             path: LookupPath(                                 [                                     S(                                         "annotation_type",                                         Py(                                             0x00007fa14aefdcf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e8602f0,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb0360b6c0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "t3d": 1,                                             "t2d": 0,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b362570,                                         ),                                         Py(                                             0x00007fa14b3625d0,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'t2d' or 't3d'",                                 strict: false,                                 class_repr: "AnnotationType",                                 name: "str-enum[AnnotationType]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "clobber",                         lookup_key: Simple {                             key: "clobber",                             py_key: Py(                                 0x00007fa14b025c80,                             ),                             path: LookupPath(                                 [                                     S(                                         "clobber",                                         Py(                                             0x00007fa14b025da0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe6e20,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "options",                         lookup_key: Simple {                             key: "options",                             py_key: Py(                                 0x00007fa14b024c30,                             ),                             path: LookupPath(                                 [                                     S(                                         "options",                                         Py(                                             0x00007fa14b024a50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3aa38,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "color",                                                 lookup_key: Simple {                                                     key: "color",                                                     py_key: Py(                                                         0x00007fa14b025e30,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "color",                                                                 Py(                                                                     0x00007fa14b025bc0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14ea1a040,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "a",                                                                                         lookup_key: Simple {                                                                                             key: "a",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3dcf0,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "a",                                                                                                         Py(                                                                                                             0x00007fa14fa3dcf0,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3dcf0,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "b",                                                                                         lookup_key: Simple {                                                                                             key: "b",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3dd20,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "b",                                                                                                         Py(                                                                                                             0x00007fa14fa3dd20,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3dd20,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "g",                                                                                         lookup_key: Simple {                                                                                             key: "g",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3de10,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "g",                                                                                                         Py(                                                                                                             0x00007fa14fa3de10,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3de10,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "r",                                                                                         lookup_key: Simple {                                                                                             key: "r",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e020,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "r",                                                                                                         Py(                                                                                                             0x00007fa14fa3e020,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e020,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "Color",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055eb03341b70,                                                                         ),                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                         name: "Color",                                                                     },                                                                 ),                                                                 name: "nullable[Color]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Color]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "line_ends",                                                 lookup_key: Simple {                                                     key: "line_ends",                                                     py_key: Py(                                                         0x00007fa14aefddb0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "line_ends",                                                                 Py(                                                                     0x00007fa14aefdd70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14b1d3770,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "end",                                                                                         lookup_key: Simple {                                                                                             key: "end",                                                                                             py_key: Py(                                                                                                 0x00007fa14b025c20,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "end",                                                                                                         Py(                                                                                                             0x00007fa14b025ad0,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa38368,                                                                                         ),                                                                                         validator: DefinitionRef(                                                                                             DefinitionRefValidator {                                                                                                 definition: "...",                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "start",                                                                                         lookup_key: Simple {                                                                                             key: "start",                                                                                             py_key: Py(                                                                                                 0x00007fa14b025e60,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "start",                                                                                                         Py(                                                                                                             0x00007fa14b025b00,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3bce8,                                                                                         ),                                                                                         validator: DefinitionRef(                                                                                             DefinitionRefValidator {                                                                                                 definition: "...",                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "AnnotationLineEndOptions",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055eb036001e0,                                                                         ),                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                         name: "AnnotationLineEndOptions",                                                                     },                                                                 ),                                                                 name: "nullable[AnnotationLineEndOptions]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[AnnotationLineEndOptions]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "line_width",                                                 lookup_key: Simple {                                                     key: "line_width",                                                     py_key: Py(                                                         0x00007fa14aefddf0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "line_width",                                                                 Py(                                                                     0x00007fa14aefde30,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14b1d37f0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 name: "nullable[float]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[float]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "position",                                                 lookup_key: Simple {                                                     key: "position",                                                     py_key: Py(                                                         0x00007fa14aefde70,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "position",                                                                 Py(                                                                     0x00007fa14aefdeb0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14e255bf0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "x",                                                                                         lookup_key: Simple {                                                                                             key: "x",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e140,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "x",                                                                                                         Py(                                                                                                             0x00007fa14fa3e140,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e140,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "y",                                                                                         lookup_key: Simple {                                                                                             key: "y",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e170,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "y",                                                                                                         Py(                                                                                                             0x00007fa14fa3e170,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e170,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "z",                                                                                         lookup_key: Simple {                                                                                             key: "z",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e1a0,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "z",                                                                                                         Py(                                                                                                             0x00007fa14fa3e1a0,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e1a0,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "Point3d",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055eb0330e750,                                                                         ),                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                         name: "Point3d",                                                                     },                                                                 ),                                                                 name: "nullable[Point3d]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Point3d]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "text",                                                 lookup_key: Simple {                                                     key: "text",                                                     py_key: Py(                                                         0x00007fa14b0c68e0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "text",                                                                 Py(                                                                     0x00007fa14b0250b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3c298,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "point_size",                                                                                         lookup_key: Simple {                                                                                             key: "point_size",                                                                                             py_key: Py(                                                                                                 0x00007fa14aefdef0,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "point_size",                                                                                                         Py(                                                                                                             0x00007fa14aefdf30,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14b2a67b0,                                                                                         ),                                                                                         validator: Int(                                                                                             IntValidator {                                                                                                 strict: false,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "text",                                                                                         lookup_key: Simple {                                                                                             key: "text",                                                                                             py_key: Py(                                                                                                 0x00007fa14b024a80,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "text",                                                                                                         Py(                                                                                                             0x00007fa14b024c90,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3c298,                                                                                         ),                                                                                         validator: Str(                                                                                             StrValidator {                                                                                                 strict: false,                                                                                                 coerce_numbers_to_str: false,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "x",                                                                                         lookup_key: Simple {                                                                                             key: "x",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e140,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "x",                                                                                                         Py(                                                                                                             0x00007fa14fa3e140,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e140,                                                                                         ),                                                                                         validator: StrEnum(                                                                                             EnumValidator {                                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                                 class: Py(                                                                                                     0x000055eb036027e0,                                                                                                 ),                                                                                                 lookup: LiteralLookup {                                                                                                     expected_bool: None,                                                                                                     expected_int: None,                                                                                                     expected_str: Some(                                                                                                         {                                                                                                             "center": 1,                                                                                                             "right": 2,                                                                                                             "left": 0,                                                                                                         },                                                                                                     ),                                                                                                     expected_py_dict: None,                                                                                                     expected_py_values: None,                                                                                                     values: [                                                                                                         Py(                                                                                                             0x00007fa14b361f10,                                                                                                         ),                                                                                                         Py(                                                                                                             0x00007fa14b361f70,                                                                                                         ),                                                                                                         Py(                                                                                                             0x00007fa14b361fd0,                                                                                                         ),                                                                                                     ],                                                                                                 },                                                                                                 missing: None,                                                                                                 expected_repr: "'left', 'center' or 'right'",                                                                                                 strict: false,                                                                                                 class_repr: "AnnotationTextAlignmentX",                                                                                                 name: "str-enum[AnnotationTextAlignmentX]",                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "y",                                                                                         lookup_key: Simple {                                                                                             key: "y",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e170,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "y",                                                                                                         Py(                                                                                                             0x00007fa14fa3e170,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e170,                                                                                         ),                                                                                         validator: StrEnum(                                                                                             EnumValidator {                                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                                 class: Py(                                                                                                     0x000055eb0333edb0,                                                                                                 ),                                                                                                 lookup: LiteralLookup {                                                                                                     expected_bool: None,                                                                                                     expected_int: None,                                                                                                     expected_str: Some(                                                                                                         {                                                                                                             "center": 1,                                                                                                             "top": 2,                                                                                                             "bottom": 0,                                                                                                         },                                                                                                     ),                                                                                                     expected_py_dict: None,                                                                                                     expected_py_values: None,                                                                                                     values: [                                                                                                         Py(                                                                                                             0x00007fa14b3620f0,                                                                                                         ),                                                                                                         Py(                                                                                                             0x00007fa14b362150,                                                                                                         ),                                                                                                         Py(                                                                                                             0x00007fa14b3621b0,                                                                                                         ),                                                                                                     ],                                                                                                 },                                                                                                 missing: None,                                                                                                 expected_repr: "'bottom', 'center' or 'top'",                                                                                                 strict: false,                                                                                                 class_repr: "AnnotationTextAlignmentY",                                                                                                 name: "str-enum[AnnotationTextAlignmentY]",                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "AnnotationTextOptions",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055eb0333f4a0,                                                                         ),                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                         name: "AnnotationTextOptions",                                                                     },                                                                 ),                                                                 name: "nullable[AnnotationTextOptions]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[AnnotationTextOptions]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "AnnotationOptions",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb033100c0,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "AnnotationOptions",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b024e10,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b024bd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd797f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "new_annotation": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd797f0,                                                 ),                                             ],                                         },                                         expected_repr: "'new_annotation'",                                         name: "literal['new_annotation']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['new_annotation']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionNewAnnotation",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ab4950,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionNewAnnotation",     }, ), definitions=[StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb0349dff0), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"arrow": 1, "none": 0}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b361730), Py(0x7fa14b361c10)] }, missing: None, expected_repr: "'none' or 'arrow'", strict: false, class_repr: "AnnotationLineEnd", name: "str-enum[AnnotationLineEnd]" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, annotation_type: kittycad.models.annotation_type.AnnotationType, clobber: bool, options: kittycad.models.annotation_options.AnnotationOptions, type: Literal['new_annotation'] = 'new_annotation') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

annotation_type: AnnotationType

clobber: bool

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation_type': FieldInfo(annotation=AnnotationType, required=True), 'clobber': FieldInfo(annotation=bool, required=True), 'options': FieldInfo(annotation=AnnotationOptions, required=True), 'type': FieldInfo(annotation=Literal['new_annotation'], required=False, default='new_annotation')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

options: AnnotationOptions

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['new_annotation']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionObjectBringToFront(**data)

Bring an object to the front of the scene

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['object_bring_to_front']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionObjectBringToFront'>, 'config': {'title': 'OptionObjectBringToFront'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionObjectBringToFront'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionObjectBringToFront'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionObjectBringToFront:94467867362448', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'object_bring_to_front', 'schema': {'expected': ['object_bring_to_front'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionObjectBringToFront', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ad4490,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd79a70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "object_bring_to_front",                                             },                                             expected_py: None,                                             name: "literal['object_bring_to_front']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionObjectBringToFront",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionObjectBringToFront", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14aeff370,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14aefecb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b025fb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b026040,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd79a70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "object_bring_to_front": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd79a70,                                                 ),                                             ],                                         },                                         expected_repr: "'object_bring_to_front'",                                         name: "literal['object_bring_to_front']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['object_bring_to_front']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionObjectBringToFront",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ad4490,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionObjectBringToFront",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, object_id: str, type: Literal['object_bring_to_front'] = 'object_bring_to_front') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['object_bring_to_front'], required=False, default='object_bring_to_front')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['object_bring_to_front']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionObjectSetMaterialParamsPbr(**data)

Set the material properties of an object

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'ambient_occlusion': <class 'float'>, 'color': <class 'kittycad.models.color.Color'>, 'metalness': <class 'float'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'roughness': <class 'float'>, 'type': typing.Literal['object_set_material_params_pbr']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionObjectSetMaterialParamsPbr'>, 'config': {'title': 'OptionObjectSetMaterialParamsPbr'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionObjectSetMaterialParamsPbr'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionObjectSetMaterialParamsPbr'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionObjectSetMaterialParamsPbr:94467867373424', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'ambient_occlusion': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'color': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.color.Color'>, 'config': {'title': 'Color'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.color.Color'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.color.Color'>>]}, 'ref': 'kittycad.models.color.Color:94467859422064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'a': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'b': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'g': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'r': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Color', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'metalness': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'roughness': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'object_set_material_params_pbr', 'schema': {'expected': ['object_set_material_params_pbr'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionObjectSetMaterialParamsPbr', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ad6f70,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd29ac0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "object_set_material_params_pbr",                                             },                                             expected_py: None,                                             name: "literal['object_set_material_params_pbr']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "ambient_occlusion": SerField {                         key_py: Py(                             0x00007fa14affc430,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "metalness": SerField {                         key_py: Py(                             0x00007fa14affc470,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "color": SerField {                         key_py: Py(                             0x00007fa14ea1a040,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb03341b70,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "a": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3dcf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "b": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3dd20,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "g": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3de10,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "r": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e020,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 4,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Color",                                 },                             ),                         ),                         required: true,                     },                     "roughness": SerField {                         key_py: Py(                             0x00007fa14affc4f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 6,             },         ),         has_extra: false,         root_model: false,         name: "OptionObjectSetMaterialParamsPbr",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionObjectSetMaterialParamsPbr", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "ambient_occlusion",                         lookup_key: Simple {                             key: "ambient_occlusion",                             py_key: Py(                                 0x00007fa14af07730,                             ),                             path: LookupPath(                                 [                                     S(                                         "ambient_occlusion",                                         Py(                                             0x00007fa14af076f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14affc430,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "color",                         lookup_key: Simple {                             key: "color",                             py_key: Py(                                 0x00007fa14b0271e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "color",                                         Py(                                             0x00007fa14b027210,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ea1a040,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "a",                                                 lookup_key: Simple {                                                     key: "a",                                                     py_key: Py(                                                         0x00007fa14fa3dcf0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "a",                                                                 Py(                                                                     0x00007fa14fa3dcf0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3dcf0,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "b",                                                 lookup_key: Simple {                                                     key: "b",                                                     py_key: Py(                                                         0x00007fa14fa3dd20,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "b",                                                                 Py(                                                                     0x00007fa14fa3dd20,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3dd20,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "g",                                                 lookup_key: Simple {                                                     key: "g",                                                     py_key: Py(                                                         0x00007fa14fa3de10,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "g",                                                                 Py(                                                                     0x00007fa14fa3de10,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3de10,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "r",                                                 lookup_key: Simple {                                                     key: "r",                                                     py_key: Py(                                                         0x00007fa14fa3e020,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "r",                                                                 Py(                                                                     0x00007fa14fa3e020,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e020,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Color",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb03341b70,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Color",                             },                         ),                         frozen: false,                     },                     Field {                         name: "metalness",                         lookup_key: Simple {                             key: "metalness",                             py_key: Py(                                 0x00007fa14af077b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "metalness",                                         Py(                                             0x00007fa14af07770,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14affc470,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af077f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14af07830,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "roughness",                         lookup_key: Simple {                             key: "roughness",                             py_key: Py(                                 0x00007fa14af07870,                             ),                             path: LookupPath(                                 [                                     S(                                         "roughness",                                         Py(                                             0x00007fa14af078b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14affc4f0,                         ),                         validator: Float(                             FloatValidator {                                 strict: false,                                 allow_inf_nan: true,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b027240,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b027270,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd29ac0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "object_set_material_params_pbr": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd29ac0,                                                 ),                                             ],                                         },                                         expected_repr: "'object_set_material_params_pbr'",                                         name: "literal['object_set_material_params_pbr']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['object_set_material_params_pbr']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionObjectSetMaterialParamsPbr",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ad6f70,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionObjectSetMaterialParamsPbr",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, ambient_occlusion: float, color: kittycad.models.color.Color, metalness: float, object_id: str, roughness: float, type: Literal['object_set_material_params_pbr'] = 'object_set_material_params_pbr') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

ambient_occlusion: float

color: Color

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

metalness: float

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'ambient_occlusion': FieldInfo(annotation=float, required=True), 'color': FieldInfo(annotation=Color, required=True), 'metalness': FieldInfo(annotation=float, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'roughness': FieldInfo(annotation=float, required=True), 'type': FieldInfo(annotation=Literal['object_set_material_params_pbr'], required=False, default='object_set_material_params_pbr')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

roughness: float

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['object_set_material_params_pbr']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionObjectVisible(**data)

Hide or show an object

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'hidden': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['object_visible']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionObjectVisible'>, 'config': {'title': 'OptionObjectVisible'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionObjectVisible'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionObjectVisible'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionObjectVisible:94467866430624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'hidden': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'object_visible', 'schema': {'expected': ['object_visible'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionObjectVisible', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb039f0ca0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd79bb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "object_visible",                                             },                                             expected_py: None,                                             name: "literal['object_visible']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "hidden": SerField {                         key_py: Py(                             0x00007fa14e0bbea0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionObjectVisible",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionObjectVisible", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "hidden",                         lookup_key: Simple {                             key: "hidden",                             py_key: Py(                                 0x00007fa14b026e20,                             ),                             path: LookupPath(                                 [                                     S(                                         "hidden",                                         Py(                                             0x00007fa14b026e50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e0bbea0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af06ef0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14af06eb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b026e80,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b026eb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd79bb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "object_visible": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd79bb0,                                                 ),                                             ],                                         },                                         expected_repr: "'object_visible'",                                         name: "literal['object_visible']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['object_visible']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionObjectVisible",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb039f0ca0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionObjectVisible",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, hidden: bool, object_id: str, type: Literal['object_visible'] = 'object_visible') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

hidden: bool

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'hidden': FieldInfo(annotation=bool, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['object_visible'], required=False, default='object_visible')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['object_visible']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionPathGetCurveUuid(**data)

Obtain curve id by index

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'index': <class 'int'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path_id': <class 'str'>, 'type': typing.Literal['path_get_curve_uuid']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionPathGetCurveUuid'>, 'config': {'title': 'OptionPathGetCurveUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionPathGetCurveUuid'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionPathGetCurveUuid'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionPathGetCurveUuid:94467856150624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'index': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'path_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'path_get_curve_uuid', 'schema': {'expected': ['path_get_curve_uuid'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetCurveUuid', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03023060,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "index": SerField {                         key_py: Py(                             0x00007fa14f9faac0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Int(                                 IntSerializer,                             ),                         ),                         required: true,                     },                     "path_id": SerField {                         key_py: Py(                             0x00007fa14afd3120,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7a430,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_curve_uuid",                                             },                                             expected_py: None,                                             name: "literal['path_get_curve_uuid']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetCurveUuid",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetCurveUuid", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "index",                         lookup_key: Simple {                             key: "index",                             py_key: Py(                                 0x00007fa14ad57210,                             ),                             path: LookupPath(                                 [                                     S(                                         "index",                                         Py(                                             0x00007fa14ad57240,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14f9faac0,                         ),                         validator: Int(                             IntValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "path_id",                         lookup_key: Simple {                             key: "path_id",                             py_key: Py(                                 0x00007fa14ad57270,                             ),                             path: LookupPath(                                 [                                     S(                                         "path_id",                                         Py(                                             0x00007fa14ad572a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd3120,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad572d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad57300,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7a430,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_curve_uuid": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7a430,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_curve_uuid'",                                         name: "literal['path_get_curve_uuid']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_curve_uuid']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetCurveUuid",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03023060,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionPathGetCurveUuid",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, index: int, path_id: str, type: Literal['path_get_curve_uuid'] = 'path_get_curve_uuid') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

index: int

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'index': FieldInfo(annotation=int, required=True), 'path_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['path_get_curve_uuid'], required=False, default='path_get_curve_uuid')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path_id: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_curve_uuid']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionPathGetCurveUuidsForVertices(**data)

Obtain curve ids for vertex ids

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path_id': <class 'str'>, 'type': typing.Literal['path_get_curve_uuids_for_vertices'], 'vertex_ids': typing.List[str]}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionPathGetCurveUuidsForVertices'>, 'config': {'title': 'OptionPathGetCurveUuidsForVertices'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionPathGetCurveUuidsForVertices'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionPathGetCurveUuidsForVertices'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionPathGetCurveUuidsForVertices:94467867827808', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'path_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'path_get_curve_uuids_for_vertices', 'schema': {'expected': ['path_get_curve_uuids_for_vertices'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'vertex_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetCurveUuidsForVertices', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b45e60,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "vertex_ids": SerField {                         key_py: Py(                             0x00007fa14b01fc70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "path_id": SerField {                         key_py: Py(                             0x00007fa14afd3120,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd297f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_curve_uuids_for_vertices",                                             },                                             expected_py: None,                                             name: "literal['path_get_curve_uuids_for_vertices']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetCurveUuidsForVertices",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetCurveUuidsForVertices", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "path_id",                         lookup_key: Simple {                             key: "path_id",                             py_key: Py(                                 0x00007fa14ad55a10,                             ),                             path: LookupPath(                                 [                                     S(                                         "path_id",                                         Py(                                             0x00007fa14ad54510,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd3120,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad55c50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad55e00,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd297f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_curve_uuids_for_vertices": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd297f0,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_curve_uuids_for_vertices'",                                         name: "literal['path_get_curve_uuids_for_vertices']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_curve_uuids_for_vertices']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "vertex_ids",                         lookup_key: Simple {                             key: "vertex_ids",                             py_key: Py(                                 0x00007fa14adb8370,                             ),                             path: LookupPath(                                 [                                     S(                                         "vertex_ids",                                         Py(                                             0x00007fa14adb8270,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01fc70,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetCurveUuidsForVertices",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b45e60,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionPathGetCurveUuidsForVertices",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, path_id: str, type: Literal['path_get_curve_uuids_for_vertices'] = 'path_get_curve_uuids_for_vertices', vertex_ids: List[str]) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'path_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['path_get_curve_uuids_for_vertices'], required=False, default='path_get_curve_uuids_for_vertices'), 'vertex_ids': FieldInfo(annotation=List[str], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path_id: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_curve_uuids_for_vertices']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

vertex_ids: List[str]

class kittycad.models.modeling_cmd.OptionPathGetInfo(**data)

Query the given path.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path_id': <class 'str'>, 'type': typing.Literal['path_get_info']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionPathGetInfo'>, 'config': {'title': 'OptionPathGetInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionPathGetInfo'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionPathGetInfo'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionPathGetInfo:94467867818416', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'path_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'path_get_info', 'schema': {'expected': ['path_get_info'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetInfo', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b439b0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7a530,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_info",                                             },                                             expected_py: None,                                             name: "literal['path_get_info']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "path_id": SerField {                         key_py: Py(                             0x00007fa14afd3120,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetInfo",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetInfo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "path_id",                         lookup_key: Simple {                             key: "path_id",                             py_key: Py(                                 0x00007fa14ad56dc0,                             ),                             path: LookupPath(                                 [                                     S(                                         "path_id",                                         Py(                                             0x00007fa14ad56df0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd3120,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad56e20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad56e50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7a530,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_info": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7a530,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_info'",                                         name: "literal['path_get_info']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_info']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetInfo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b439b0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionPathGetInfo",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, path_id: str, type: Literal['path_get_info'] = 'path_get_info') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'path_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['path_get_info'], required=False, default='path_get_info')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path_id: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_info']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionPathGetSketchTargetUuid(**data)

Obtain the sketch target id (if the path was drawn in sketchmode) for a path

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path_id': <class 'str'>, 'type': typing.Literal['path_get_sketch_target_uuid']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionPathGetSketchTargetUuid'>, 'config': {'title': 'OptionPathGetSketchTargetUuid'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionPathGetSketchTargetUuid'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionPathGetSketchTargetUuid'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionPathGetSketchTargetUuid:94467867853312', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'path_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'path_get_sketch_target_uuid', 'schema': {'expected': ['path_get_sketch_target_uuid'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetSketchTargetUuid', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b4c200,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2add0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_sketch_target_uuid",                                             },                                             expected_py: None,                                             name: "literal['path_get_sketch_target_uuid']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "path_id": SerField {                         key_py: Py(                             0x00007fa14afd3120,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetSketchTargetUuid",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetSketchTargetUuid", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "path_id",                         lookup_key: Simple {                             key: "path_id",                             py_key: Py(                                 0x00007fa14ad57db0,                             ),                             path: LookupPath(                                 [                                     S(                                         "path_id",                                         Py(                                             0x00007fa14ad57de0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd3120,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad57e10,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad57e40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2add0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_sketch_target_uuid": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2add0,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_sketch_target_uuid'",                                         name: "literal['path_get_sketch_target_uuid']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_sketch_target_uuid']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetSketchTargetUuid",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b4c200,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionPathGetSketchTargetUuid",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, path_id: str, type: Literal['path_get_sketch_target_uuid'] = 'path_get_sketch_target_uuid') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'path_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['path_get_sketch_target_uuid'], required=False, default='path_get_sketch_target_uuid')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path_id: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_sketch_target_uuid']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionPathGetVertexUuids(**data)

Obtain vertex ids for a path

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'path_id': <class 'str'>, 'type': typing.Literal['path_get_vertex_uuids']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionPathGetVertexUuids'>, 'config': {'title': 'OptionPathGetVertexUuids'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionPathGetVertexUuids'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionPathGetVertexUuids'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionPathGetVertexUuids:94467867835536', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'path_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'path_get_vertex_uuids', 'schema': {'expected': ['path_get_vertex_uuids'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPathGetVertexUuids', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b47c90,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7a6b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "path_get_vertex_uuids",                                             },                                             expected_py: None,                                             name: "literal['path_get_vertex_uuids']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "path_id": SerField {                         key_py: Py(                             0x00007fa14afd3120,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionPathGetVertexUuids",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPathGetVertexUuids", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "path_id",                         lookup_key: Simple {                             key: "path_id",                             py_key: Py(                                 0x00007fa14ad57810,                             ),                             path: LookupPath(                                 [                                     S(                                         "path_id",                                         Py(                                             0x00007fa14ad57840,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd3120,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad57870,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad578a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7a6b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "path_get_vertex_uuids": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7a6b0,                                                 ),                                             ],                                         },                                         expected_repr: "'path_get_vertex_uuids'",                                         name: "literal['path_get_vertex_uuids']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['path_get_vertex_uuids']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPathGetVertexUuids",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b47c90,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionPathGetVertexUuids",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, path_id: str, type: Literal['path_get_vertex_uuids'] = 'path_get_vertex_uuids') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'path_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['path_get_vertex_uuids'], required=False, default='path_get_vertex_uuids')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

path_id: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['path_get_vertex_uuids']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionPlaneIntersectAndProject(**data)

Utility method. Performs both a ray cast and projection to plane-local coordinates. Returns the plane coordinates for the given window coordinates.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'plane_id': <class 'str'>, 'type': typing.Literal['plane_intersect_and_project'], 'window': <class 'kittycad.models.point2d.Point2d'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionPlaneIntersectAndProject'>, 'config': {'title': 'OptionPlaneIntersectAndProject'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionPlaneIntersectAndProject'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionPlaneIntersectAndProject'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionPlaneIntersectAndProject:94467867914096', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'plane_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'plane_intersect_and_project', 'schema': {'expected': ['plane_intersect_and_project'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}}, 'model_name': 'OptionPlaneIntersectAndProject', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b5af70,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "window": SerField {                         key_py: Py(                             0x00007fa14e1645a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                     "plane_id": SerField {                         key_py: Py(                             0x00007fa14b01dfb0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2af10,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "plane_intersect_and_project",                                             },                                             expected_py: None,                                             name: "literal['plane_intersect_and_project']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionPlaneIntersectAndProject",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPlaneIntersectAndProject", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "plane_id",                         lookup_key: Simple {                             key: "plane_id",                             py_key: Py(                                 0x00007fa14add04b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "plane_id",                                         Py(                                             0x00007fa14add0470,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01dfb0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc4ab0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc4ae0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2af10,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "plane_intersect_and_project": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2af10,                                                 ),                                             ],                                         },                                         expected_repr: "'plane_intersect_and_project'",                                         name: "literal['plane_intersect_and_project']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['plane_intersect_and_project']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "window",                         lookup_key: Simple {                             key: "window",                             py_key: Py(                                 0x00007fa14adc4b10,                             ),                             path: LookupPath(                                 [                                     S(                                         "window",                                         Py(                                             0x00007fa14adc4b40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e1645a0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14add0340,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14add0340,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPlaneIntersectAndProject",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b5af70,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionPlaneIntersectAndProject",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, plane_id: str, type: Literal['plane_intersect_and_project'] = 'plane_intersect_and_project', window: kittycad.models.point2d.Point2d) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'plane_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['plane_intersect_and_project'], required=False, default='plane_intersect_and_project'), 'window': FieldInfo(annotation=Point2d, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

plane_id: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['plane_intersect_and_project']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

window: Point2d

class kittycad.models.modeling_cmd.OptionPlaneSetColor(**data)

Set the color of a plane.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'color': <class 'kittycad.models.color.Color'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'plane_id': <class 'str'>, 'type': typing.Literal['plane_set_color']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionPlaneSetColor'>, 'config': {'title': 'OptionPlaneSetColor'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionPlaneSetColor'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionPlaneSetColor'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionPlaneSetColor:94467867603808', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'color': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.color.Color'>, 'config': {'title': 'Color'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.color.Color'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.color.Color'>>]}, 'ref': 'kittycad.models.color.Color:94467859422064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'a': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'b': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'g': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'r': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Color', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'plane_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'plane_set_color', 'schema': {'expected': ['plane_set_color'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionPlaneSetColor', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b0f360,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "plane_id": SerField {                         key_py: Py(                             0x00007fa14b01dfb0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7acf0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "plane_set_color",                                             },                                             expected_py: None,                                             name: "literal['plane_set_color']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "color": SerField {                         key_py: Py(                             0x00007fa14ea1a040,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb03341b70,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "r": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e020,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "b": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3dd20,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "g": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3de10,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "a": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3dcf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 4,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Color",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionPlaneSetColor",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionPlaneSetColor", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "color",                         lookup_key: Simple {                             key: "color",                             py_key: Py(                                 0x00007fa14ad541b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "color",                                         Py(                                             0x00007fa14ad541e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ea1a040,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "a",                                                 lookup_key: Simple {                                                     key: "a",                                                     py_key: Py(                                                         0x00007fa14fa3dcf0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "a",                                                                 Py(                                                                     0x00007fa14fa3dcf0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3dcf0,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "b",                                                 lookup_key: Simple {                                                     key: "b",                                                     py_key: Py(                                                         0x00007fa14fa3dd20,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "b",                                                                 Py(                                                                     0x00007fa14fa3dd20,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3dd20,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "g",                                                 lookup_key: Simple {                                                     key: "g",                                                     py_key: Py(                                                         0x00007fa14fa3de10,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "g",                                                                 Py(                                                                     0x00007fa14fa3de10,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3de10,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "r",                                                 lookup_key: Simple {                                                     key: "r",                                                     py_key: Py(                                                         0x00007fa14fa3e020,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "r",                                                                 Py(                                                                     0x00007fa14fa3e020,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e020,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Color",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb03341b70,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Color",                             },                         ),                         frozen: false,                     },                     Field {                         name: "plane_id",                         lookup_key: Simple {                             key: "plane_id",                             py_key: Py(                                 0x00007fa14ad527b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "plane_id",                                         Py(                                             0x00007fa14ad52770,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01dfb0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad54210,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad54240,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7acf0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "plane_set_color": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7acf0,                                                 ),                                             ],                                         },                                         expected_repr: "'plane_set_color'",                                         name: "literal['plane_set_color']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['plane_set_color']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionPlaneSetColor",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b0f360,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionPlaneSetColor",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, color: kittycad.models.color.Color, plane_id: str, type: Literal['plane_set_color'] = 'plane_set_color') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

color: Color

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'color': FieldInfo(annotation=Color, required=True), 'plane_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['plane_set_color'], required=False, default='plane_set_color')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

plane_id: str

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['plane_set_color']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionReconfigureStream(**data)

Reconfigure the stream.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'bitrate': typing.Optional[int], 'fps': <class 'int'>, 'height': <class 'int'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['reconfigure_stream'], 'width': <class 'int'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionReconfigureStream'>, 'config': {'title': 'OptionReconfigureStream'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionReconfigureStream'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionReconfigureStream'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionReconfigureStream:94467867937760', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'bitrate': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'int'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'fps': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'height': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'reconfigure_stream', 'schema': {'expected': ['reconfigure_stream'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'width': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}}, 'model_name': 'OptionReconfigureStream', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b60be0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "bitrate": SerField {                         key_py: Py(                             0x00007fa14b0252f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Int(                                                 IntSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7afb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "reconfigure_stream",                                             },                                             expected_py: None,                                             name: "literal['reconfigure_stream']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "fps": SerField {                         key_py: Py(                             0x00007fa14b0253e0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Int(                                 IntSerializer,                             ),                         ),                         required: true,                     },                     "height": SerField {                         key_py: Py(                             0x00007fa14e3a6a30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Int(                                 IntSerializer,                             ),                         ),                         required: true,                     },                     "width": SerField {                         key_py: Py(                             0x00007fa14ef0b1b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Int(                                 IntSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 5,             },         ),         has_extra: false,         root_model: false,         name: "OptionReconfigureStream",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionReconfigureStream", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "bitrate",                         lookup_key: Simple {                             key: "bitrate",                             py_key: Py(                                 0x00007fa14adc56e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "bitrate",                                         Py(                                             0x00007fa14adc5710,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0252f0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Int(                                             IntValidator {                                                 strict: false,                                             },                                         ),                                         name: "nullable[int]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[int]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "fps",                         lookup_key: Simple {                             key: "fps",                             py_key: Py(                                 0x00007fa14adc5740,                             ),                             path: LookupPath(                                 [                                     S(                                         "fps",                                         Py(                                             0x00007fa14adc5770,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0253e0,                         ),                         validator: Int(                             IntValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "height",                         lookup_key: Simple {                             key: "height",                             py_key: Py(                                 0x00007fa14adc57a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "height",                                         Py(                                             0x00007fa14adc57d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e3a6a30,                         ),                         validator: Int(                             IntValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc5800,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc5830,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7afb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "reconfigure_stream": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7afb0,                                                 ),                                             ],                                         },                                         expected_repr: "'reconfigure_stream'",                                         name: "literal['reconfigure_stream']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['reconfigure_stream']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "width",                         lookup_key: Simple {                             key: "width",                             py_key: Py(                                 0x00007fa14adc5860,                             ),                             path: LookupPath(                                 [                                     S(                                         "width",                                         Py(                                             0x00007fa14adc5890,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ef0b1b0,                         ),                         validator: Int(                             IntValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionReconfigureStream",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b60be0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionReconfigureStream",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, bitrate: Optional[int] = None, fps: int, height: int, type: Literal['reconfigure_stream'] = 'reconfigure_stream', width: int) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

bitrate: Optional[int]

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

fps: int

classmethod from_orm(obj)

Return type:

Self

height: int

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'bitrate': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'fps': FieldInfo(annotation=int, required=True), 'height': FieldInfo(annotation=int, required=True), 'type': FieldInfo(annotation=Literal['reconfigure_stream'], required=False, default='reconfigure_stream'), 'width': FieldInfo(annotation=int, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['reconfigure_stream']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

width: int

class kittycad.models.modeling_cmd.OptionRemoveSceneObjects(**data)

Remove scene objects.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_ids': typing.List[str], 'type': typing.Literal['remove_scene_objects']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionRemoveSceneObjects'>, 'config': {'title': 'OptionRemoveSceneObjects'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionRemoveSceneObjects'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionRemoveSceneObjects'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionRemoveSceneObjects:94467867900416', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'object_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'remove_scene_objects', 'schema': {'expected': ['remove_scene_objects'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionRemoveSceneObjects', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b57a00,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_ids": SerField {                         key_py: Py(                             0x00007fa14ae2c770,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7b0b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "remove_scene_objects",                                             },                                             expected_py: None,                                             name: "literal['remove_scene_objects']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionRemoveSceneObjects",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionRemoveSceneObjects", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "object_ids",                         lookup_key: Simple {                             key: "object_ids",                             py_key: Py(                                 0x00007fa14adcaaf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_ids",                                         Py(                                             0x00007fa14adcaab0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ae2c770,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc4750,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc4690,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7b0b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "remove_scene_objects": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7b0b0,                                                 ),                                             ],                                         },                                         expected_repr: "'remove_scene_objects'",                                         name: "literal['remove_scene_objects']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['remove_scene_objects']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionRemoveSceneObjects",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b57a00,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionRemoveSceneObjects",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, object_ids: List[str], type: Literal['remove_scene_objects'] = 'remove_scene_objects') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'object_ids': FieldInfo(annotation=List[str], required=True), 'type': FieldInfo(annotation=Literal['remove_scene_objects'], required=False, default='remove_scene_objects')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_ids: List[str]

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['remove_scene_objects']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionRevolve(**data)

Command for revolving a solid 2d.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'angle': <class 'kittycad.models.angle.Angle'>, 'axis': <class 'kittycad.models.point3d.Point3d'>, 'axis_is_2d': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'origin': <class 'kittycad.models.point3d.Point3d'>, 'target': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'tolerance': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['revolve']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionRevolve'>, 'config': {'title': 'OptionRevolve'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionRevolve'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionRevolve'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionRevolve:94467866550528', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'angle': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.angle.Angle'>, 'config': {'title': 'Angle'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.angle.Angle'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.angle.Angle'>>]}, 'ref': 'kittycad.models.angle.Angle:94467862185984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitAngle'>, 'members': [UnitAngle.DEGREES, UnitAngle.RADIANS], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_angle.UnitAngle:94467859501968', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'value': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Angle', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'axis': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'axis_is_2d': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'origin': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94467859212112', 'type': 'definition-ref'}, 'type': 'model-field'}, 'target': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'type': 'no-info'}, 'schema': {'type': 'str'}, 'type': 'function-after'}, 'type': 'model-field'}, 'tolerance': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'revolve', 'schema': {'expected': ['revolve'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionRevolve', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a0e100,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "tolerance": SerField {                         key_py: Py(                             0x00007fa14afd8570,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14c398f00,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "revolve",                                             },                                             expected_py: None,                                             name: "literal['revolve']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "target": SerField {                         key_py: Py(                             0x00007fa14fa3c088,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "origin": SerField {                         key_py: Py(                             0x00007fa14fa3aa98,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "angle": SerField {                         key_py: Py(                             0x00007fa14d9ed140,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb035e4800,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "unit": SerField {                                                     key_py: Py(                                                         0x00007fa14e161380,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055eb03355390,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "value": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3c768,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Angle",                                 },                             ),                         ),                         required: true,                     },                     "axis": SerField {                         key_py: Py(                             0x00007fa14c13dce0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "axis_is_2d": SerField {                         key_py: Py(                             0x00007fa14afd84f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 7,             },         ),         has_extra: false,         root_model: false,         name: "OptionRevolve",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55eb0330e750), serializer: Fields(GeneralFieldsSerializer { fields: {"x": SerField { key_py: Py(0x7fa14fa3e140), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7fa14fa3e170), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7fa14fa3e1a0), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }}, computed_fields: Some(ComputedFields([])), mode: SimpleDict, extra_serializer: None, filter: SchemaFilter { include: None, exclude: None }, required_fields: 3 }), has_extra: false, root_model: false, name: "Point3d" })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionRevolve", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "angle",                         lookup_key: Simple {                             key: "angle",                             py_key: Py(                                 0x00007fa14afe62b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "angle",                                         Py(                                             0x00007fa14afe62e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d9ed140,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "unit",                                                 lookup_key: Simple {                                                     key: "unit",                                                     py_key: Py(                                                         0x00007fa14afe61f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "unit",                                                                 Py(                                                                     0x00007fa14afe6220,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14e161380,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055eb03355390,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "degrees": 0,                                                                     "radians": 1,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             values: [                                                                 Py(                                                                     0x00007fa14b361850,                                                                 ),                                                                 Py(                                                                     0x00007fa14b3618b0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'degrees' or 'radians'",                                                         strict: false,                                                         class_repr: "UnitAngle",                                                         name: "str-enum[UnitAngle]",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "value",                                                 lookup_key: Simple {                                                     key: "value",                                                     py_key: Py(                                                         0x00007fa14afe6250,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "value",                                                                 Py(                                                                     0x00007fa14afe6280,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3c768,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Angle",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb035e4800,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Angle",                             },                         ),                         frozen: false,                     },                     Field {                         name: "axis",                         lookup_key: Simple {                             key: "axis",                             py_key: Py(                                 0x00007fa14afe6310,                             ),                             path: LookupPath(                                 [                                     S(                                         "axis",                                         Py(                                             0x00007fa14afe6340,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14c13dce0,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "axis_is_2d",                         lookup_key: Simple {                             key: "axis_is_2d",                             py_key: Py(                                 0x00007fa14ae43f70,                             ),                             path: LookupPath(                                 [                                     S(                                         "axis_is_2d",                                         Py(                                             0x00007fa14ae43fb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd84f0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "origin",                         lookup_key: Simple {                             key: "origin",                             py_key: Py(                                 0x00007fa14afe6370,                             ),                             path: LookupPath(                                 [                                     S(                                         "origin",                                         Py(                                             0x00007fa14afe63a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3aa98,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "target",                         lookup_key: Simple {                             key: "target",                             py_key: Py(                                 0x00007fa14afe63d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "target",                                         Py(                                             0x00007fa14afe6400,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c088,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Str(                                     StrValidator {                                         strict: false,                                         coerce_numbers_to_str: false,                                     },                                 ),                                 func: Py(                                     0x000055eb039991a0,                                 ),                                 config: Py(                                     0x00007fa14ae71100,                                 ),                                 name: "function-after[ModelingCmdId(), str]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "tolerance",                         lookup_key: Simple {                             key: "tolerance",                             py_key: Py(                                 0x00007fa14ae410b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "tolerance",                                         Py(                                             0x00007fa14ae410f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd8570,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14ae71100,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe6430,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe6460,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14c398f00,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "revolve": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14c398f00,                                                 ),                                             ],                                         },                                         expected_repr: "'revolve'",                                         name: "literal['revolve']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['revolve']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionRevolve",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a0e100,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionRevolve",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fa14fa3e140), path: LookupPath([S("x", Py(0x7fa14fa3e140))]) }, name_py: Py(0x7fa14fa3e140), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fa14fa3e170), path: LookupPath([S("y", Py(0x7fa14fa3e170))]) }, name_py: Py(0x7fa14fa3e170), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fa14fa3e1a0), path: LookupPath([S("z", Py(0x7fa14fa3e1a0))]) }, name_py: Py(0x7fa14fa3e1a0), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }], model_name: "Point3d", extra_behavior: Ignore, extras_validator: None, strict: false, from_attributes: false, loc_by_alias: true }), class: Py(0x55eb0330e750), post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fa14d802350), name: "Point3d" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, angle: kittycad.models.angle.Angle, axis: kittycad.models.point3d.Point3d, axis_is_2d: bool, origin: kittycad.models.point3d.Point3d, target: kittycad.models.modeling_cmd_id.ModelingCmdId, tolerance: kittycad.models.length_unit.LengthUnit, type: Literal['revolve'] = 'revolve') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

angle: Angle

axis: Point3d

axis_is_2d: bool

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'angle': FieldInfo(annotation=Angle, required=True), 'axis': FieldInfo(annotation=Point3d, required=True), 'axis_is_2d': FieldInfo(annotation=bool, required=True), 'origin': FieldInfo(annotation=Point3d, required=True), 'target': FieldInfo(annotation=ModelingCmdId, required=True), 'tolerance': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['revolve'], required=False, default='revolve')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

origin: Point3d

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

target: ModelingCmdId

tolerance: LengthUnit

type: Literal['revolve']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionRevolveAboutEdge(**data)

Command for revolving a solid 2d about a brep edge

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'angle': <class 'kittycad.models.angle.Angle'>, 'edge_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'target': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'tolerance': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['revolve_about_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionRevolveAboutEdge'>, 'config': {'title': 'OptionRevolveAboutEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionRevolveAboutEdge'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionRevolveAboutEdge'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionRevolveAboutEdge:94467866586800', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'angle': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.angle.Angle'>, 'config': {'title': 'Angle'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.angle.Angle'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.angle.Angle'>>]}, 'ref': 'kittycad.models.angle.Angle:94467862185984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitAngle'>, 'members': [UnitAngle.DEGREES, UnitAngle.RADIANS], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_angle.UnitAngle:94467859501968', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'value': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Angle', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'target': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.modeling_cmd_id.ModelingCmdId'>, 'type': 'no-info'}, 'schema': {'type': 'str'}, 'type': 'function-after'}, 'type': 'model-field'}, 'tolerance': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'revolve_about_edge', 'schema': {'expected': ['revolve_about_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionRevolveAboutEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a16eb0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "target": SerField {                         key_py: Py(                             0x00007fa14fa3c088,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "angle": SerField {                         key_py: Py(                             0x00007fa14d9ed140,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb035e4800,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "unit": SerField {                                                     key_py: Py(                                                         0x00007fa14e161380,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055eb03355390,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "value": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3c768,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Angle",                                 },                             ),                         ),                         required: true,                     },                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7b1b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "revolve_about_edge",                                             },                                             expected_py: None,                                             name: "literal['revolve_about_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "tolerance": SerField {                         key_py: Py(                             0x00007fa14afd8570,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 5,             },         ),         has_extra: false,         root_model: false,         name: "OptionRevolveAboutEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionRevolveAboutEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "angle",                         lookup_key: Simple {                             key: "angle",                             py_key: Py(                                 0x00007fa14afe7180,                             ),                             path: LookupPath(                                 [                                     S(                                         "angle",                                         Py(                                             0x00007fa14afe6ca0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d9ed140,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "unit",                                                 lookup_key: Simple {                                                     key: "unit",                                                     py_key: Py(                                                         0x00007fa14afe7150,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "unit",                                                                 Py(                                                                     0x00007fa14afe6ee0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14e161380,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055eb03355390,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "degrees": 0,                                                                     "radians": 1,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             values: [                                                                 Py(                                                                     0x00007fa14b361850,                                                                 ),                                                                 Py(                                                                     0x00007fa14b3618b0,                                                                 ),                                                             ],                                                         },                                                         missing: None,                                                         expected_repr: "'degrees' or 'radians'",                                                         strict: false,                                                         class_repr: "UnitAngle",                                                         name: "str-enum[UnitAngle]",                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "value",                                                 lookup_key: Simple {                                                     key: "value",                                                     py_key: Py(                                                         0x00007fa14afe6f10,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "value",                                                                 Py(                                                                     0x00007fa14afe6e50,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3c768,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Angle",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb035e4800,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Angle",                             },                         ),                         frozen: false,                     },                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14afe6d00,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14afe6cd0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "target",                         lookup_key: Simple {                             key: "target",                             py_key: Py(                                 0x00007fa14afe6e80,                             ),                             path: LookupPath(                                 [                                     S(                                         "target",                                         Py(                                             0x00007fa14afe6df0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c088,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Str(                                     StrValidator {                                         strict: false,                                         coerce_numbers_to_str: false,                                     },                                 ),                                 func: Py(                                     0x000055eb039991a0,                                 ),                                 config: Py(                                     0x00007fa14ae39900,                                 ),                                 name: "function-after[ModelingCmdId(), str]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "tolerance",                         lookup_key: Simple {                             key: "tolerance",                             py_key: Py(                                 0x00007fa14b100870,                             ),                             path: LookupPath(                                 [                                     S(                                         "tolerance",                                         Py(                                             0x00007fa14af733b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd8570,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14ae39900,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe6d90,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe6d60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7b1b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "revolve_about_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7b1b0,                                                 ),                                             ],                                         },                                         expected_repr: "'revolve_about_edge'",                                         name: "literal['revolve_about_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['revolve_about_edge']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionRevolveAboutEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a16eb0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionRevolveAboutEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, angle: kittycad.models.angle.Angle, edge_id: str, target: kittycad.models.modeling_cmd_id.ModelingCmdId, tolerance: kittycad.models.length_unit.LengthUnit, type: Literal['revolve_about_edge'] = 'revolve_about_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

angle: Angle

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'angle': FieldInfo(annotation=Angle, required=True), 'edge_id': FieldInfo(annotation=str, required=True), 'target': FieldInfo(annotation=ModelingCmdId, required=True), 'tolerance': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['revolve_about_edge'], required=False, default='revolve_about_edge')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

target: ModelingCmdId

tolerance: LengthUnit

type: Literal['revolve_about_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSceneClearAll(**data)

Removes all of the Objects in the scene

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['scene_clear_all']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSceneClearAll'>, 'config': {'title': 'OptionSceneClearAll'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSceneClearAll'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSceneClearAll'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSceneClearAll:94467867190112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'scene_clear_all', 'schema': {'expected': ['scene_clear_all'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSceneClearAll', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03aaa360,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7b6b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "scene_clear_all",                                             },                                             expected_py: None,                                             name: "literal['scene_clear_all']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionSceneClearAll",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSceneClearAll", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b0253b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b025410,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7b6b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "scene_clear_all": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7b6b0,                                                 ),                                             ],                                         },                                         expected_repr: "'scene_clear_all'",                                         name: "literal['scene_clear_all']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['scene_clear_all']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSceneClearAll",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03aaa360,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSceneClearAll",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['scene_clear_all'] = 'scene_clear_all') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['scene_clear_all'], required=False, default='scene_clear_all')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['scene_clear_all']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSelectAdd(**data)

Adds one or more entities (by UUID) to the selection.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entities': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['select_add']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSelectAdd'>, 'config': {'title': 'OptionSelectAdd'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSelectAdd'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSelectAdd'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSelectAdd:94467867091728', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entities': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'select_add', 'schema': {'expected': ['select_add'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectAdd', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a92310,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entities": SerField {                         key_py: Py(                             0x00007fa14d502070,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7b8b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_add",                                             },                                             expected_py: None,                                             name: "literal['select_add']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectAdd",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectAdd", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entities",                         lookup_key: Simple {                             key: "entities",                             py_key: Py(                                 0x00007fa14aec6f30,                             ),                             path: LookupPath(                                 [                                     S(                                         "entities",                                         Py(                                             0x00007fa14aec6ef0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d502070,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b024900,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b024930,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7b8b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_add": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7b8b0,                                                 ),                                             ],                                         },                                         expected_repr: "'select_add'",                                         name: "literal['select_add']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_add']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectAdd",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a92310,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSelectAdd",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entities: List[str], type: Literal['select_add'] = 'select_add') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entities: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entities': FieldInfo(annotation=List[str], required=True), 'type': FieldInfo(annotation=Literal['select_add'], required=False, default='select_add')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_add']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSelectClear(**data)

Clear the selection

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['select_clear']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSelectClear'>, 'config': {'title': 'OptionSelectClear'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSelectClear'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSelectClear'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSelectClear:94467868262544', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'select_clear', 'schema': {'expected': ['select_clear'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectClear', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03bb0090,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7b930,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_clear",                                             },                                             expected_py: None,                                             name: "literal['select_clear']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectClear",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectClear", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae01920,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae01950,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7b930,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_clear": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7b930,                                                 ),                                             ],                                         },                                         expected_repr: "'select_clear'",                                         name: "literal['select_clear']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_clear']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectClear",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03bb0090,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSelectClear",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['select_clear'] = 'select_clear') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['select_clear'], required=False, default='select_clear')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_clear']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSelectGet(**data)

Find all IDs of selected entities

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['select_get']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSelectGet'>, 'config': {'title': 'OptionSelectGet'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSelectGet'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSelectGet'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSelectGet:94467868271984', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'select_get', 'schema': {'expected': ['select_get'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectGet', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03bb2570,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7b9b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_get",                                             },                                             expected_py: None,                                             name: "literal['select_get']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectGet",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectGet", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae01e00,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae01e30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7b9b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_get": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7b9b0,                                                 ),                                             ],                                         },                                         expected_repr: "'select_get'",                                         name: "literal['select_get']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_get']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectGet",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03bb2570,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSelectGet",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['select_get'] = 'select_get') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['select_get'], required=False, default='select_get')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_get']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSelectRemove(**data)

Removes one or more entities (by UUID) from the selection.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entities': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['select_remove']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSelectRemove'>, 'config': {'title': 'OptionSelectRemove'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSelectRemove'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSelectRemove'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSelectRemove:94467867181088', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entities': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'select_remove', 'schema': {'expected': ['select_remove'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectRemove', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03aa8020,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entities": SerField {                         key_py: Py(                             0x00007fa14d502070,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7ba30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_remove",                                             },                                             expected_py: None,                                             name: "literal['select_remove']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectRemove",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectRemove", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entities",                         lookup_key: Simple {                             key: "entities",                             py_key: Py(                                 0x00007fa14aee41f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entities",                                         Py(                                             0x00007fa14aee41b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d502070,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b024e70,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b024ea0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7ba30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_remove": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7ba30,                                                 ),                                             ],                                         },                                         expected_repr: "'select_remove'",                                         name: "literal['select_remove']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_remove']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectRemove",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03aa8020,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSelectRemove",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entities: List[str], type: Literal['select_remove'] = 'select_remove') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entities: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entities': FieldInfo(annotation=List[str], required=True), 'type': FieldInfo(annotation=Literal['select_remove'], required=False, default='select_remove')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_remove']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSelectReplace(**data)

Replaces current selection with these entities (by UUID).

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entities': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['select_replace']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSelectReplace'>, 'config': {'title': 'OptionSelectReplace'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSelectReplace'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSelectReplace'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSelectReplace:94467867199344', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entities': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'select_replace', 'schema': {'expected': ['select_replace'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectReplace', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03aac770,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7bab0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_replace",                                             },                                             expected_py: None,                                             name: "literal['select_replace']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entities": SerField {                         key_py: Py(                             0x00007fa14d502070,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectReplace",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectReplace", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entities",                         lookup_key: Simple {                             key: "entities",                             py_key: Py(                                 0x00007fa14aee63b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entities",                                         Py(                                             0x00007fa14aee6370,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d502070,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b025950,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b025980,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7bab0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_replace": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7bab0,                                                 ),                                             ],                                         },                                         expected_repr: "'select_replace'",                                         name: "literal['select_replace']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_replace']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectReplace",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03aac770,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSelectReplace",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entities: List[str], type: Literal['select_replace'] = 'select_replace') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entities: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entities': FieldInfo(annotation=List[str], required=True), 'type': FieldInfo(annotation=Literal['select_replace'], required=False, default='select_replace')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['select_replace']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSelectWithPoint(**data)

Modifies the selection by simulating a “mouse click” at the given x,y window coordinate Returns ID of whatever was selected.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'selected_at_window': <class 'kittycad.models.point2d.Point2d'>, 'selection_type': <enum 'SceneSelectionType'>, 'type': typing.Literal['select_with_point']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSelectWithPoint'>, 'config': {'title': 'OptionSelectWithPoint'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSelectWithPoint'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSelectWithPoint'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSelectWithPoint:94467867081696', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'selected_at_window': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point2d.Point2d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94467866083888', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}}, 'model_name': 'Point2d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'selection_type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'SceneSelectionType'>, 'members': [SceneSelectionType.REPLACE, SceneSelectionType.ADD, SceneSelectionType.REMOVE], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.scene_selection_type.SceneSelectionType:94467866263200', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'select_with_point', 'schema': {'expected': ['select_with_point'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSelectWithPoint', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a8fbe0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "selection_type": SerField {                         key_py: Py(                             0x00007fa14aff6e30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb039c7ea0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "selected_at_window": SerField {                         key_py: Py(                             0x00007fa14aff6df0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb0399c230,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 2,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Point2d",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7bb70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "select_with_point",                                             },                                             expected_py: None,                                             name: "literal['select_with_point']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionSelectWithPoint",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSelectWithPoint", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "selected_at_window",                         lookup_key: Simple {                             key: "selected_at_window",                             py_key: Py(                                 0x00007fa14aeb9030,                             ),                             path: LookupPath(                                 [                                     S(                                         "selected_at_window",                                         Py(                                             0x00007fa14aebac70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6df0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fa14fa3e140,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e140,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14aeb9f40,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fa14fa3e170,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e170,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055eb03768720,                                                         ),                                                         config: Py(                                                             0x00007fa14aeb9f40,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Point2d",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb0399c230,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "selection_type",                         lookup_key: Simple {                             key: "selection_type",                             py_key: Py(                                 0x00007fa14aebad70,                             ),                             path: LookupPath(                                 [                                     S(                                         "selection_type",                                         Py(                                             0x00007fa14aebaeb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6e30,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb039c7ea0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "replace": 0,                                             "add": 1,                                             "remove": 2,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14afec7d0,                                         ),                                         Py(                                             0x00007fa14afec890,                                         ),                                         Py(                                             0x00007fa14afec8f0,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'replace', 'add' or 'remove'",                                 strict: false,                                 class_repr: "SceneSelectionType",                                 name: "str-enum[SceneSelectionType]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe57d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe5ce0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7bb70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "select_with_point": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7bb70,                                                 ),                                             ],                                         },                                         expected_repr: "'select_with_point'",                                         name: "literal['select_with_point']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['select_with_point']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSelectWithPoint",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a8fbe0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSelectWithPoint",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, selected_at_window: kittycad.models.point2d.Point2d, selection_type: kittycad.models.scene_selection_type.SceneSelectionType, type: Literal['select_with_point'] = 'select_with_point') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'selected_at_window': FieldInfo(annotation=Point2d, required=True), 'selection_type': FieldInfo(annotation=SceneSelectionType, required=True), 'type': FieldInfo(annotation=Literal['select_with_point'], required=False, default='select_with_point')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

selected_at_window: Point2d

selection_type: SceneSelectionType

type: Literal['select_with_point']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSendObject(**data)

Send object to front or back.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'front': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['send_object']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSendObject'>, 'config': {'title': 'OptionSendObject'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSendObject'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSendObject'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSendObject:94467867558720', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'front': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'send_object', 'schema': {'expected': ['send_object'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSendObject', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b04340,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "front": SerField {                         key_py: Py(                             0x00007fa14b0215f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7bc70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "send_object",                                             },                                             expected_py: None,                                             name: "literal['send_object']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionSendObject",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSendObject", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "front",                         lookup_key: Simple {                             key: "front",                             py_key: Py(                                 0x00007fa14ae77360,                             ),                             path: LookupPath(                                 [                                     S(                                         "front",                                         Py(                                             0x00007fa14ae77390,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b0215f0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ad49130,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ad490f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae773c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae773f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7bc70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "send_object": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7bc70,                                                 ),                                             ],                                         },                                         expected_repr: "'send_object'",                                         name: "literal['send_object']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['send_object']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSendObject",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b04340,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSendObject",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, front: bool, object_id: str, type: Literal['send_object'] = 'send_object') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

front: bool

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'front': FieldInfo(annotation=bool, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['send_object'], required=False, default='send_object')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['send_object']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSetBackgroundColor(**data)

Set the background color of the scene.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'color': <class 'kittycad.models.color.Color'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['set_background_color']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSetBackgroundColor'>, 'config': {'title': 'OptionSetBackgroundColor'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSetBackgroundColor'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSetBackgroundColor'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSetBackgroundColor:94467867736144', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'color': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.color.Color'>, 'config': {'title': 'Color'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.color.Color'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.color.Color'>>]}, 'ref': 'kittycad.models.color.Color:94467859422064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'a': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'b': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'g': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'r': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Color', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'set_background_color', 'schema': {'expected': ['set_background_color'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetBackgroundColor', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b2f850,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7bfb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_background_color",                                             },                                             expected_py: None,                                             name: "literal['set_background_color']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "color": SerField {                         key_py: Py(                             0x00007fa14ea1a040,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb03341b70,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "g": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3de10,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "a": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3dcf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "b": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3dd20,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "r": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3e020,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 4,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "Color",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetBackgroundColor",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetBackgroundColor", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "color",                         lookup_key: Simple {                             key: "color",                             py_key: Py(                                 0x00007fa14ad55e90,                             ),                             path: LookupPath(                                 [                                     S(                                         "color",                                         Py(                                             0x00007fa14ad55ec0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ea1a040,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "a",                                                 lookup_key: Simple {                                                     key: "a",                                                     py_key: Py(                                                         0x00007fa14fa3dcf0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "a",                                                                 Py(                                                                     0x00007fa14fa3dcf0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3dcf0,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "b",                                                 lookup_key: Simple {                                                     key: "b",                                                     py_key: Py(                                                         0x00007fa14fa3dd20,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "b",                                                                 Py(                                                                     0x00007fa14fa3dd20,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3dd20,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "g",                                                 lookup_key: Simple {                                                     key: "g",                                                     py_key: Py(                                                         0x00007fa14fa3de10,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "g",                                                                 Py(                                                                     0x00007fa14fa3de10,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3de10,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "r",                                                 lookup_key: Simple {                                                     key: "r",                                                     py_key: Py(                                                         0x00007fa14fa3e020,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "r",                                                                 Py(                                                                     0x00007fa14fa3e020,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3e020,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "Color",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb03341b70,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "Color",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad55ef0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad55f20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7bfb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_background_color": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7bfb0,                                                 ),                                             ],                                         },                                         expected_repr: "'set_background_color'",                                         name: "literal['set_background_color']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_background_color']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetBackgroundColor",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b2f850,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSetBackgroundColor",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, color: kittycad.models.color.Color, type: Literal['set_background_color'] = 'set_background_color') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

color: Color

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'color': FieldInfo(annotation=Color, required=True), 'type': FieldInfo(annotation=Literal['set_background_color'], required=False, default='set_background_color')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_background_color']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSetCurrentToolProperties(**data)

Set the properties of the tool lines for the scene.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'color': typing.Optional[kittycad.models.color.Color], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['set_current_tool_properties']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSetCurrentToolProperties'>, 'config': {'title': 'OptionSetCurrentToolProperties'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSetCurrentToolProperties'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSetCurrentToolProperties'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSetCurrentToolProperties:94467867744160', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'color': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.color.Color'>, 'config': {'title': 'Color'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.color.Color'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.color.Color'>>]}, 'ref': 'kittycad.models.color.Color:94467859422064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'a': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'b': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'g': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'r': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Color', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'set_current_tool_properties', 'schema': {'expected': ['set_current_tool_properties'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetCurrentToolProperties', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b317a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2b0f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_current_tool_properties",                                             },                                             expected_py: None,                                             name: "literal['set_current_tool_properties']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "color": SerField {                         key_py: Py(                             0x00007fa14ea1a040,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Model(                                                 ModelSerializer {                                                     class: Py(                                                         0x000055eb03341b70,                                                     ),                                                     serializer: Fields(                                                         GeneralFieldsSerializer {                                                             fields: {                                                                 "g": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3de10,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "b": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3dd20,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "r": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3e020,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "a": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3dcf0,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                             },                                                             computed_fields: Some(                                                                 ComputedFields(                                                                     [],                                                                 ),                                                             ),                                                             mode: SimpleDict,                                                             extra_serializer: None,                                                             filter: SchemaFilter {                                                                 include: None,                                                                 exclude: None,                                                             },                                                             required_fields: 4,                                                         },                                                     ),                                                     has_extra: false,                                                     root_model: false,                                                     name: "Color",                                                 },                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetCurrentToolProperties",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetCurrentToolProperties", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "color",                         lookup_key: Simple {                             key: "color",                             py_key: Py(                                 0x00007fa14ad55b00,                             ),                             path: LookupPath(                                 [                                     S(                                         "color",                                         Py(                                             0x00007fa14ad55ad0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ea1a040,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Model(                                             ModelValidator {                                                 revalidate: Never,                                                 validator: ModelFields(                                                     ModelFieldsValidator {                                                         fields: [                                                             Field {                                                                 name: "a",                                                                 lookup_key: Simple {                                                                     key: "a",                                                                     py_key: Py(                                                                         0x00007fa14fa3dcf0,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "a",                                                                                 Py(                                                                                     0x00007fa14fa3dcf0,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3dcf0,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "b",                                                                 lookup_key: Simple {                                                                     key: "b",                                                                     py_key: Py(                                                                         0x00007fa14fa3dd20,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "b",                                                                                 Py(                                                                                     0x00007fa14fa3dd20,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3dd20,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "g",                                                                 lookup_key: Simple {                                                                     key: "g",                                                                     py_key: Py(                                                                         0x00007fa14fa3de10,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "g",                                                                                 Py(                                                                                     0x00007fa14fa3de10,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3de10,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "r",                                                                 lookup_key: Simple {                                                                     key: "r",                                                                     py_key: Py(                                                                         0x00007fa14fa3e020,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "r",                                                                                 Py(                                                                                     0x00007fa14fa3e020,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3e020,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                         ],                                                         model_name: "Color",                                                         extra_behavior: Ignore,                                                         extras_validator: None,                                                         strict: false,                                                         from_attributes: false,                                                         loc_by_alias: true,                                                     },                                                 ),                                                 class: Py(                                                     0x000055eb03341b70,                                                 ),                                                 post_init: None,                                                 frozen: false,                                                 custom_init: false,                                                 root_model: false,                                                 undefined: Py(                                                     0x00007fa14d802350,                                                 ),                                                 name: "Color",                                             },                                         ),                                         name: "nullable[Color]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[Color]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad55c20,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad55bf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2b0f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_current_tool_properties": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2b0f0,                                                 ),                                             ],                                         },                                         expected_repr: "'set_current_tool_properties'",                                         name: "literal['set_current_tool_properties']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_current_tool_properties']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetCurrentToolProperties",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b317a0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSetCurrentToolProperties",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, color: Optional[kittycad.models.color.Color] = None, type: Literal['set_current_tool_properties'] = 'set_current_tool_properties') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

color: Optional[Color]

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'color': FieldInfo(annotation=Union[Color, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['set_current_tool_properties'], required=False, default='set_current_tool_properties')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_current_tool_properties']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSetDefaultSystemProperties(**data)

Set the default system properties used when a specific property isn’t set.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'color': typing.Optional[kittycad.models.color.Color], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['set_default_system_properties']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSetDefaultSystemProperties'>, 'config': {'title': 'OptionSetDefaultSystemProperties'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSetDefaultSystemProperties'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSetDefaultSystemProperties'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSetDefaultSystemProperties:94467867759344', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'color': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.color.Color'>, 'config': {'title': 'Color'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.color.Color'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.color.Color'>>]}, 'ref': 'kittycad.models.color.Color:94467859422064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'a': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'b': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'g': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'r': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Color', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'set_default_system_properties', 'schema': {'expected': ['set_default_system_properties'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetDefaultSystemProperties', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b352f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "color": SerField {                         key_py: Py(                             0x00007fa14ea1a040,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Model(                                                 ModelSerializer {                                                     class: Py(                                                         0x000055eb03341b70,                                                     ),                                                     serializer: Fields(                                                         GeneralFieldsSerializer {                                                             fields: {                                                                 "g": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3de10,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "r": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3e020,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "b": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3dd20,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "a": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3dcf0,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                             },                                                             computed_fields: Some(                                                                 ComputedFields(                                                                     [],                                                                 ),                                                             ),                                                             mode: SimpleDict,                                                             extra_serializer: None,                                                             filter: SchemaFilter {                                                                 include: None,                                                                 exclude: None,                                                             },                                                             required_fields: 4,                                                         },                                                     ),                                                     has_extra: false,                                                     root_model: false,                                                     name: "Color",                                                 },                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2b190,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_default_system_properties",                                             },                                             expected_py: None,                                             name: "literal['set_default_system_properties']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetDefaultSystemProperties",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetDefaultSystemProperties", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "color",                         lookup_key: Simple {                             key: "color",                             py_key: Py(                                 0x00007fa14ad55260,                             ),                             path: LookupPath(                                 [                                     S(                                         "color",                                         Py(                                             0x00007fa14ad55200,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ea1a040,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Model(                                             ModelValidator {                                                 revalidate: Never,                                                 validator: ModelFields(                                                     ModelFieldsValidator {                                                         fields: [                                                             Field {                                                                 name: "a",                                                                 lookup_key: Simple {                                                                     key: "a",                                                                     py_key: Py(                                                                         0x00007fa14fa3dcf0,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "a",                                                                                 Py(                                                                                     0x00007fa14fa3dcf0,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3dcf0,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "b",                                                                 lookup_key: Simple {                                                                     key: "b",                                                                     py_key: Py(                                                                         0x00007fa14fa3dd20,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "b",                                                                                 Py(                                                                                     0x00007fa14fa3dd20,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3dd20,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "g",                                                                 lookup_key: Simple {                                                                     key: "g",                                                                     py_key: Py(                                                                         0x00007fa14fa3de10,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "g",                                                                                 Py(                                                                                     0x00007fa14fa3de10,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3de10,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "r",                                                                 lookup_key: Simple {                                                                     key: "r",                                                                     py_key: Py(                                                                         0x00007fa14fa3e020,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "r",                                                                                 Py(                                                                                     0x00007fa14fa3e020,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3e020,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                         ],                                                         model_name: "Color",                                                         extra_behavior: Ignore,                                                         extras_validator: None,                                                         strict: false,                                                         from_attributes: false,                                                         loc_by_alias: true,                                                     },                                                 ),                                                 class: Py(                                                     0x000055eb03341b70,                                                 ),                                                 post_init: None,                                                 frozen: false,                                                 custom_init: false,                                                 root_model: false,                                                 undefined: Py(                                                     0x00007fa14d802350,                                                 ),                                                 name: "Color",                                             },                                         ),                                         name: "nullable[Color]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[Color]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad551a0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad55170,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2b190,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_default_system_properties": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2b190,                                                 ),                                             ],                                         },                                         expected_repr: "'set_default_system_properties'",                                         name: "literal['set_default_system_properties']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_default_system_properties']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetDefaultSystemProperties",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b352f0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSetDefaultSystemProperties",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, color: Optional[kittycad.models.color.Color] = None, type: Literal['set_default_system_properties'] = 'set_default_system_properties') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

color: Optional[Color]

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'color': FieldInfo(annotation=Union[Color, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Literal['set_default_system_properties'], required=False, default='set_default_system_properties')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_default_system_properties']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSetSceneUnits(**data)

Set the units of the scene. For all following commands, the units will be interpreted as the given units.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['set_scene_units'], 'unit': <enum 'UnitLength'>}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSetSceneUnits'>, 'config': {'title': 'OptionSetSceneUnits'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSetSceneUnits'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSetSceneUnits'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSetSceneUnits:94467867959648', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'set_scene_units', 'schema': {'expected': ['set_scene_units'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}, 'unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitLength'>, 'members': [UnitLength.CM, UnitLength.FT, UnitLength.IN, UnitLength.M, UnitLength.MM, UnitLength.YD], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_length.UnitLength:94467861018320', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'OptionSetSceneUnits', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b66160,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7c1b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_scene_units",                                             },                                             expected_py: None,                                             name: "literal['set_scene_units']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "unit": SerField {                         key_py: Py(                             0x00007fa14e161380,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb034c76d0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetSceneUnits",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetSceneUnits", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc5e60,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc5f80,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7c1b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_scene_units": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7c1b0,                                                 ),                                             ],                                         },                                         expected_repr: "'set_scene_units'",                                         name: "literal['set_scene_units']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_scene_units']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "unit",                         lookup_key: Simple {                             key: "unit",                             py_key: Py(                                 0x00007fa14adc5fb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "unit",                                         Py(                                             0x00007fa14adc5fe0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14e161380,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb034c76d0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "cm": 0,                                             "ft": 1,                                             "in": 2,                                             "m": 3,                                             "mm": 4,                                             "yd": 5,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b3c4c50,                                         ),                                         Py(                                             0x00007fa14b3c51f0,                                         ),                                         Py(                                             0x00007fa14b3c52b0,                                         ),                                         Py(                                             0x00007fa14b3c5310,                                         ),                                         Py(                                             0x00007fa14b3c5370,                                         ),                                         Py(                                             0x00007fa14b3c53d0,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'cm', 'ft', 'in', 'm', 'mm' or 'yd'",                                 strict: false,                                 class_repr: "UnitLength",                                 name: "str-enum[UnitLength]",                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetSceneUnits",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b66160,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSetSceneUnits",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['set_scene_units'] = 'set_scene_units', unit: kittycad.models.unit_length.UnitLength) -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['set_scene_units'], required=False, default='set_scene_units'), 'unit': FieldInfo(annotation=UnitLength, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_scene_units']

unit: UnitLength

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSetSelectionFilter(**data)

What kind of entities can be selected?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'filter': typing.List[kittycad.models.entity_type.EntityType], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['set_selection_filter']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSetSelectionFilter'>, 'config': {'title': 'OptionSetSelectionFilter'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSetSelectionFilter'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSetSelectionFilter'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSetSelectionFilter:94467849608080', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'filter': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'cls': <enum 'EntityType'>, 'members': [EntityType.ENTITY, EntityType.OBJECT, EntityType.PATH, EntityType.CURVE, EntityType.SOLID2D, EntityType.SOLID3D, EntityType.EDGE, EntityType.FACE, EntityType.PLANE, EntityType.VERTEX], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.entity_type.EntityType:94467864596176', 'sub_type': 'str', 'type': 'enum'}, 'type': 'list'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'set_selection_filter', 'schema': {'expected': ['set_selection_filter'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetSelectionFilter', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb029e5b90,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7c270,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_selection_filter",                                             },                                             expected_py: None,                                             name: "literal['set_selection_filter']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "filter": SerField {                         key_py: Py(                             0x00007fa14ef96430,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Enum(                                         EnumSerializer {                                             class: Py(                                                 0x000055eb03830ed0,                                             ),                                             serializer: Some(                                                 Str(                                                     StrSerializer,                                                 ),                                             ),                                         },                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[enum]",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetSelectionFilter",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetSelectionFilter", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "filter",                         lookup_key: Simple {                             key: "filter",                             py_key: Py(                                 0x00007fa14adc6d90,                             ),                             path: LookupPath(                                 [                                     S(                                         "filter",                                         Py(                                             0x00007fa14adc7120,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ef96430,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     StrEnum(                                         EnumValidator {                                             phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                             class: Py(                                                 0x000055eb03830ed0,                                             ),                                             lookup: LiteralLookup {                                                 expected_bool: None,                                                 expected_int: None,                                                 expected_str: Some(                                                     {                                                         "curve": 3,                                                         "entity": 0,                                                         "solid3d": 5,                                                         "path": 2,                                                         "plane": 8,                                                         "vertex": 9,                                                         "face": 7,                                                         "solid2d": 4,                                                         "edge": 6,                                                         "object": 1,                                                     },                                                 ),                                                 expected_py_dict: None,                                                 expected_py_values: None,                                                 values: [                                                     Py(                                                         0x00007fa14b0411f0,                                                     ),                                                     Py(                                                         0x00007fa14b041250,                                                     ),                                                     Py(                                                         0x00007fa14b0412b0,                                                     ),                                                     Py(                                                         0x00007fa14b041310,                                                     ),                                                     Py(                                                         0x00007fa14b041370,                                                     ),                                                     Py(                                                         0x00007fa14b0413d0,                                                     ),                                                     Py(                                                         0x00007fa14b041430,                                                     ),                                                     Py(                                                         0x00007fa14b041490,                                                     ),                                                     Py(                                                         0x00007fa14b0414f0,                                                     ),                                                     Py(                                                         0x00007fa14b041550,                                                     ),                                                 ],                                             },                                             missing: None,                                             expected_repr: "'entity', 'object', 'path', 'curve', 'solid2d', 'solid3d', 'edge', 'face', 'plane' or 'vertex'",                                             strict: false,                                             class_repr: "EntityType",                                             name: "str-enum[EntityType]",                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc5410,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc52c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7c270,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_selection_filter": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7c270,                                                 ),                                             ],                                         },                                         expected_repr: "'set_selection_filter'",                                         name: "literal['set_selection_filter']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_selection_filter']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetSelectionFilter",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb029e5b90,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSetSelectionFilter",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, filter: List[kittycad.models.entity_type.EntityType], type: Literal['set_selection_filter'] = 'set_selection_filter') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

filter: List[EntityType]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=List[EntityType], required=True), 'type': FieldInfo(annotation=Literal['set_selection_filter'], required=False, default='set_selection_filter')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['set_selection_filter']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSetSelectionType(**data)

When you select some entity with the current tool, what should happen to the entity?

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'selection_type': <enum 'SceneSelectionType'>, 'type': typing.Literal['set_selection_type']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSetSelectionType'>, 'config': {'title': 'OptionSetSelectionType'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSetSelectionType'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSetSelectionType'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSetSelectionType:94467868107792', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'selection_type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'SceneSelectionType'>, 'members': [SceneSelectionType.REPLACE, SceneSelectionType.ADD, SceneSelectionType.REMOVE], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.scene_selection_type.SceneSelectionType:94467866263200', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'set_selection_type', 'schema': {'expected': ['set_selection_type'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetSelectionType', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b8a410,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "selection_type": SerField {                         key_py: Py(                             0x00007fa14aff6e30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb039c7ea0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7c370,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_selection_type",                                             },                                             expected_py: None,                                             name: "literal['set_selection_type']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetSelectionType",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetSelectionType", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "selection_type",                         lookup_key: Simple {                             key: "selection_type",                             py_key: Py(                                 0x00007fa14ada95b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "selection_type",                                         Py(                                             0x00007fa14affcbf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff6e30,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb039c7ea0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "replace": 0,                                             "remove": 2,                                             "add": 1,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14afec7d0,                                         ),                                         Py(                                             0x00007fa14afec890,                                         ),                                         Py(                                             0x00007fa14afec8f0,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'replace', 'add' or 'remove'",                                 strict: false,                                 class_repr: "SceneSelectionType",                                 name: "str-enum[SceneSelectionType]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc7960,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc7930,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7c370,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_selection_type": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7c370,                                                 ),                                             ],                                         },                                         expected_repr: "'set_selection_type'",                                         name: "literal['set_selection_type']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_selection_type']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetSelectionType",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b8a410,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSetSelectionType",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, selection_type: kittycad.models.scene_selection_type.SceneSelectionType, type: Literal['set_selection_type'] = 'set_selection_type') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'selection_type': FieldInfo(annotation=SceneSelectionType, required=True), 'type': FieldInfo(annotation=Literal['set_selection_type'], required=False, default='set_selection_type')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

selection_type: SceneSelectionType

type: Literal['set_selection_type']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSetTool(**data)

Set the current tool.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'tool': <enum 'SceneToolType'>, 'type': typing.Literal['set_tool']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSetTool'>, 'config': {'title': 'OptionSetTool'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSetTool'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSetTool'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSetTool:94467867626416', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'tool': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'SceneToolType'>, 'members': [SceneToolType.CAMERA_REVOLVE, SceneToolType.SELECT, SceneToolType.MOVE, SceneToolType.SKETCH_LINE, SceneToolType.SKETCH_TANGENTIAL_ARC, SceneToolType.SKETCH_CURVE, SceneToolType.SKETCH_CURVE_MOD], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.scene_tool_type.SceneToolType:94467866267360', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'set_tool', 'schema': {'expected': ['set_tool'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSetTool', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b14bb0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "tool": SerField {                         key_py: Py(                             0x00007fa14b022340,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb039c8ee0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7c430,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "set_tool",                                             },                                             expected_py: None,                                             name: "literal['set_tool']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionSetTool",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSetTool", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "tool",                         lookup_key: Simple {                             key: "tool",                             py_key: Py(                                 0x00007fa14ae77570,                             ),                             path: LookupPath(                                 [                                     S(                                         "tool",                                         Py(                                             0x00007fa14ae76eb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b022340,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb039c8ee0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "select": 1,                                             "sketch_line": 3,                                             "camera_revolve": 0,                                             "sketch_tangential_arc": 4,                                             "move": 2,                                             "sketch_curve": 5,                                             "sketch_curve_mod": 6,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14afecad0,                                         ),                                         Py(                                             0x00007fa14afeca10,                                         ),                                         Py(                                             0x00007fa14afecb30,                                         ),                                         Py(                                             0x00007fa14afecb90,                                         ),                                         Py(                                             0x00007fa14afecbf0,                                         ),                                         Py(                                             0x00007fa14afecc50,                                         ),                                         Py(                                             0x00007fa14afeccb0,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'camera_revolve', 'select', 'move', 'sketch_line', 'sketch_tangential_arc', 'sketch_curve' or 'sketch_curve_mod'",                                 strict: false,                                 class_repr: "SceneToolType",                                 name: "str-enum[SceneToolType]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae767c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae775a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7c430,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "set_tool": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7c430,                                                 ),                                             ],                                         },                                         expected_repr: "'set_tool'",                                         name: "literal['set_tool']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['set_tool']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSetTool",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b14bb0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSetTool",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, tool: kittycad.models.scene_tool_type.SceneToolType, type: Literal['set_tool'] = 'set_tool') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'tool': FieldInfo(annotation=SceneToolType, required=True), 'type': FieldInfo(annotation=Literal['set_tool'], required=False, default='set_tool')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

tool: SceneToolType

type: Literal['set_tool']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSketchModeDisable(**data)

Disable sketch mode. If you are sketching on a face, be sure to not disable sketch mode until you have extruded. Otherwise, your object will not be fused with the face.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['sketch_mode_disable']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSketchModeDisable'>, 'config': {'title': 'OptionSketchModeDisable'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSketchModeDisable'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSketchModeDisable'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSketchModeDisable:94467867667600', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'sketch_mode_disable', 'schema': {'expected': ['sketch_mode_disable'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSketchModeDisable', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b1ec90,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7c630,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "sketch_mode_disable",                                             },                                             expected_py: None,                                             name: "literal['sketch_mode_disable']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionSketchModeDisable",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSketchModeDisable", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad54810,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad54840,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7c630,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "sketch_mode_disable": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7c630,                                                 ),                                             ],                                         },                                         expected_repr: "'sketch_mode_disable'",                                         name: "literal['sketch_mode_disable']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['sketch_mode_disable']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSketchModeDisable",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b1ec90,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSketchModeDisable",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['sketch_mode_disable'] = 'sketch_mode_disable') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['sketch_mode_disable'], required=False, default='sketch_mode_disable')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['sketch_mode_disable']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid2DAddHole(**data)

Add a hole to a Solid2d object before extruding it.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'hole_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['solid2d_add_hole']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid2DAddHole'>, 'config': {'title': 'OptionSolid2DAddHole'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid2DAddHole'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid2DAddHole'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid2DAddHole:94467867410640', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'hole_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid2d_add_hole', 'schema': {'expected': ['solid2d_add_hole'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid2DAddHole', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ae00d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7c730,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid2d_add_hole",                                             },                                             expected_py: None,                                             name: "literal['solid2d_add_hole']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "hole_id": SerField {                         key_py: Py(                             0x00007fa14afe7cc0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid2DAddHole",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid2DAddHole", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "hole_id",                         lookup_key: Simple {                             key: "hole_id",                             py_key: Py(                                 0x00007fa14ae74c90,                             ),                             path: LookupPath(                                 [                                     S(                                         "hole_id",                                         Py(                                             0x00007fa14ae74cf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe7cc0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af12df0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14af12db0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae74d50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae74db0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7c730,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid2d_add_hole": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7c730,                                                 ),                                             ],                                         },                                         expected_repr: "'solid2d_add_hole'",                                         name: "literal['solid2d_add_hole']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid2d_add_hole']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid2DAddHole",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ae00d0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid2DAddHole",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, hole_id: str, object_id: str, type: Literal['solid2d_add_hole'] = 'solid2d_add_hole') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

hole_id: str

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'hole_id': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['solid2d_add_hole'], required=False, default='solid2d_add_hole')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid2d_add_hole']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DFilletEdge(**data)

Fillets the given edge with the specified radius.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'cut_type': <enum 'CutType'>, 'edge_id': <class 'str'>, 'face_id': typing.Optional[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'radius': <class 'kittycad.models.length_unit.LengthUnit'>, 'tolerance': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['solid3d_fillet_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DFilletEdge'>, 'config': {'title': 'OptionSolid3DFilletEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DFilletEdge'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DFilletEdge'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DFilletEdge:94467867481856', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'cut_type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'fillet', 'schema': {'cls': <enum 'CutType'>, 'members': [CutType.FILLET, CutType.CHAMFER], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.cut_type.CutType:94467864271312', 'sub_type': 'str', 'type': 'enum'}, 'type': 'default'}, 'type': 'model-field'}, 'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'face_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'str'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'radius': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'tolerance': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_fillet_edge', 'schema': {'expected': ['solid3d_fillet_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DFilletEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03af1700,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "face_id": SerField {                         key_py: Py(                             0x00007fa14b32c8a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Str(                                                 StrSerializer,                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "cut_type": SerField {                         key_py: Py(                             0x00007fa14beb7170,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14b188c60,                                         ),                                     ),                                     serializer: Enum(                                         EnumSerializer {                                             class: Py(                                                 0x000055eb037e19d0,                                             ),                                             serializer: Some(                                                 Str(                                                     StrSerializer,                                                 ),                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "radius": SerField {                         key_py: Py(                             0x00007fa14b020cf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "tolerance": SerField {                         key_py: Py(                             0x00007fa14afd8570,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7c7f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_fillet_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_fillet_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 7,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DFilletEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DFilletEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "cut_type",                         lookup_key: Simple {                             key: "cut_type",                             py_key: Py(                                 0x00007fa14af386f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "cut_type",                                         Py(                                             0x00007fa14ad2f7f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14beb7170,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14b188c60,                                     ),                                 ),                                 on_error: Raise,                                 validator: StrEnum(                                     EnumValidator {                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                         class: Py(                                             0x000055eb037e19d0,                                         ),                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "fillet": 0,                                                     "chamfer": 1,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14b1a1550,                                                 ),                                                 Py(                                                     0x00007fa14b1a15b0,                                                 ),                                             ],                                         },                                         missing: None,                                         expected_repr: "'fillet' or 'chamfer'",                                         strict: false,                                         class_repr: "CutType",                                         name: "str-enum[CutType]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[str-enum[CutType]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14b025590,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14b027180,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "face_id",                         lookup_key: Simple {                             key: "face_id",                             py_key: Py(                                 0x00007fa14b024750,                             ),                             path: LookupPath(                                 [                                     S(                                         "face_id",                                         Py(                                             0x00007fa14b025b60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b32c8a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Str(                                             StrValidator {                                                 strict: false,                                                 coerce_numbers_to_str: false,                                             },                                         ),                                         name: "nullable[str]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[str]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ad2f870,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ad2f830,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "radius",                         lookup_key: Simple {                             key: "radius",                             py_key: Py(                                 0x00007fa14b025b90,                             ),                             path: LookupPath(                                 [                                     S(                                         "radius",                                         Py(                                             0x00007fa14b024540,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b020cf0,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14ad2f780,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "tolerance",                         lookup_key: Simple {                             key: "tolerance",                             py_key: Py(                                 0x00007fa14ad2f8b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "tolerance",                                         Py(                                             0x00007fa14ad2f8f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd8570,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14ad2f780,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b026ac0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b0245d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7c7f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_fillet_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7c7f0,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_fillet_edge'",                                         name: "literal['solid3d_fillet_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_fillet_edge']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DFilletEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03af1700,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DFilletEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, cut_type: kittycad.models.cut_type.CutType = 'fillet', edge_id: str, face_id: Optional[str] = None, object_id: str, radius: kittycad.models.length_unit.LengthUnit, tolerance: kittycad.models.length_unit.LengthUnit, type: Literal['solid3d_fillet_edge'] = 'solid3d_fillet_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

cut_type: CutType

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

face_id: Optional[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'cut_type': FieldInfo(annotation=CutType, required=False, default='fillet'), 'edge_id': FieldInfo(annotation=str, required=True), 'face_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'object_id': FieldInfo(annotation=str, required=True), 'radius': FieldInfo(annotation=LengthUnit, required=True), 'tolerance': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['solid3d_fillet_edge'], required=False, default='solid3d_fillet_edge')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

radius: LengthUnit

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

tolerance: LengthUnit

type: Literal['solid3d_fillet_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DGetAllEdgeFaces(**data)

Gets all faces which use the given edge.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'edge_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['solid3d_get_all_edge_faces']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DGetAllEdgeFaces'>, 'config': {'title': 'OptionSolid3DGetAllEdgeFaces'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DGetAllEdgeFaces'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DGetAllEdgeFaces'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DGetAllEdgeFaces:94467867402032', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_get_all_edge_faces', 'schema': {'expected': ['solid3d_get_all_edge_faces'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetAllEdgeFaces', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03addf30,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2b230,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_all_edge_faces",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_all_edge_faces']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetAllEdgeFaces",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetAllEdgeFaces", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14b027d20,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14b027d50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af11930,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14af118f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b027d80,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b027db0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2b230,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_all_edge_faces": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2b230,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_all_edge_faces'",                                         name: "literal['solid3d_get_all_edge_faces']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_all_edge_faces']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetAllEdgeFaces",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03addf30,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DGetAllEdgeFaces",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, edge_id: str, object_id: str, type: Literal['solid3d_get_all_edge_faces'] = 'solid3d_get_all_edge_faces') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'edge_id': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_all_edge_faces'], required=False, default='solid3d_get_all_edge_faces')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_all_edge_faces']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DGetAllOppositeEdges(**data)

Gets all edges which are opposite the given edge, across all possible faces.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'along_vector': typing.Optional[kittycad.models.point3d.Point3d], 'edge_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['solid3d_get_all_opposite_edges']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DGetAllOppositeEdges'>, 'config': {'title': 'OptionSolid3DGetAllOppositeEdges'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DGetAllOppositeEdges'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DGetAllOppositeEdges'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DGetAllOppositeEdges:94467867420064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'along_vector': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_get_all_opposite_edges', 'schema': {'expected': ['solid3d_get_all_opposite_edges'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetAllOppositeEdges', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ae25a0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2b280,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_all_opposite_edges",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_all_opposite_edges']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "along_vector": SerField {                         key_py: Py(                             0x00007fa14b01cbb0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f947100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Model(                                                 ModelSerializer {                                                     class: Py(                                                         0x000055eb0330e750,                                                     ),                                                     serializer: Fields(                                                         GeneralFieldsSerializer {                                                             fields: {                                                                 "y": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3e170,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "z": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3e1a0,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "x": SerField {                                                                     key_py: Py(                                                                         0x00007fa14fa3e140,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                             },                                                             computed_fields: Some(                                                                 ComputedFields(                                                                     [],                                                                 ),                                                             ),                                                             mode: SimpleDict,                                                             extra_serializer: None,                                                             filter: SchemaFilter {                                                                 include: None,                                                                 exclude: None,                                                             },                                                             required_fields: 3,                                                         },                                                     ),                                                     has_extra: false,                                                     root_model: false,                                                     name: "Point3d",                                                 },                                             ),                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetAllOppositeEdges",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetAllOppositeEdges", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "along_vector",                         lookup_key: Simple {                             key: "along_vector",                             py_key: Py(                                 0x00007fa14af111f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "along_vector",                                         Py(                                             0x00007fa14af116b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01cbb0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f947100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Model(                                             ModelValidator {                                                 revalidate: Never,                                                 validator: ModelFields(                                                     ModelFieldsValidator {                                                         fields: [                                                             Field {                                                                 name: "x",                                                                 lookup_key: Simple {                                                                     key: "x",                                                                     py_key: Py(                                                                         0x00007fa14fa3e140,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "x",                                                                                 Py(                                                                                     0x00007fa14fa3e140,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3e140,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "y",                                                                 lookup_key: Simple {                                                                     key: "y",                                                                     py_key: Py(                                                                         0x00007fa14fa3e170,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "y",                                                                                 Py(                                                                                     0x00007fa14fa3e170,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3e170,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                             Field {                                                                 name: "z",                                                                 lookup_key: Simple {                                                                     key: "z",                                                                     py_key: Py(                                                                         0x00007fa14fa3e1a0,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "z",                                                                                 Py(                                                                                     0x00007fa14fa3e1a0,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fa14fa3e1a0,                                                                 ),                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 frozen: false,                                                             },                                                         ],                                                         model_name: "Point3d",                                                         extra_behavior: Ignore,                                                         extras_validator: None,                                                         strict: false,                                                         from_attributes: false,                                                         loc_by_alias: true,                                                     },                                                 ),                                                 class: Py(                                                     0x000055eb0330e750,                                                 ),                                                 post_init: None,                                                 frozen: false,                                                 custom_init: false,                                                 root_model: false,                                                 undefined: Py(                                                     0x00007fa14d802350,                                                 ),                                                 name: "Point3d",                                             },                                         ),                                         name: "nullable[Point3d]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[Point3d]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14b0274e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14b0274b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af11570,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14af114b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b027450,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b027420,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2b280,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_all_opposite_edges": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2b280,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_all_opposite_edges'",                                         name: "literal['solid3d_get_all_opposite_edges']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_all_opposite_edges']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetAllOppositeEdges",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ae25a0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DGetAllOppositeEdges",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, along_vector: Optional[kittycad.models.point3d.Point3d] = None, edge_id: str, object_id: str, type: Literal['solid3d_get_all_opposite_edges'] = 'solid3d_get_all_opposite_edges') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

along_vector: Optional[Point3d]

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'along_vector': FieldInfo(annotation=Union[Point3d, NoneType], required=False, default=None), 'edge_id': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_all_opposite_edges'], required=False, default='solid3d_get_all_opposite_edges')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_all_opposite_edges']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DGetCommonEdge(**data)

Gets the shared edge between these two faces if it exists

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'face_ids': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['solid3d_get_common_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DGetCommonEdge'>, 'config': {'title': 'OptionSolid3DGetCommonEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DGetCommonEdge'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DGetCommonEdge'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DGetCommonEdge:94467867470352', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'face_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_get_common_edge', 'schema': {'expected': ['solid3d_get_common_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetCommonEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03aeea10,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7ca30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_common_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_common_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "face_ids": SerField {                         key_py: Py(                             0x00007fa14afe06b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetCommonEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetCommonEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "face_ids",                         lookup_key: Simple {                             key: "face_ids",                             py_key: Py(                                 0x00007fa14ad2cdb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "face_ids",                                         Py(                                             0x00007fa14ad2cd70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe06b0,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ad2ce30,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ad2cdf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae76130,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae76160,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7ca30,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_common_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7ca30,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_common_edge'",                                         name: "literal['solid3d_get_common_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_common_edge']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetCommonEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03aeea10,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DGetCommonEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, face_ids: List[str], object_id: str, type: Literal['solid3d_get_common_edge'] = 'solid3d_get_common_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

face_ids: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'face_ids': FieldInfo(annotation=List[str], required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_common_edge'], required=False, default='solid3d_get_common_edge')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_common_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DGetExtrusionFaceInfo(**data)

Get a concise description of all of an extrusion’s faces.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'edge_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['solid3d_get_extrusion_face_info']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DGetExtrusionFaceInfo'>, 'config': {'title': 'OptionSolid3DGetExtrusionFaceInfo'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DGetExtrusionFaceInfo'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DGetExtrusionFaceInfo'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DGetExtrusionFaceInfo:94467868253488', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_get_extrusion_face_info', 'schema': {'expected': ['solid3d_get_extrusion_face_info'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetExtrusionFaceInfo', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03badd30,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2b320,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_extrusion_face_info",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_extrusion_face_info']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetExtrusionFaceInfo",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetExtrusionFaceInfo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14ae013e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14ae01410,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ae34af0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ae197f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae01440,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae01470,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2b320,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_extrusion_face_info": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2b320,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_extrusion_face_info'",                                         name: "literal['solid3d_get_extrusion_face_info']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_extrusion_face_info']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetExtrusionFaceInfo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03badd30,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DGetExtrusionFaceInfo",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, edge_id: str, object_id: str, type: Literal['solid3d_get_extrusion_face_info'] = 'solid3d_get_extrusion_face_info') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'edge_id': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_extrusion_face_info'], required=False, default='solid3d_get_extrusion_face_info')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_extrusion_face_info']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DGetNextAdjacentEdge(**data)

Gets the next adjacent edge for the given edge, along the given face.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'edge_id': <class 'str'>, 'face_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['solid3d_get_next_adjacent_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DGetNextAdjacentEdge'>, 'config': {'title': 'OptionSolid3DGetNextAdjacentEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DGetNextAdjacentEdge'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DGetNextAdjacentEdge'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DGetNextAdjacentEdge:94467867447408', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'face_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_get_next_adjacent_edge', 'schema': {'expected': ['solid3d_get_next_adjacent_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetNextAdjacentEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ae9070,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "face_id": SerField {                         key_py: Py(                             0x00007fa14b32c8a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2b3c0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_next_adjacent_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_next_adjacent_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetNextAdjacentEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetNextAdjacentEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14ae75470,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14ae754a0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "face_id",                         lookup_key: Simple {                             key: "face_id",                             py_key: Py(                                 0x00007fa14ae754d0,                             ),                             path: LookupPath(                                 [                                     S(                                         "face_id",                                         Py(                                             0x00007fa14ae75500,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b32c8a0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af1e030,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14af1dff0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae75530,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae75560,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2b3c0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_next_adjacent_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2b3c0,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_next_adjacent_edge'",                                         name: "literal['solid3d_get_next_adjacent_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_next_adjacent_edge']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetNextAdjacentEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ae9070,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DGetNextAdjacentEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, edge_id: str, face_id: str, object_id: str, type: Literal['solid3d_get_next_adjacent_edge'] = 'solid3d_get_next_adjacent_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

face_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'edge_id': FieldInfo(annotation=str, required=True), 'face_id': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_next_adjacent_edge'], required=False, default='solid3d_get_next_adjacent_edge')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_next_adjacent_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DGetOppositeEdge(**data)

Gets the edge opposite the given edge, along the given face.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'edge_id': <class 'str'>, 'face_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['solid3d_get_opposite_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DGetOppositeEdge'>, 'config': {'title': 'OptionSolid3DGetOppositeEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DGetOppositeEdge'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DGetOppositeEdge'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DGetOppositeEdge:94467867429456', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'face_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_get_opposite_edge', 'schema': {'expected': ['solid3d_get_opposite_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetOppositeEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ae4a50,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "face_id": SerField {                         key_py: Py(                             0x00007fa14b32c8a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2b460,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_opposite_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_opposite_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetOppositeEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetOppositeEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14ae74ed0,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14ae74fc0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "face_id",                         lookup_key: Simple {                             key: "face_id",                             py_key: Py(                                 0x00007fa14ae75050,                             ),                             path: LookupPath(                                 [                                     S(                                         "face_id",                                         Py(                                             0x00007fa14ae75020,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b32c8a0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af1c8f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14af1c8b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae74ff0,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae74f90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2b460,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_opposite_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2b460,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_opposite_edge'",                                         name: "literal['solid3d_get_opposite_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_opposite_edge']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetOppositeEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ae4a50,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DGetOppositeEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, edge_id: str, face_id: str, object_id: str, type: Literal['solid3d_get_opposite_edge'] = 'solid3d_get_opposite_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

face_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'edge_id': FieldInfo(annotation=str, required=True), 'face_id': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_opposite_edge'], required=False, default='solid3d_get_opposite_edge')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_opposite_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DGetPrevAdjacentEdge(**data)

Gets the previous adjacent edge for the given edge, along the given face.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'edge_id': <class 'str'>, 'face_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'type': typing.Literal['solid3d_get_prev_adjacent_edge']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DGetPrevAdjacentEdge'>, 'config': {'title': 'OptionSolid3DGetPrevAdjacentEdge'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DGetPrevAdjacentEdge'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DGetPrevAdjacentEdge'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DGetPrevAdjacentEdge:94467867458848', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'edge_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'face_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_get_prev_adjacent_edge', 'schema': {'expected': ['solid3d_get_prev_adjacent_edge'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DGetPrevAdjacentEdge', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03aebd20,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd2b4b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_get_prev_adjacent_edge",                                             },                                             expected_py: None,                                             name: "literal['solid3d_get_prev_adjacent_edge']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "edge_id": SerField {                         key_py: Py(                             0x00007fa14afd2a60,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "face_id": SerField {                         key_py: Py(                             0x00007fa14b32c8a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DGetPrevAdjacentEdge",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DGetPrevAdjacentEdge", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "edge_id",                         lookup_key: Simple {                             key: "edge_id",                             py_key: Py(                                 0x00007fa14ae75a70,                             ),                             path: LookupPath(                                 [                                     S(                                         "edge_id",                                         Py(                                             0x00007fa14ae75a40,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2a60,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "face_id",                         lookup_key: Simple {                             key: "face_id",                             py_key: Py(                                 0x00007fa14ae75b00,                             ),                             path: LookupPath(                                 [                                     S(                                         "face_id",                                         Py(                                             0x00007fa14ae75b30,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b32c8a0,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14af1f770,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14af1f730,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae75b60,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae75b90,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd2b4b0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_get_prev_adjacent_edge": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd2b4b0,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_get_prev_adjacent_edge'",                                         name: "literal['solid3d_get_prev_adjacent_edge']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_get_prev_adjacent_edge']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DGetPrevAdjacentEdge",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03aebd20,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DGetPrevAdjacentEdge",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, edge_id: str, face_id: str, object_id: str, type: Literal['solid3d_get_prev_adjacent_edge'] = 'solid3d_get_prev_adjacent_edge') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

edge_id: str

face_id: str

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'edge_id': FieldInfo(annotation=str, required=True), 'face_id': FieldInfo(annotation=str, required=True), 'object_id': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['solid3d_get_prev_adjacent_edge'], required=False, default='solid3d_get_prev_adjacent_edge')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['solid3d_get_prev_adjacent_edge']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSolid3DShellFace(**data)

Command for shelling a solid3d face

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'face_ids': typing.List[str], 'hollow': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_id': <class 'str'>, 'shell_thickness': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['solid3d_shell_face']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSolid3DShellFace'>, 'config': {'title': 'OptionSolid3DShellFace'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSolid3DShellFace'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSolid3DShellFace'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSolid3DShellFace:94467866561008', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'face_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'hollow': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': False, 'schema': {'type': 'bool'}, 'type': 'default'}, 'type': 'model-field'}, 'object_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'shell_thickness': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'solid3d_shell_face', 'schema': {'expected': ['solid3d_shell_face'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSolid3DShellFace', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03a109f0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "shell_thickness": SerField {                         key_py: Py(                             0x00007fa14afe06f0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "object_id": SerField {                         key_py: Py(                             0x00007fa14d969d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "hollow": SerField {                         key_py: Py(                             0x00007fa14afd2760,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f930d20,                                         ),                                     ),                                     serializer: Bool(                                         BoolSerializer,                                     ),                                 },                             ),                         ),                         required: true,                     },                     "face_ids": SerField {                         key_py: Py(                             0x00007fa14afe06b0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7cd70,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "solid3d_shell_face",                                             },                                             expected_py: None,                                             name: "literal['solid3d_shell_face']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 5,             },         ),         has_extra: false,         root_model: false,         name: "OptionSolid3DShellFace",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSolid3DShellFace", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "face_ids",                         lookup_key: Simple {                             key: "face_ids",                             py_key: Py(                                 0x00007fa14ae3ba30,                             ),                             path: LookupPath(                                 [                                     S(                                         "face_ids",                                         Py(                                             0x00007fa14ae3ba70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe06b0,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "hollow",                         lookup_key: Simple {                             key: "hollow",                             py_key: Py(                                 0x00007fa14afe6af0,                             ),                             path: LookupPath(                                 [                                     S(                                         "hollow",                                         Py(                                             0x00007fa14afe6b20,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afd2760,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f930d20,                                     ),                                 ),                                 on_error: Raise,                                 validator: Bool(                                     BoolValidator {                                         strict: false,                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[bool]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_id",                         lookup_key: Simple {                             key: "object_id",                             py_key: Py(                                 0x00007fa14ae3b9b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_id",                                         Py(                                             0x00007fa14ae3b9f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14d969d70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "shell_thickness",                         lookup_key: Simple {                             key: "shell_thickness",                             py_key: Py(                                 0x00007fa14ae3b970,                             ),                             path: LookupPath(                                 [                                     S(                                         "shell_thickness",                                         Py(                                             0x00007fa14ae3b930,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14afe06f0,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055eb03768720,                                 ),                                 config: Py(                                     0x00007fa14ae3bb00,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe6b50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe6b80,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7cd70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "solid3d_shell_face": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7cd70,                                                 ),                                             ],                                         },                                         expected_repr: "'solid3d_shell_face'",                                         name: "literal['solid3d_shell_face']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['solid3d_shell_face']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSolid3DShellFace",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03a109f0,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSolid3DShellFace",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, face_ids: List[str], hollow: bool = False, object_id: str, shell_thickness: kittycad.models.length_unit.LengthUnit, type: Literal['solid3d_shell_face'] = 'solid3d_shell_face') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

face_ids: List[str]

classmethod from_orm(obj)

Return type:

Self

hollow: bool

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'face_ids': FieldInfo(annotation=List[str], required=True), 'hollow': FieldInfo(annotation=bool, required=False, default=False), 'object_id': FieldInfo(annotation=str, required=True), 'shell_thickness': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['solid3d_shell_face'], required=False, default='solid3d_shell_face')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_id: str

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

shell_thickness: LengthUnit

type: Literal['solid3d_shell_face']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionStartPath(**data)

Start a new path.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['start_path']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionStartPath'>, 'config': {'title': 'OptionStartPath'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionStartPath'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionStartPath'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionStartPath:94467866433152', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'start_path', 'schema': {'expected': ['start_path'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionStartPath', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb039f1680,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7d030,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "start_path",                                             },                                             expected_py: None,                                             name: "literal['start_path']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 1,             },         ),         has_extra: false,         root_model: false,         name: "OptionStartPath",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionStartPath", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14afe4e10,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14afe4ed0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7d030,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "start_path": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7d030,                                                 ),                                             ],                                         },                                         expected_repr: "'start_path'",                                         name: "literal['start_path']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['start_path']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionStartPath",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb039f1680,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionStartPath",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, type: Literal['start_path'] = 'start_path') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['start_path'], required=False, default='start_path')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['start_path']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionSurfaceArea(**data)

Get the surface area of entities in the scene or the default scene.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_ids': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'output_unit': <enum 'UnitArea'>, 'type': typing.Literal['surface_area']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionSurfaceArea'>, 'config': {'title': 'OptionSurfaceArea'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionSurfaceArea'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionSurfaceArea'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionSurfaceArea:94467868085632', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'output_unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitArea'>, 'members': [UnitArea.CM2, UnitArea.DM2, UnitArea.FT2, UnitArea.IN2, UnitArea.KM2, UnitArea.M2, UnitArea.MM2, UnitArea.YD2], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_area.UnitArea:94467863212352', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'surface_area', 'schema': {'expected': ['surface_area'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionSurfaceArea', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b84d80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "entity_ids": SerField {                         key_py: Py(                             0x00007fa14b038970,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "output_unit": SerField {                         key_py: Py(                             0x00007fa14bb4f470,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb036df140,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7d5f0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "surface_area",                                             },                                             expected_py: None,                                             name: "literal['surface_area']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionSurfaceArea",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionSurfaceArea", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_ids",                         lookup_key: Simple {                             key: "entity_ids",                             py_key: Py(                                 0x00007fa14adf4670,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_ids",                                         Py(                                             0x00007fa14adf4630,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b038970,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "output_unit",                         lookup_key: Simple {                             key: "output_unit",                             py_key: Py(                                 0x00007fa14af38730,                             ),                             path: LookupPath(                                 [                                     S(                                         "output_unit",                                         Py(                                             0x00007fa14adf46f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bb4f470,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb036df140,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "yd2": 7,                                             "cm2": 0,                                             "ft2": 2,                                             "in2": 3,                                             "dm2": 1,                                             "mm2": 6,                                             "m2": 5,                                             "km2": 4,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b3c7950,                                         ),                                         Py(                                             0x00007fa14b3c79b0,                                         ),                                         Py(                                             0x00007fa14b3c7a10,                                         ),                                         Py(                                             0x00007fa14b3c7a70,                                         ),                                         Py(                                             0x00007fa14b3c7ad0,                                         ),                                         Py(                                             0x00007fa14b3c7b30,                                         ),                                         Py(                                             0x00007fa14b3c7b90,                                         ),                                         Py(                                             0x00007fa14b3c7bf0,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'cm2', 'dm2', 'ft2', 'in2', 'km2', 'm2', 'mm2' or 'yd2'",                                 strict: false,                                 class_repr: "UnitArea",                                 name: "str-enum[UnitArea]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc7780,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc77e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7d5f0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "surface_area": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7d5f0,                                                 ),                                             ],                                         },                                         expected_repr: "'surface_area'",                                         name: "literal['surface_area']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['surface_area']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionSurfaceArea",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b84d80,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionSurfaceArea",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_ids: List[str], output_unit: kittycad.models.unit_area.UnitArea, type: Literal['surface_area'] = 'surface_area') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_ids: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_ids': FieldInfo(annotation=List[str], required=True), 'output_unit': FieldInfo(annotation=UnitArea, required=True), 'type': FieldInfo(annotation=Literal['surface_area'], required=False, default='surface_area')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

output_unit: UnitArea

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['surface_area']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionTakeSnapshot(**data)

Take a snapshot of the current view.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'format': <enum 'ImageFormat'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'type': typing.Literal['take_snapshot']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionTakeSnapshot'>, 'config': {'title': 'OptionTakeSnapshot'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionTakeSnapshot'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionTakeSnapshot'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionTakeSnapshot:94467867800912', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'format': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'ImageFormat'>, 'members': [ImageFormat.PNG, ImageFormat.JPEG], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.image_format.ImageFormat:94467850098944', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'take_snapshot', 'schema': {'expected': ['take_snapshot'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionTakeSnapshot', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b3f550,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7d670,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "take_snapshot",                                             },                                             expected_py: None,                                             name: "literal['take_snapshot']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "format": SerField {                         key_py: Py(                             0x00007fa14fa38b50,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb02a5d900,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionTakeSnapshot",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionTakeSnapshot", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "format",                         lookup_key: Simple {                             key: "format",                             py_key: Py(                                 0x00007fa14ad56b20,                             ),                             path: LookupPath(                                 [                                     S(                                         "format",                                         Py(                                             0x00007fa14ad56b50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa38b50,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb02a5d900,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "jpeg": 1,                                             "png": 0,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b1185f0,                                         ),                                         Py(                                             0x00007fa14b118650,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'png' or 'jpeg'",                                 strict: false,                                 class_repr: "ImageFormat",                                 name: "str-enum[ImageFormat]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ad56670,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ad56700,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7d670,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "take_snapshot": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7d670,                                                 ),                                             ],                                         },                                         expected_repr: "'take_snapshot'",                                         name: "literal['take_snapshot']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['take_snapshot']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionTakeSnapshot",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b3f550,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionTakeSnapshot",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, format: kittycad.models.image_format.ImageFormat, type: Literal['take_snapshot'] = 'take_snapshot') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

format: ImageFormat

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'format': FieldInfo(annotation=ImageFormat, required=True), 'type': FieldInfo(annotation=Literal['take_snapshot'], required=False, default='take_snapshot')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['take_snapshot']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionUpdateAnnotation(**data)

Update an annotation

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'annotation_id': <class 'str'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'options': <class 'kittycad.models.annotation_options.AnnotationOptions'>, 'type': typing.Literal['update_annotation']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <enum 'AnnotationLineEnd'>, 'members': [AnnotationLineEnd.NONE, AnnotationLineEnd.ARROW], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.annotation_line_end.AnnotationLineEnd:94467860848624', 'sub_type': 'str', 'type': 'enum'}], 'schema': {'cls': <class 'kittycad.models.modeling_cmd.OptionUpdateAnnotation'>, 'config': {'title': 'OptionUpdateAnnotation'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionUpdateAnnotation'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionUpdateAnnotation'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionUpdateAnnotation:94467867242048', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'annotation_id': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'options': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <class 'kittycad.models.annotation_options.AnnotationOptions'>, 'config': {'title': 'AnnotationOptions'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.annotation_options.AnnotationOptions'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.annotation_options.AnnotationOptions'>>]}, 'ref': 'kittycad.models.annotation_options.AnnotationOptions:94467859218624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'color': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.color.Color'>, 'config': {'title': 'Color'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.color.Color'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.color.Color'>>]}, 'ref': 'kittycad.models.color.Color:94467859422064', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'a': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'b': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'g': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'r': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Color', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'line_ends': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.annotation_line_end_options.AnnotationLineEndOptions'>, 'config': {'title': 'AnnotationLineEndOptions'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.annotation_line_end_options.AnnotationLineEndOptions'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.annotation_line_end_options.AnnotationLineEndOptions'>>]}, 'ref': 'kittycad.models.annotation_line_end_options.AnnotationLineEndOptions:94467862299104', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'end': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.annotation_line_end.AnnotationLineEnd:94467860848624', 'type': 'definition-ref'}, 'type': 'model-field'}, 'start': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'schema_ref': 'kittycad.models.annotation_line_end.AnnotationLineEnd:94467860848624', 'type': 'definition-ref'}, 'type': 'model-field'}}, 'model_name': 'AnnotationLineEndOptions', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'line_width': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'type': 'float'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'position': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.point3d.Point3d'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94467859212112', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'text': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.annotation_text_options.AnnotationTextOptions'>, 'config': {'title': 'AnnotationTextOptions'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.annotation_text_options.AnnotationTextOptions'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.annotation_text_options.AnnotationTextOptions'>>]}, 'ref': 'kittycad.models.annotation_text_options.AnnotationTextOptions:94467859412128', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'point_size': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'int'}, 'type': 'model-field'}, 'text': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'type': 'str'}, 'type': 'model-field'}, 'x': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'AnnotationTextAlignmentX'>, 'members': [AnnotationTextAlignmentX.LEFT, AnnotationTextAlignmentX.CENTER, AnnotationTextAlignmentX.RIGHT], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.annotation_text_alignment_x.AnnotationTextAlignmentX:94467862308832', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'y': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'AnnotationTextAlignmentY'>, 'members': [AnnotationTextAlignmentY.BOTTOM, AnnotationTextAlignmentY.CENTER, AnnotationTextAlignmentY.TOP], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.annotation_text_alignment_y.AnnotationTextAlignmentY:94467859410352', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}}, 'model_name': 'AnnotationTextOptions', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'AnnotationOptions', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'update_annotation', 'schema': {'expected': ['update_annotation'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionUpdateAnnotation', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'definitions'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ab6e40,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "annotation_id": SerField {                         key_py: Py(                             0x00007fa14aff7c70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Str(                                 StrSerializer,                             ),                         ),                         required: true,                     },                     "options": SerField {                         key_py: Py(                             0x00007fa14fa3aa38,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055eb033100c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "position": SerField {                                                     key_py: Py(                                                         0x00007fa14e255bf0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb0330e750,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "y": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e170,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "x": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e140,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "z": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e1a0,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 3,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "Point3d",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "line_ends": SerField {                                                     key_py: Py(                                                         0x00007fa14b1d3770,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb036001e0,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "end": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa38368,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Recursive(                                                                                                         DefinitionRefSerializer {                                                                                                             definition: "...",                                                                                                             retry_with_lax_check: false,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "start": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3bce8,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Recursive(                                                                                                         DefinitionRefSerializer {                                                                                                             definition: "...",                                                                                                             retry_with_lax_check: false,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 2,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "AnnotationLineEndOptions",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "text": SerField {                                                     key_py: Py(                                                         0x00007fa14fa3c298,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb0333f4a0,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "point_size": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14b2a67b0,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Int(                                                                                                         IntSerializer,                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "text": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3c298,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Str(                                                                                                         StrSerializer,                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "x": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e140,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Enum(                                                                                                         EnumSerializer {                                                                                                             class: Py(                                                                                                                 0x000055eb036027e0,                                                                                                             ),                                                                                                             serializer: Some(                                                                                                                 Str(                                                                                                                     StrSerializer,                                                                                                                 ),                                                                                                             ),                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "y": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e170,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Enum(                                                                                                         EnumSerializer {                                                                                                             class: Py(                                                                                                                 0x000055eb0333edb0,                                                                                                             ),                                                                                                             serializer: Some(                                                                                                                 Str(                                                                                                                     StrSerializer,                                                                                                                 ),                                                                                                             ),                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 4,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "AnnotationTextOptions",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "line_width": SerField {                                                     key_py: Py(                                                         0x00007fa14b1d37f0,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "color": SerField {                                                     key_py: Py(                                                         0x00007fa14ea1a040,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         WithDefault(                                                             WithDefaultSerializer {                                                                 default: Default(                                                                     Py(                                                                         0x00007fa14f947100,                                                                     ),                                                                 ),                                                                 serializer: Nullable(                                                                     NullableSerializer {                                                                         serializer: Model(                                                                             ModelSerializer {                                                                                 class: Py(                                                                                     0x000055eb03341b70,                                                                                 ),                                                                                 serializer: Fields(                                                                                     GeneralFieldsSerializer {                                                                                         fields: {                                                                                             "b": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3dd20,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "r": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3e020,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "a": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3dcf0,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                             "g": SerField {                                                                                                 key_py: Py(                                                                                                     0x00007fa14fa3de10,                                                                                                 ),                                                                                                 alias: None,                                                                                                 alias_py: None,                                                                                                 serializer: Some(                                                                                                     Float(                                                                                                         FloatSerializer {                                                                                                             inf_nan_mode: Null,                                                                                                         },                                                                                                     ),                                                                                                 ),                                                                                                 required: true,                                                                                             },                                                                                         },                                                                                         computed_fields: Some(                                                                                             ComputedFields(                                                                                                 [],                                                                                             ),                                                                                         ),                                                                                         mode: SimpleDict,                                                                                         extra_serializer: None,                                                                                         filter: SchemaFilter {                                                                                             include: None,                                                                                             exclude: None,                                                                                         },                                                                                         required_fields: 4,                                                                                     },                                                                                 ),                                                                                 has_extra: false,                                                                                 root_model: false,                                                                                 name: "Color",                                                                             },                                                                         ),                                                                     },                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                             },                                             computed_fields: Some(                                                 ComputedFields(                                                     [],                                                 ),                                             ),                                             mode: SimpleDict,                                             extra_serializer: None,                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             required_fields: 5,                                         },                                     ),                                     has_extra: false,                                     root_model: false,                                     name: "AnnotationOptions",                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd7eff0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "update_annotation",                                             },                                             expected_py: None,                                             name: "literal['update_annotation']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionUpdateAnnotation",     }, ), definitions=[Enum(EnumSerializer { class: Py(0x55eb0349dff0), serializer: Some(Str(StrSerializer)) })])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionUpdateAnnotation", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "annotation_id",                         lookup_key: Simple {                             key: "annotation_id",                             py_key: Py(                                 0x00007fa14af05730,                             ),                             path: LookupPath(                                 [                                     S(                                         "annotation_id",                                         Py(                                             0x00007fa14af056f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14aff7c70,                         ),                         validator: Str(                             StrValidator {                                 strict: false,                                 coerce_numbers_to_str: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "options",                         lookup_key: Simple {                             key: "options",                             py_key: Py(                                 0x00007fa14b0262b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "options",                                         Py(                                             0x00007fa14b0262e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3aa38,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "color",                                                 lookup_key: Simple {                                                     key: "color",                                                     py_key: Py(                                                         0x00007fa14b0260d0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "color",                                                                 Py(                                                                     0x00007fa14b026100,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14ea1a040,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "a",                                                                                         lookup_key: Simple {                                                                                             key: "a",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3dcf0,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "a",                                                                                                         Py(                                                                                                             0x00007fa14fa3dcf0,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3dcf0,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "b",                                                                                         lookup_key: Simple {                                                                                             key: "b",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3dd20,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "b",                                                                                                         Py(                                                                                                             0x00007fa14fa3dd20,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3dd20,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "g",                                                                                         lookup_key: Simple {                                                                                             key: "g",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3de10,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "g",                                                                                                         Py(                                                                                                             0x00007fa14fa3de10,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3de10,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "r",                                                                                         lookup_key: Simple {                                                                                             key: "r",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e020,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "r",                                                                                                         Py(                                                                                                             0x00007fa14fa3e020,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e020,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "Color",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055eb03341b70,                                                                         ),                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                         name: "Color",                                                                     },                                                                 ),                                                                 name: "nullable[Color]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Color]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "line_ends",                                                 lookup_key: Simple {                                                     key: "line_ends",                                                     py_key: Py(                                                         0x00007fa14af057b0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "line_ends",                                                                 Py(                                                                     0x00007fa14af05770,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14b1d3770,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "end",                                                                                         lookup_key: Simple {                                                                                             key: "end",                                                                                             py_key: Py(                                                                                                 0x00007fa14b026130,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "end",                                                                                                         Py(                                                                                                             0x00007fa14b026160,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa38368,                                                                                         ),                                                                                         validator: DefinitionRef(                                                                                             DefinitionRefValidator {                                                                                                 definition: "...",                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "start",                                                                                         lookup_key: Simple {                                                                                             key: "start",                                                                                             py_key: Py(                                                                                                 0x00007fa14b026190,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "start",                                                                                                         Py(                                                                                                             0x00007fa14b0261c0,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3bce8,                                                                                         ),                                                                                         validator: DefinitionRef(                                                                                             DefinitionRefValidator {                                                                                                 definition: "...",                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "AnnotationLineEndOptions",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055eb036001e0,                                                                         ),                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                         name: "AnnotationLineEndOptions",                                                                     },                                                                 ),                                                                 name: "nullable[AnnotationLineEndOptions]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[AnnotationLineEndOptions]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "line_width",                                                 lookup_key: Simple {                                                     key: "line_width",                                                     py_key: Py(                                                         0x00007fa14af057f0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "line_width",                                                                 Py(                                                                     0x00007fa14af05830,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14b1d37f0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Float(                                                                     FloatValidator {                                                                         strict: false,                                                                         allow_inf_nan: true,                                                                     },                                                                 ),                                                                 name: "nullable[float]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[float]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "position",                                                 lookup_key: Simple {                                                     key: "position",                                                     py_key: Py(                                                         0x00007fa14af05870,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "position",                                                                 Py(                                                                     0x00007fa14af058b0,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14e255bf0,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "x",                                                                                         lookup_key: Simple {                                                                                             key: "x",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e140,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "x",                                                                                                         Py(                                                                                                             0x00007fa14fa3e140,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e140,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "y",                                                                                         lookup_key: Simple {                                                                                             key: "y",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e170,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "y",                                                                                                         Py(                                                                                                             0x00007fa14fa3e170,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e170,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "z",                                                                                         lookup_key: Simple {                                                                                             key: "z",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e1a0,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "z",                                                                                                         Py(                                                                                                             0x00007fa14fa3e1a0,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e1a0,                                                                                         ),                                                                                         validator: Float(                                                                                             FloatValidator {                                                                                                 strict: false,                                                                                                 allow_inf_nan: true,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "Point3d",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055eb0330e750,                                                                         ),                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                         name: "Point3d",                                                                     },                                                                 ),                                                                 name: "nullable[Point3d]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[Point3d]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "text",                                                 lookup_key: Simple {                                                     key: "text",                                                     py_key: Py(                                                         0x00007fa14b026250,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "text",                                                                 Py(                                                                     0x00007fa14b026280,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fa14fa3c298,                                                 ),                                                 validator: WithDefault(                                                     WithDefaultValidator {                                                         default: Default(                                                             Py(                                                                 0x00007fa14f947100,                                                             ),                                                         ),                                                         on_error: Raise,                                                         validator: Nullable(                                                             NullableValidator {                                                                 validator: Model(                                                                     ModelValidator {                                                                         revalidate: Never,                                                                         validator: ModelFields(                                                                             ModelFieldsValidator {                                                                                 fields: [                                                                                     Field {                                                                                         name: "point_size",                                                                                         lookup_key: Simple {                                                                                             key: "point_size",                                                                                             py_key: Py(                                                                                                 0x00007fa14af058f0,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "point_size",                                                                                                         Py(                                                                                                             0x00007fa14af05930,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14b2a67b0,                                                                                         ),                                                                                         validator: Int(                                                                                             IntValidator {                                                                                                 strict: false,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "text",                                                                                         lookup_key: Simple {                                                                                             key: "text",                                                                                             py_key: Py(                                                                                                 0x00007fa14b0261f0,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "text",                                                                                                         Py(                                                                                                             0x00007fa14b026220,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3c298,                                                                                         ),                                                                                         validator: Str(                                                                                             StrValidator {                                                                                                 strict: false,                                                                                                 coerce_numbers_to_str: false,                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "x",                                                                                         lookup_key: Simple {                                                                                             key: "x",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e140,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "x",                                                                                                         Py(                                                                                                             0x00007fa14fa3e140,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e140,                                                                                         ),                                                                                         validator: StrEnum(                                                                                             EnumValidator {                                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                                 class: Py(                                                                                                     0x000055eb036027e0,                                                                                                 ),                                                                                                 lookup: LiteralLookup {                                                                                                     expected_bool: None,                                                                                                     expected_int: None,                                                                                                     expected_str: Some(                                                                                                         {                                                                                                             "left": 0,                                                                                                             "center": 1,                                                                                                             "right": 2,                                                                                                         },                                                                                                     ),                                                                                                     expected_py_dict: None,                                                                                                     expected_py_values: None,                                                                                                     values: [                                                                                                         Py(                                                                                                             0x00007fa14b361f10,                                                                                                         ),                                                                                                         Py(                                                                                                             0x00007fa14b361f70,                                                                                                         ),                                                                                                         Py(                                                                                                             0x00007fa14b361fd0,                                                                                                         ),                                                                                                     ],                                                                                                 },                                                                                                 missing: None,                                                                                                 expected_repr: "'left', 'center' or 'right'",                                                                                                 strict: false,                                                                                                 class_repr: "AnnotationTextAlignmentX",                                                                                                 name: "str-enum[AnnotationTextAlignmentX]",                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                     Field {                                                                                         name: "y",                                                                                         lookup_key: Simple {                                                                                             key: "y",                                                                                             py_key: Py(                                                                                                 0x00007fa14fa3e170,                                                                                             ),                                                                                             path: LookupPath(                                                                                                 [                                                                                                     S(                                                                                                         "y",                                                                                                         Py(                                                                                                             0x00007fa14fa3e170,                                                                                                         ),                                                                                                     ),                                                                                                 ],                                                                                             ),                                                                                         },                                                                                         name_py: Py(                                                                                             0x00007fa14fa3e170,                                                                                         ),                                                                                         validator: StrEnum(                                                                                             EnumValidator {                                                                                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                                                 class: Py(                                                                                                     0x000055eb0333edb0,                                                                                                 ),                                                                                                 lookup: LiteralLookup {                                                                                                     expected_bool: None,                                                                                                     expected_int: None,                                                                                                     expected_str: Some(                                                                                                         {                                                                                                             "top": 2,                                                                                                             "bottom": 0,                                                                                                             "center": 1,                                                                                                         },                                                                                                     ),                                                                                                     expected_py_dict: None,                                                                                                     expected_py_values: None,                                                                                                     values: [                                                                                                         Py(                                                                                                             0x00007fa14b3620f0,                                                                                                         ),                                                                                                         Py(                                                                                                             0x00007fa14b362150,                                                                                                         ),                                                                                                         Py(                                                                                                             0x00007fa14b3621b0,                                                                                                         ),                                                                                                     ],                                                                                                 },                                                                                                 missing: None,                                                                                                 expected_repr: "'bottom', 'center' or 'top'",                                                                                                 strict: false,                                                                                                 class_repr: "AnnotationTextAlignmentY",                                                                                                 name: "str-enum[AnnotationTextAlignmentY]",                                                                                             },                                                                                         ),                                                                                         frozen: false,                                                                                     },                                                                                 ],                                                                                 model_name: "AnnotationTextOptions",                                                                                 extra_behavior: Ignore,                                                                                 extras_validator: None,                                                                                 strict: false,                                                                                 from_attributes: false,                                                                                 loc_by_alias: true,                                                                             },                                                                         ),                                                                         class: Py(                                                                             0x000055eb0333f4a0,                                                                         ),                                                                         post_init: None,                                                                         frozen: false,                                                                         custom_init: false,                                                                         root_model: false,                                                                         undefined: Py(                                                                             0x00007fa14d802350,                                                                         ),                                                                         name: "AnnotationTextOptions",                                                                     },                                                                 ),                                                                 name: "nullable[AnnotationTextOptions]",                                                             },                                                         ),                                                         validate_default: false,                                                         copy_default: false,                                                         name: "default[nullable[AnnotationTextOptions]]",                                                         undefined: Py(                                                             0x00007fa14d802350,                                                         ),                                                     },                                                 ),                                                 frozen: false,                                             },                                         ],                                         model_name: "AnnotationOptions",                                         extra_behavior: Ignore,                                         extras_validator: None,                                         strict: false,                                         from_attributes: false,                                         loc_by_alias: true,                                     },                                 ),                                 class: Py(                                     0x000055eb033100c0,                                 ),                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                                 name: "AnnotationOptions",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14b026310,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14b026340,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd7eff0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "update_annotation": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd7eff0,                                                 ),                                             ],                                         },                                         expected_repr: "'update_annotation'",                                         name: "literal['update_annotation']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['update_annotation']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionUpdateAnnotation",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ab6e40,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionUpdateAnnotation",     }, ), definitions=[StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55eb0349dff0), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"none": 0, "arrow": 1}), expected_py_dict: None, expected_py_values: None, values: [Py(0x7fa14b361730), Py(0x7fa14b361c10)] }, missing: None, expected_repr: "'none' or 'arrow'", strict: false, class_repr: "AnnotationLineEnd", name: "str-enum[AnnotationLineEnd]" })], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, annotation_id: str, options: kittycad.models.annotation_options.AnnotationOptions, type: Literal['update_annotation'] = 'update_annotation') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

annotation_id: str

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation_id': FieldInfo(annotation=str, required=True), 'options': FieldInfo(annotation=AnnotationOptions, required=True), 'type': FieldInfo(annotation=Literal['update_annotation'], required=False, default='update_annotation')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

options: AnnotationOptions

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['update_annotation']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionViewIsometric(**data)

Fit the view to the scene with an isometric view.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'padding': <class 'float'>, 'type': typing.Literal['view_isometric']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionViewIsometric'>, 'config': {'title': 'OptionViewIsometric'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionViewIsometric'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionViewIsometric'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionViewIsometric:94467868238624', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'padding': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 0.0, 'schema': {'type': 'float'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'view_isometric', 'schema': {'expected': ['view_isometric'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionViewIsometric', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03baa320,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "padding": SerField {                         key_py: Py(                             0x00007fa14ea196e0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14b1e7e70,                                         ),                                     ),                                     serializer: Float(                                         FloatSerializer {                                             inf_nan_mode: Null,                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd9f870,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "view_isometric",                                             },                                             expected_py: None,                                             name: "literal['view_isometric']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 2,             },         ),         has_extra: false,         root_model: false,         name: "OptionViewIsometric",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionViewIsometric", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "padding",                         lookup_key: Simple {                             key: "padding",                             py_key: Py(                                 0x00007fa14ae00b10,                             ),                             path: LookupPath(                                 [                                     S(                                         "padding",                                         Py(                                             0x00007fa14ae00c00,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ea196e0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14b1e7e70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[float]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae00930,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae009f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd9f870,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "view_isometric": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd9f870,                                                 ),                                             ],                                         },                                         expected_repr: "'view_isometric'",                                         name: "literal['view_isometric']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['view_isometric']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionViewIsometric",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03baa320,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionViewIsometric",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, padding: float = 0.0, type: Literal['view_isometric'] = 'view_isometric') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'padding': FieldInfo(annotation=float, required=False, default=0.0), 'type': FieldInfo(annotation=Literal['view_isometric'], required=False, default='view_isometric')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

padding: float

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['view_isometric']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionVolume(**data)

Get the volume of entities in the scene or the default scene.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'entity_ids': typing.List[str], 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'output_unit': <enum 'UnitVolume'>, 'type': typing.Literal['volume']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionVolume'>, 'config': {'title': 'OptionVolume'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionVolume'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionVolume'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionVolume:94467868059776', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'entity_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'model-field'}, 'output_unit': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'cls': <enum 'UnitVolume'>, 'members': [UnitVolume.CM3, UnitVolume.FT3, UnitVolume.IN3, UnitVolume.M3, UnitVolume.YD3, UnitVolume.USFLOZ, UnitVolume.USGAL, UnitVolume.L, UnitVolume.ML], 'metadata': {'pydantic_js_functions': [<function GenerateSchema._enum_schema.<locals>.get_json_schema>]}, 'ref': 'kittycad.models.unit_volume.UnitVolume:94467863223008', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'volume', 'schema': {'expected': ['volume'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionVolume', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03b7e880,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14fa3c7f8,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "volume",                                             },                                             expected_py: None,                                             name: "literal['volume']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "entity_ids": SerField {                         key_py: Py(                             0x00007fa14b038970,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             List(                                 ListSerializer {                                     item_serializer: Str(                                         StrSerializer,                                     ),                                     filter: SchemaFilter {                                         include: None,                                         exclude: None,                                     },                                     name: "list[str]",                                 },                             ),                         ),                         required: true,                     },                     "output_unit": SerField {                         key_py: Py(                             0x00007fa14bb4f470,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Enum(                                 EnumSerializer {                                     class: Py(                                         0x000055eb036e1ae0,                                     ),                                     serializer: Some(                                         Str(                                             StrSerializer,                                         ),                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 3,             },         ),         has_extra: false,         root_model: false,         name: "OptionVolume",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionVolume", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "entity_ids",                         lookup_key: Simple {                             key: "entity_ids",                             py_key: Py(                                 0x00007fa14affcff0,                             ),                             path: LookupPath(                                 [                                     S(                                         "entity_ids",                                         Py(                                             0x00007fa14ade83f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b038970,                         ),                         validator: List(                             ListValidator {                                 strict: false,                                 item_validator: Some(                                     Str(                                         StrValidator {                                             strict: false,                                             coerce_numbers_to_str: false,                                         },                                     ),                                 ),                                 min_length: None,                                 max_length: None,                                 name: OnceLock(                                     <uninit>,                                 ),                                 fail_fast: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "output_unit",                         lookup_key: Simple {                             key: "output_unit",                             py_key: Py(                                 0x00007fa14ad2dd30,                             ),                             path: LookupPath(                                 [                                     S(                                         "output_unit",                                         Py(                                             0x00007fa14ade82b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14bb4f470,                         ),                         validator: StrEnum(                             EnumValidator {                                 phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                 class: Py(                                     0x000055eb036e1ae0,                                 ),                                 lookup: LiteralLookup {                                     expected_bool: None,                                     expected_int: None,                                     expected_str: Some(                                         {                                             "m3": 3,                                             "cm3": 0,                                             "usgal": 6,                                             "l": 7,                                             "in3": 2,                                             "ft3": 1,                                             "yd3": 4,                                             "usfloz": 5,                                             "ml": 8,                                         },                                     ),                                     expected_py_dict: None,                                     expected_py_values: None,                                     values: [                                         Py(                                             0x00007fa14b3c7f50,                                         ),                                         Py(                                             0x00007fa14b3c7fb0,                                         ),                                         Py(                                             0x00007fa14b38c050,                                         ),                                         Py(                                             0x00007fa14b38c0b0,                                         ),                                         Py(                                             0x00007fa14b38c110,                                         ),                                         Py(                                             0x00007fa14b38c170,                                         ),                                         Py(                                             0x00007fa14b38c1d0,                                         ),                                         Py(                                             0x00007fa14b38c230,                                         ),                                         Py(                                             0x00007fa14b38c290,                                         ),                                     ],                                 },                                 missing: None,                                 expected_repr: "'cm3', 'ft3', 'in3', 'm3', 'yd3', 'usfloz', 'usgal', 'l' or 'ml'",                                 strict: false,                                 class_repr: "UnitVolume",                                 name: "str-enum[UnitVolume]",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14adc6b50,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14adc6bb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14fa3c7f8,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "volume": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14fa3c7f8,                                                 ),                                             ],                                         },                                         expected_repr: "'volume'",                                         name: "literal['volume']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['volume']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionVolume",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03b7e880,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionVolume",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, entity_ids: List[str], output_unit: kittycad.models.unit_volume.UnitVolume, type: Literal['volume'] = 'volume') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

entity_ids: List[str]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'entity_ids': FieldInfo(annotation=List[str], required=True), 'output_unit': FieldInfo(annotation=UnitVolume, required=True), 'type': FieldInfo(annotation=Literal['volume'], required=False, default='volume')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

output_unit: UnitVolume

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['volume']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.modeling_cmd.OptionZoomToFit(**data)

Fit the view to the specified object(s).

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__abstractmethods__ = frozenset({})

__annotations__ = {'__class_vars__': 'ClassVar[set[str]]', '__private_attributes__': 'ClassVar[Dict[str, ModelPrivateAttr]]', '__pydantic_complete__': 'ClassVar[bool]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields_set__': 'set[str]', '__pydantic_generic_metadata__': 'ClassVar[_generics.PydanticGenericMetadata]', '__pydantic_parent_namespace__': 'ClassVar[Dict[str, Any] | None]', '__pydantic_post_init__': "ClassVar[None | Literal['model_post_init']]", '__pydantic_private__': 'dict[str, Any] | None', '__pydantic_root_model__': 'ClassVar[bool]', '__pydantic_serializer__': 'ClassVar[SchemaSerializer]', '__pydantic_validator__': 'ClassVar[SchemaValidator | PluggableSchemaValidator]', '__signature__': 'ClassVar[Signature]', 'animated': <class 'bool'>, 'model_computed_fields': 'ClassVar[Dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[Dict[str, FieldInfo]]', 'object_ids': typing.List[str], 'padding': <class 'float'>, 'type': typing.Literal['zoom_to_fit']}

classmethod __class_getitem__(typevar_values)

Return type:

type[BaseModel] | PydanticRecursiveRef

__class_vars__: ClassVar[set[str]] = {}

The names of the class variables defined on the model.

__copy__()

Returns a shallow copy of the model.

Return type:

Self

__deepcopy__(memo=None)

Returns a deep copy of the model.

Return type:

Self

__delattr__(item)

Implement delattr(self, name).

Return type:

Any

__dict__

__eq__(other)

Return self==value.

Return type:

bool

property __fields_set__: set[str]

classmethod __get_pydantic_core_schema__(source, handler, /)

Hook into generating the model’s CoreSchema.

Parameters:

• source (type[BaseModel]) – The class we are generating a schema for. This will generally be the same as the cls argument if this is a classmethod.

• handler (GetCoreSchemaHandler) – A callable that calls into Pydantic’s internal CoreSchema generation logic.

Return type:

Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]

Returns:

A pydantic-core CoreSchema.

classmethod __get_pydantic_json_schema__(core_schema, handler, /)

Hook into generating the model’s JSON schema.

Parameters:

• core_schema (Union[AnySchema, NoneSchema, BoolSchema, IntSchema, FloatSchema, DecimalSchema, StringSchema, BytesSchema, DateSchema, TimeSchema, DatetimeSchema, TimedeltaSchema, LiteralSchema, EnumSchema, IsInstanceSchema, IsSubclassSchema, CallableSchema, ListSchema, TupleSchema, SetSchema, FrozenSetSchema, GeneratorSchema, DictSchema, AfterValidatorFunctionSchema, BeforeValidatorFunctionSchema, WrapValidatorFunctionSchema, PlainValidatorFunctionSchema, WithDefaultSchema, NullableSchema, UnionSchema, TaggedUnionSchema, ChainSchema, LaxOrStrictSchema, JsonOrPythonSchema, TypedDictSchema, ModelFieldsSchema, ModelSchema, DataclassArgsSchema, DataclassSchema, ArgumentsSchema, CallSchema, CustomErrorSchema, JsonSchema, UrlSchema, MultiHostUrlSchema, DefinitionsSchema, DefinitionReferenceSchema, UuidSchema, ComplexSchema]) – A pydantic-core CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema ({'type': 'nullable', 'schema': current_schema}), or just call the handler with the original schema.

• handler (GetJsonSchemaHandler) – Call into Pydantic’s internal JSON schema generation. This will raise a pydantic.errors.PydanticInvalidForJsonSchema if JSON schema generation fails. Since this gets called by BaseModel.model_json_schema you can override the schema_generator argument to that function to change JSON schema generation globally for a type.

Return type:

Dict[str, Any]

Returns:

A JSON schema, as a Python object.

__getattr__(item)

Return type:

Any

__getstate__()

Helper for pickle.

Return type:

dict[Any, Any]

__hash__ = None

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__iter__()

So dict(model) works.

Return type:

Generator[Tuple[str, Any], None, None]

__module__ = 'kittycad.models.modeling_cmd'

__pretty__(fmt, **kwargs)

Used by devtools (https://python-devtools.helpmanual.io/) to pretty print objects.

Return type:

Generator[Any, None, None]

__private_attributes__: ClassVar[Dict[str, ModelPrivateAttr]] = {}

Metadata about the private attributes of the model.

__pydantic_complete__: ClassVar[bool] = True

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.modeling_cmd.OptionZoomToFit'>, 'config': {'title': 'OptionZoomToFit'}, 'custom_init': False, 'metadata': {'pydantic_js_annotation_functions': [], 'pydantic_js_functions': [functools.partial(<function modify_model_json_schema>, cls=<class 'kittycad.models.modeling_cmd.OptionZoomToFit'>, title=None), <bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.modeling_cmd.OptionZoomToFit'>>]}, 'ref': 'kittycad.models.modeling_cmd.OptionZoomToFit:94467868228480', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'animated': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': False, 'schema': {'type': 'bool'}, 'type': 'default'}, 'type': 'model-field'}, 'object_ids': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': [], 'schema': {'items_schema': {'type': 'str'}, 'type': 'list'}, 'type': 'default'}, 'type': 'model-field'}, 'padding': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 0.0, 'schema': {'type': 'float'}, 'type': 'default'}, 'type': 'model-field'}, 'type': {'metadata': {'pydantic_js_annotation_functions': [<function get_json_schema_update_func.<locals>.json_schema_update_func>], 'pydantic_js_functions': []}, 'schema': {'default': 'zoom_to_fit', 'schema': {'expected': ['zoom_to_fit'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionZoomToFit', 'type': 'model-fields'}, 'type': 'model'}

The core schema of the model.

__pydantic_custom_init__: ClassVar[bool] = False

Whether the model has a custom __init__ method.

__pydantic_decorators__: ClassVar[_decorators.DecoratorInfos] = DecoratorInfos(validators={}, field_validators={}, root_validators={}, field_serializers={}, model_serializers={}, model_validators={}, computed_fields={})

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_extra__: dict[str, Any] | None

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.

__pydantic_fields_set__: set[str]

The names of fields explicitly set during instantiation.

__pydantic_generic_metadata__: ClassVar[_generics.PydanticGenericMetadata] = {'args': (), 'origin': None, 'parameters': ()}

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

classmethod __pydantic_init_subclass__(**kwargs)

This is intended to behave just like __init_subclass__, but is called by ModelMetaclass only after the class is actually fully initialized. In particular, attributes like model_fields will be present when this is called.

This is necessary because __init_subclass__ will always be called by type.__new__, and it would require a prohibitively large refactor to the ModelMetaclass to ensure that type.__new__ was called in such a manner that the class would already be sufficiently initialized.

This will receive the same kwargs that would be passed to the standard __init_subclass__, namely, any kwargs passed to the class definition that aren’t used internally by pydantic.

Parameters:

**kwargs (Any) – Any keyword arguments passed to the class definition that aren’t used internally by pydantic.

Return type:

None

__pydantic_parent_namespace__: ClassVar[Dict[str, Any] | None] = None

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__: ClassVar[None | Literal['model_post_init']] = None

The name of the post-init method for the model, if defined.

__pydantic_private__: dict[str, Any] | None

Values of private attributes set on the model instance.

__pydantic_root_model__: ClassVar[bool] = False

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__: ClassVar[SchemaSerializer] = SchemaSerializer(serializer=Model(     ModelSerializer {         class: Py(             0x000055eb03ba7b80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "object_ids": SerField {                         key_py: Py(                             0x00007fa14ae2c770,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14add0600,                                         ),                                     ),                                     serializer: List(                                         ListSerializer {                                             item_serializer: Str(                                                 StrSerializer,                                             ),                                             filter: SchemaFilter {                                                 include: None,                                                 exclude: None,                                             },                                             name: "list[str]",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fa14fa3c5a0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14bd9fcb0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "zoom_to_fit",                                             },                                             expected_py: None,                                             name: "literal['zoom_to_fit']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "animated": SerField {                         key_py: Py(                             0x00007fa14b01ec30,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14f930d20,                                         ),                                     ),                                     serializer: Bool(                                         BoolSerializer,                                     ),                                 },                             ),                         ),                         required: true,                     },                     "padding": SerField {                         key_py: Py(                             0x00007fa14ea196e0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fa14b1e7e70,                                         ),                                     ),                                     serializer: Float(                                         FloatSerializer {                                             inf_nan_mode: Null,                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                 },                 computed_fields: Some(                     ComputedFields(                         [],                     ),                 ),                 mode: SimpleDict,                 extra_serializer: None,                 filter: SchemaFilter {                     include: None,                     exclude: None,                 },                 required_fields: 4,             },         ),         has_extra: false,         root_model: false,         name: "OptionZoomToFit",     }, ), definitions=[])

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionZoomToFit", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "animated",                         lookup_key: Simple {                             key: "animated",                             py_key: Py(                                 0x00007fa14ae188b0,                             ),                             path: LookupPath(                                 [                                     S(                                         "animated",                                         Py(                                             0x00007fa14ae18870,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14b01ec30,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14f930d20,                                     ),                                 ),                                 on_error: Raise,                                 validator: Bool(                                     BoolValidator {                                         strict: false,                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[bool]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "object_ids",                         lookup_key: Simple {                             key: "object_ids",                             py_key: Py(                                 0x00007fa14ae18930,                             ),                             path: LookupPath(                                 [                                     S(                                         "object_ids",                                         Py(                                             0x00007fa14ae188f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ae2c770,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14add0600,                                     ),                                 ),                                 on_error: Raise,                                 validator: List(                                     ListValidator {                                         strict: false,                                         item_validator: Some(                                             Str(                                                 StrValidator {                                                     strict: false,                                                     coerce_numbers_to_str: false,                                                 },                                             ),                                         ),                                         min_length: None,                                         max_length: None,                                         name: OnceLock(                                             "list[str]",                                         ),                                         fail_fast: false,                                     },                                 ),                                 validate_default: false,                                 copy_default: true,                                 name: "default[list[str]]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "padding",                         lookup_key: Simple {                             key: "padding",                             py_key: Py(                                 0x00007fa14ae01020,                             ),                             path: LookupPath(                                 [                                     S(                                         "padding",                                         Py(                                             0x00007fa14ae01050,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14ea196e0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14b1e7e70,                                     ),                                 ),                                 on_error: Raise,                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[float]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fa14ae01080,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fa14ae010b0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fa14fa3c5a0,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fa14bd9fcb0,                                     ),                                 ),                                 on_error: Raise,                                 validator: Literal(                                     LiteralValidator {                                         lookup: LiteralLookup {                                             expected_bool: None,                                             expected_int: None,                                             expected_str: Some(                                                 {                                                     "zoom_to_fit": 0,                                                 },                                             ),                                             expected_py_dict: None,                                             expected_py_values: None,                                             values: [                                                 Py(                                                     0x00007fa14bd9fcb0,                                                 ),                                             ],                                         },                                         expected_repr: "'zoom_to_fit'",                                         name: "literal['zoom_to_fit']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['zoom_to_fit']]",                                 undefined: Py(                                     0x00007fa14d802350,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionZoomToFit",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055eb03ba7b80,         ),         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fa14d802350,         ),         name: "OptionZoomToFit",     }, ), definitions=[], cache_strings=True)

The pydantic-core SchemaValidator used to validate instances of the model.

__repr__()

Return repr(self).

Return type:

str

__repr_args__()

Return type:

Iterable[tuple[str | None, Any]]

__repr_name__()

Name of the instance’s class, used in __repr__.

Return type:

str

__repr_str__(join_str)

Return type:

str

__rich_repr__()

Used by Rich (https://rich.readthedocs.io/en/stable/pretty.html) to pretty print objects.

Return type:

Iterable[Any | tuple[Any] | tuple[str, Any] | tuple[str, Any, Any]]

__setattr__(name, value)

Implement setattr(self, name, value).

Return type:

None

__setstate__(state)

Return type:

None

__signature__: ClassVar[Signature] = <Signature (*, animated: bool = False, object_ids: List[str] = [], padding: float = 0.0, type: Literal['zoom_to_fit'] = 'zoom_to_fit') -> None>

The synthesized __init__ [Signature][inspect.Signature] of the model.

__slots__ = ('__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__')

__str__()

Return str(self).

Return type:

str

_abc_impl = <_abc._abc_data object>

_calculate_keys(*args, **kwargs)

Return type:

Any

_check_frozen(name, value)

Return type:

None

_copy_and_set_values(*args, **kwargs)

Return type:

Any

classmethod _get_value(*args, **kwargs)

Return type:

Any

_iter(*args, **kwargs)

Return type:

Any

animated: bool

classmethod construct(_fields_set=None, **values)

Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

• include – Optional set or mapping specifying which fields to include in the copied model.

• exclude – Optional set or mapping specifying which fields to exclude in the copied model.

• update – Optional dictionary of field-value pairs to override field values in the copied model.

• deep – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)

Return type:

Dict[str, Any]

classmethod from_orm(obj)

Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)

Return type:

str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == 'allow', then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == 'ignore' (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == 'forbid' does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values (Any) – Trusted or pre-validated data dictionary.

Return type:

Self

Returns:

A new instance of the Model class with validated data.

model_copy(*, update=None, deep=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (dict[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

• deep (bool) – Set to True to make a deep copy of the model.

Return type:

Self

Returns:

New model instance.

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

• mode (Union[Literal['json', 'python'], str]) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to include in the output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – A set of fields to exclude from the output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to use the field’s alias in the dictionary key if defined.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

dict[str, Any]

Returns:

A dictionary representation of the model.

model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)

Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

• indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

• include (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to include in the JSON output.

• exclude (Union[Set[int], Set[str], Mapping[int, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, Literal[True]]], Mapping[str, Union[IncEx, Literal[True]]], Literal[True]]], None]) – Field(s) to exclude from the JSON output.

• context (Any | None) – Additional context to pass to the serializer.

• by_alias (bool) – Whether to serialize using field aliases.

• exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

• exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

• exclude_none (bool) – Whether to exclude fields that have a value of None.

• round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

• warnings (Union[bool, Literal['none', 'warn', 'error']]) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

• serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

Return type:

str

Returns:

A JSON string representation of the model.

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to "allow".

model_fields: ClassVar[Dict[str, FieldInfo]] = {'animated': FieldInfo(annotation=bool, required=False, default=False), 'object_ids': FieldInfo(annotation=List[str], required=False, default=[]), 'padding': FieldInfo(annotation=float, required=False, default=0.0), 'type': FieldInfo(annotation=Literal['zoom_to_fit'], required=False, default='zoom_to_fit')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')

Generates a JSON schema for a model class.

Parameters:

• by_alias (bool) – Whether to use attribute aliases or not.

• ref_template (str) – The reference template.

• schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

• mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Return type:

dict[str, Any]

Returns:

The JSON schema for the given model class.

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Return type:

str

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

Return type:

None

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

• force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

• raise_errors (bool) – Whether to raise errors, defaults to True.

• _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

• _types_namespace (dict[str, Any] | None) – The types namespace, defaults to None.

Return type:

bool | None

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)

Validate a pydantic model instance.

Parameters:

• obj (Any) – The object to validate.

• strict (bool | None) – Whether to enforce types strictly.

• from_attributes (bool | None) – Whether to extract data from object attributes.

• context (Any | None) – Additional context to pass to the validator.

Raises:

ValidationError – If the object could not be validated.

Return type:

Self

Returns:

The validated model instance.

classmethod model_validate_json(json_data, *, strict=None, context=None)

Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

• json_data (str | bytes | bytearray) – The JSON data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

classmethod model_validate_strings(obj, *, strict=None, context=None)

Validate the given object with string data against the Pydantic model.

Parameters:

• obj (Any) – The object containing string data to validate.

• strict (bool | None) – Whether to enforce types strictly.

• context (Any | None) – Extra variables to pass to the validator.

Return type:

Self

Returns:

The validated Pydantic model.

object_ids: List[str]

padding: float

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod parse_obj(obj)

Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')

Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)

Return type:

str

type: Literal['zoom_to_fit']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self