kittycad.models.path_segment

Classes

OptionArc(**data)	A circular arc segment.
OptionArcTo(**data)	Adds an arc from the current position that goes through the given interior point and ends at the given end position
OptionBezier(**data)	A cubic bezier curve segment.
OptionLine(**data)	A straight line segment.
OptionTangentialArc(**data)	Adds a tangent arc from current pen position with the given radius and angle.
OptionTangentialArcTo(**data)	Adds a tangent arc from current pen position to the new position.

class kittycad.models.path_segment.OptionArc(**data)

A circular arc segment. Arcs can be drawn clockwise when start > end.

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_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__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.point2d.Point2d'>, 'end': <class 'kittycad.models.angle.Angle'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'radius': <class 'kittycad.models.length_unit.LengthUnit'>, 'relative': <class 'bool'>, 'start': <class 'kittycad.models.angle.Angle'>, 'type': typing.Literal['arc']}

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[InvalidSchema, 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[InvalidSchema, 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.path_segment'

__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_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.angle.Angle'>, 'config': {'title': 'Angle'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.angle.Angle'>>]}, 'ref': 'kittycad.models.angle.Angle:94250672058048', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'unit': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.unit_angle.UnitAngle:94250676395408', 'type': 'definition-ref'}, 'type': 'model-field'}, 'value': {'metadata': {}, '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:94250676395408', 'sub_type': 'str', 'type': 'enum'}], 'schema': {'cls': <class 'kittycad.models.path_segment.OptionArc'>, 'config': {'title': 'OptionArc'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionArc'>>]}, 'ref': 'kittycad.models.path_segment.OptionArc:94250679769056', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'center': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point2d.Point2d'>, 'config': {'title': 'Point2d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point2d.Point2d'>>]}, 'ref': 'kittycad.models.point2d.Point2d:94250679674304', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'y': {'metadata': {}, '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': {}, 'schema': {'schema_ref': 'kittycad.models.angle.Angle:94250672058048', 'type': 'definition-ref'}, 'type': 'model-field'}, 'radius': {'metadata': {}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'relative': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'start': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.angle.Angle:94250672058048', 'type': 'definition-ref'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'arc', 'schema': {'expected': ['arc'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionArc', '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__: ClassVar[Dict[str, FieldInfo]] = {'center': FieldInfo(annotation=Point2d, required=True), 'end': FieldInfo(annotation=Angle, required=True), 'radius': FieldInfo(annotation=LengthUnit, required=True), 'relative': FieldInfo(annotation=bool, required=True), 'start': FieldInfo(annotation=Angle, required=True), 'type': FieldInfo(annotation=Literal['arc'], required=False, default='arc')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__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(             0x000055b8724997e0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "center": SerField {                         key_py: Py(                             0x00007fc70fb08150,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055b8724825c0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fc710624450,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fc710624420,                                                     ),                                                     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,                     },                     "start": SerField {                         key_py: Py(                             0x00007fc710621fc8,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "end": SerField {                         key_py: Py(                             0x00007fc71061e648,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "relative": SerField {                         key_py: Py(                             0x00007fc70ee5ecf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "radius": SerField {                         key_py: Py(                             0x00007fc70b9f1260,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fc710622880,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fc70d939920,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "arc",                                             },                                             expected_py: None,                                             name: "literal['arc']",                                         },                                     ),                                 },                             ),                         ),                         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",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55b871d3eec0), serializer: Fields(GeneralFieldsSerializer { fields: {"unit": SerField { key_py: Py(0x7fc70ed61a10), alias: None, alias_py: None, serializer: Some(Recursive(DefinitionRefSerializer { definition: "...", retry_with_lax_check: false })), required: true }, "value": SerField { key_py: Py(0x7fc710622a48), 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" }), Enum(EnumSerializer { class: Py(0x55b872161d90), serializer: Some(Str(StrSerializer)) })])

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

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionArc", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "center",                         lookup_key: Simple {                             key: "center",                             py_key: Py(                                 0x00007fc70b9a09c0,                             ),                             path: LookupPath(                                 [                                     S(                                         "center",                                         Py(                                             0x00007fc70b9a09f0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70fb08150,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fc710624420,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fc710624420,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710624420,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055b87230c5c0,                                                         ),                                                         config: Py(                                                             0x00007fc70b94de80,                                                         ),                                                         name: "function-after[LengthUnit(), float]",                                                         field_name: None,                                                         info_arg: false,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fc710624450,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fc710624450,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710624450,                                                 ),                                                 validator: FunctionAfter(                                                     FunctionAfterValidator {                                                         validator: Float(                                                             FloatValidator {                                                                 strict: false,                                                                 allow_inf_nan: true,                                                             },                                                         ),                                                         func: Py(                                                             0x000055b87230c5c0,                                                         ),                                                         config: Py(                                                             0x00007fc70b94de80,                                                         ),                                                         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(                                     0x000055b8724825c0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                                 name: "Point2d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "end",                         lookup_key: Simple {                             key: "end",                             py_key: Py(                                 0x00007fc70b9a0a20,                             ),                             path: LookupPath(                                 [                                     S(                                         "end",                                         Py(                                             0x00007fc70b9a0a50,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc71061e648,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "radius",                         lookup_key: Simple {                             key: "radius",                             py_key: Py(                                 0x00007fc70b9a0a80,                             ),                             path: LookupPath(                                 [                                     S(                                         "radius",                                         Py(                                             0x00007fc70b9a0ab0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70b9f1260,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055b87230c5c0,                                 ),                                 config: Py(                                     0x00007fc70b94eac0,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "relative",                         lookup_key: Simple {                             key: "relative",                             py_key: Py(                                 0x00007fc70b97baf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "relative",                                         Py(                                             0x00007fc70b97b970,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70ee5ecf0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "start",                         lookup_key: Simple {                             key: "start",                             py_key: Py(                                 0x00007fc70b9a0ae0,                             ),                             path: LookupPath(                                 [                                     S(                                         "start",                                         Py(                                             0x00007fc70b9a0b10,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc710621fc8,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fc70b9a0b40,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fc70b9a0b70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc710622880,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fc70d939920,                                     ),                                 ),                                 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,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007fc70b97bd80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007fc70d939920,                                                 ),                                             ],                                         },                                         expected_repr: "'arc'",                                         name: "literal['arc']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['arc']]",                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionArc",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055b8724997e0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fc70e4ea3d0,         ),         name: "OptionArc",     }, ), definitions=[StrEnum(EnumValidator { phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>, class: Py(0x55b872161d90), lookup: LiteralLookup { expected_bool: None, expected_int: None, expected_str: Some({"degrees": 0, "radians": 1}), expected_py_dict: None, expected_py_values: None, expected_py_primitives: Some(Py(0x7fc70b97bf40)), values: [Py(0x7fc70bd734d0), Py(0x7fc70bd73530)] }, missing: None, expected_repr: "'degrees' or 'radians'", strict: false, class_repr: "UnitAngle", name: "str-enum[UnitAngle]" }), Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "unit", lookup_key: Simple { key: "unit", py_key: Py(0x7fc70b9a0900), path: LookupPath([S("unit", Py(0x7fc70b9a0930))]) }, name_py: Py(0x7fc70ed61a10), validator: DefinitionRef(DefinitionRefValidator { definition: "..." }), frozen: false }, Field { name: "value", lookup_key: Simple { key: "value", py_key: Py(0x7fc70b9a0960), path: LookupPath([S("value", Py(0x7fc70b9a0990))]) }, name_py: Py(0x7fc710622a48), 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(0x55b871d3eec0), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fc70e4ea3d0), name: "Angle" })], cache_strings=True)

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

__replace__(**changes)

Return type:

Self

__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_recursion__(object)

Returns the string representation of a recursive object.

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.point2d.Point2d, end: kittycad.models.angle.Angle, radius: kittycad.models.length_unit.LengthUnit, relative: bool, start: kittycad.models.angle.Angle, type: Literal['arc'] = 'arc') -> 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: Point2d

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:

`python {test="skip" lint="skip"} 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]

end: Angle

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]] = {}

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/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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=Point2d, required=True), 'end': FieldInfo(annotation=Angle, required=True), 'radius': FieldInfo(annotation=LengthUnit, required=True), 'relative': FieldInfo(annotation=bool, required=True), 'start': FieldInfo(annotation=Angle, required=True), 'type': FieldInfo(annotation=Literal['arc'], required=False, default='arc')}

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 (Optional[Mapping[str, Any]]) – 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/2.10/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

radius: LengthUnit

relative: 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

start: Angle

type: Literal['arc']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.path_segment.OptionArcTo(**data)

Adds an arc from the current position that goes through the given interior point and ends at the given end position

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_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__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]', 'end': <class 'kittycad.models.point3d.Point3d'>, 'interior': <class 'kittycad.models.point3d.Point3d'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'relative': <class 'bool'>, 'type': typing.Literal['arc_to']}

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[InvalidSchema, 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[InvalidSchema, 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.path_segment'

__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_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94250662434656', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.path_segment.OptionArcTo'>, 'config': {'title': 'OptionArcTo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionArcTo'>>]}, 'ref': 'kittycad.models.path_segment.OptionArcTo:94250679725760', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'end': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94250662434656', 'type': 'definition-ref'}, 'type': 'model-field'}, 'interior': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94250662434656', 'type': 'definition-ref'}, 'type': 'model-field'}, 'relative': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'arc_to', 'schema': {'expected': ['arc_to'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionArcTo', '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__: ClassVar[Dict[str, FieldInfo]] = {'end': FieldInfo(annotation=Point3d, required=True), 'interior': FieldInfo(annotation=Point3d, required=True), 'relative': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['arc_to'], required=False, default='arc_to')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__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(             0x000055b87248eec0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "interior": SerField {                         key_py: Py(                             0x00007fc70b83da70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "relative": SerField {                         key_py: Py(                             0x00007fc70ee5ecf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fc710622880,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fc70b9a13b0,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "arc_to",                                             },                                             expected_py: None,                                             name: "literal['arc_to']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "end": SerField {                         key_py: Py(                             0x00007fc71061e648,                         ),                         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",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55b871411760), serializer: Fields(GeneralFieldsSerializer { fields: {"x": SerField { key_py: Py(0x7fc710624420), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7fc710624480), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "y": SerField { key_py: Py(0x7fc710624450), 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="OptionArcTo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "end",                         lookup_key: Simple {                             key: "end",                             py_key: Py(                                 0x00007fc70b9a1320,                             ),                             path: LookupPath(                                 [                                     S(                                         "end",                                         Py(                                             0x00007fc70b9a1350,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc71061e648,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "interior",                         lookup_key: Simple {                             key: "interior",                             py_key: Py(                                 0x00007fc70b83dc30,                             ),                             path: LookupPath(                                 [                                     S(                                         "interior",                                         Py(                                             0x00007fc70b83dbf0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70b83da70,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "relative",                         lookup_key: Simple {                             key: "relative",                             py_key: Py(                                 0x00007fc70b83dcf0,                             ),                             path: LookupPath(                                 [                                     S(                                         "relative",                                         Py(                                             0x00007fc70b83dcb0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70ee5ecf0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fc70b9a1380,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fc70b9a13e0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc710622880,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fc70b9a13b0,                                     ),                                 ),                                 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,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007fc70b83dd80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007fc70b9a13b0,                                                 ),                                             ],                                         },                                         expected_repr: "'arc_to'",                                         name: "literal['arc_to']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['arc_to']]",                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionArcTo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055b87248eec0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fc70e4ea3d0,         ),         name: "OptionArcTo",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fc710624420), path: LookupPath([S("x", Py(0x7fc710624420))]) }, name_py: Py(0x7fc710624420), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fc710624450), path: LookupPath([S("y", Py(0x7fc710624450))]) }, name_py: Py(0x7fc710624450), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fc710624480), path: LookupPath([S("z", Py(0x7fc710624480))]) }, name_py: Py(0x7fc710624480), 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(0x55b871411760), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fc70e4ea3d0), name: "Point3d" })], cache_strings=True)

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

__replace__(**changes)

Return type:

Self

__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_recursion__(object)

Returns the string representation of a recursive object.

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 (*, end: kittycad.models.point3d.Point3d, interior: kittycad.models.point3d.Point3d, relative: bool, type: Literal['arc_to'] = 'arc_to') -> 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:

`python {test="skip" lint="skip"} 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]

end: Point3d

classmethod from_orm(obj)

Return type:

Self

interior: Point3d

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]] = {}

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/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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]] = {'end': FieldInfo(annotation=Point3d, required=True), 'interior': FieldInfo(annotation=Point3d, required=True), 'relative': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['arc_to'], required=False, default='arc_to')}

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 (Optional[Mapping[str, Any]]) – 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/2.10/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

relative: 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['arc_to']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.path_segment.OptionBezier(**data)

A cubic bezier curve segment. Start at the end of the current line, go through control point 1 and 2, then end at a given point.

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_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__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]', 'control1': <class 'kittycad.models.point3d.Point3d'>, 'control2': <class 'kittycad.models.point3d.Point3d'>, 'end': <class 'kittycad.models.point3d.Point3d'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'relative': <class 'bool'>, 'type': typing.Literal['bezier']}

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[InvalidSchema, 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[InvalidSchema, 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.path_segment'

__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_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'definitions': [{'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94250662434656', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}], 'schema': {'cls': <class 'kittycad.models.path_segment.OptionBezier'>, 'config': {'title': 'OptionBezier'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionBezier'>>]}, 'ref': 'kittycad.models.path_segment.OptionBezier:94250679979232', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'control1': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94250662434656', 'type': 'definition-ref'}, 'type': 'model-field'}, 'control2': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94250662434656', 'type': 'definition-ref'}, 'type': 'model-field'}, 'end': {'metadata': {}, 'schema': {'schema_ref': 'kittycad.models.point3d.Point3d:94250662434656', 'type': 'definition-ref'}, 'type': 'model-field'}, 'relative': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'bezier', 'schema': {'expected': ['bezier'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionBezier', '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__: ClassVar[Dict[str, FieldInfo]] = {'control1': FieldInfo(annotation=Point3d, required=True), 'control2': FieldInfo(annotation=Point3d, required=True), 'end': FieldInfo(annotation=Point3d, required=True), 'relative': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['bezier'], required=False, default='bezier')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__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(             0x000055b8724ccce0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "control2": SerField {                         key_py: Py(                             0x00007fc70b9f5a70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "control1": SerField {                         key_py: Py(                             0x00007fc70b97beb0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "end": SerField {                         key_py: Py(                             0x00007fc71061e648,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Recursive(                                 DefinitionRefSerializer {                                     definition: "...",                                     retry_with_lax_check: true,                                 },                             ),                         ),                         required: true,                     },                     "relative": SerField {                         key_py: Py(                             0x00007fc70ee5ecf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fc710622880,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fc70e4e7780,                                         ),                                     ),                                     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",     }, ), definitions=[Model(ModelSerializer { class: Py(0x55b871411760), serializer: Fields(GeneralFieldsSerializer { fields: {"y": SerField { key_py: Py(0x7fc710624450), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "z": SerField { key_py: Py(0x7fc710624480), alias: None, alias_py: None, serializer: Some(Float(FloatSerializer { inf_nan_mode: Null })), required: true }, "x": SerField { key_py: Py(0x7fc710624420), 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="OptionBezier", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "control1",                         lookup_key: Simple {                             key: "control1",                             py_key: Py(                                 0x00007fc70bafe2f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "control1",                                         Py(                                             0x00007fc70bafd070,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70b97beb0,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "control2",                         lookup_key: Simple {                             key: "control2",                             py_key: Py(                                 0x00007fc70bb15bb0,                             ),                             path: LookupPath(                                 [                                     S(                                         "control2",                                         Py(                                             0x00007fc70bb15970,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70b9f5a70,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "end",                         lookup_key: Simple {                             key: "end",                             py_key: Py(                                 0x00007fc70b9a0ed0,                             ),                             path: LookupPath(                                 [                                     S(                                         "end",                                         Py(                                             0x00007fc70b9a0f00,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc71061e648,                         ),                         validator: DefinitionRef(                             DefinitionRefValidator {                                 definition: "...",                             },                         ),                         frozen: false,                     },                     Field {                         name: "relative",                         lookup_key: Simple {                             key: "relative",                             py_key: Py(                                 0x00007fc70bb15ab0,                             ),                             path: LookupPath(                                 [                                     S(                                         "relative",                                         Py(                                             0x00007fc70b964ef0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70ee5ecf0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fc70b9a0f30,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fc70b9a0f60,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc710622880,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fc70e4e7780,                                     ),                                 ),                                 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,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007fc70b964d80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007fc70e4e7780,                                                 ),                                             ],                                         },                                         expected_repr: "'bezier'",                                         name: "literal['bezier']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['bezier']]",                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionBezier",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055b8724ccce0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fc70e4ea3d0,         ),         name: "OptionBezier",     }, ), definitions=[Model(ModelValidator { revalidate: Never, validator: ModelFields(ModelFieldsValidator { fields: [Field { name: "x", lookup_key: Simple { key: "x", py_key: Py(0x7fc710624420), path: LookupPath([S("x", Py(0x7fc710624420))]) }, name_py: Py(0x7fc710624420), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "y", lookup_key: Simple { key: "y", py_key: Py(0x7fc710624450), path: LookupPath([S("y", Py(0x7fc710624450))]) }, name_py: Py(0x7fc710624450), validator: Float(FloatValidator { strict: false, allow_inf_nan: true }), frozen: false }, Field { name: "z", lookup_key: Simple { key: "z", py_key: Py(0x7fc710624480), path: LookupPath([S("z", Py(0x7fc710624480))]) }, name_py: Py(0x7fc710624480), 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(0x55b871411760), generic_origin: None, post_init: None, frozen: false, custom_init: false, root_model: false, undefined: Py(0x7fc70e4ea3d0), name: "Point3d" })], cache_strings=True)

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

__replace__(**changes)

Return type:

Self

__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_recursion__(object)

Returns the string representation of a recursive object.

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 (*, control1: kittycad.models.point3d.Point3d, control2: kittycad.models.point3d.Point3d, end: kittycad.models.point3d.Point3d, relative: bool, type: Literal['bezier'] = 'bezier') -> 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

control1: Point3d

control2: Point3d

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:

`python {test="skip" lint="skip"} 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]

end: Point3d

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]] = {}

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/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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]] = {'control1': FieldInfo(annotation=Point3d, required=True), 'control2': FieldInfo(annotation=Point3d, required=True), 'end': FieldInfo(annotation=Point3d, required=True), 'relative': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['bezier'], required=False, default='bezier')}

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 (Optional[Mapping[str, Any]]) – 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/2.10/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

relative: 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['bezier']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.path_segment.OptionLine(**data)

A straight line segment. Goes from the current path “pen” to the given endpoint.

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_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__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]', 'end': <class 'kittycad.models.point3d.Point3d'>, 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'relative': <class 'bool'>, 'type': typing.Literal['line']}

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[InvalidSchema, 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[InvalidSchema, 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.path_segment'

__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_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.path_segment.OptionLine'>, 'config': {'title': 'OptionLine'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionLine'>>]}, 'ref': 'kittycad.models.path_segment.OptionLine:94250679756512', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'end': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94250662434656', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'relative': {'metadata': {}, 'schema': {'type': 'bool'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'line', 'schema': {'expected': ['line'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionLine', '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__: ClassVar[Dict[str, FieldInfo]] = {'end': FieldInfo(annotation=Point3d, required=True), 'relative': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['line'], required=False, default='line')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__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(             0x000055b8724966e0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "relative": SerField {                         key_py: Py(                             0x00007fc70ee5ecf0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Bool(                                 BoolSerializer,                             ),                         ),                         required: true,                     },                     "end": SerField {                         key_py: Py(                             0x00007fc71061e648,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055b871411760,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fc710624420,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "z": SerField {                                                     key_py: Py(                                                         0x00007fc710624480,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fc710624450,                                                     ),                                                     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,                     },                     "type": SerField {                         key_py: Py(                             0x00007fc710622880,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fc71061ff18,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "line",                                             },                                             expected_py: None,                                             name: "literal['line']",                                         },                                     ),                                 },                             ),                         ),                         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",     }, ), definitions=[])

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

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionLine", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "end",                         lookup_key: Simple {                             key: "end",                             py_key: Py(                                 0x00007fc70b9a04e0,                             ),                             path: LookupPath(                                 [                                     S(                                         "end",                                         Py(                                             0x00007fc70b9a0510,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc71061e648,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fc710624420,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fc710624420,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710624420,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fc710624450,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fc710624450,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710624450,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "z",                                                 lookup_key: Simple {                                                     key: "z",                                                     py_key: Py(                                                         0x00007fc710624480,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "z",                                                                 Py(                                                                     0x00007fc710624480,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710624480,                                                 ),                                                 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(                                     0x000055b871411760,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                                 name: "Point3d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "relative",                         lookup_key: Simple {                             key: "relative",                             py_key: Py(                                 0x00007fc70b9f61f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "relative",                                         Py(                                             0x00007fc70b9f6230,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70ee5ecf0,                         ),                         validator: Bool(                             BoolValidator {                                 strict: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fc70b9a0540,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fc70b9a0570,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc710622880,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fc71061ff18,                                     ),                                 ),                                 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,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007fc70b9f61c0,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007fc71061ff18,                                                 ),                                             ],                                         },                                         expected_repr: "'line'",                                         name: "literal['line']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['line']]",                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionLine",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055b8724966e0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fc70e4ea3d0,         ),         name: "OptionLine",     }, ), definitions=[], cache_strings=True)

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

__replace__(**changes)

Return type:

Self

__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_recursion__(object)

Returns the string representation of a recursive object.

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 (*, end: kittycad.models.point3d.Point3d, relative: bool, type: Literal['line'] = 'line') -> 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:

`python {test="skip" lint="skip"} 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]

end: Point3d

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]] = {}

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/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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]] = {'end': FieldInfo(annotation=Point3d, required=True), 'relative': FieldInfo(annotation=bool, required=True), 'type': FieldInfo(annotation=Literal['line'], required=False, default='line')}

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 (Optional[Mapping[str, Any]]) – 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/2.10/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

relative: 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['line']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.path_segment.OptionTangentialArc(**data)

Adds a tangent arc from current pen position with the given radius and angle.

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_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__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]]', 'offset': <class 'kittycad.models.angle.Angle'>, 'radius': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': typing.Literal['tangential_arc']}

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[InvalidSchema, 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[InvalidSchema, 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.path_segment'

__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_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.path_segment.OptionTangentialArc'>, 'config': {'title': 'OptionTangentialArc'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionTangentialArc'>>]}, 'ref': 'kittycad.models.path_segment.OptionTangentialArc:94250679691216', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'offset': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.angle.Angle'>, 'config': {'title': 'Angle'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.angle.Angle'>>]}, 'ref': 'kittycad.models.angle.Angle:94250672058048', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'unit': {'metadata': {}, '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:94250676395408', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'value': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Angle', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'radius': {'metadata': {}, 'schema': {'function': {'function': <class 'kittycad.models.length_unit.LengthUnit'>, 'type': 'no-info'}, 'schema': {'type': 'float'}, 'type': 'function-after'}, 'type': 'model-field'}, 'type': {'metadata': {}, 'schema': {'default': 'tangential_arc', 'schema': {'expected': ['tangential_arc'], 'type': 'literal'}, 'type': 'default'}, 'type': 'model-field'}}, 'model_name': 'OptionTangentialArc', '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__: ClassVar[Dict[str, FieldInfo]] = {'offset': FieldInfo(annotation=Angle, required=True), 'radius': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['tangential_arc'], required=False, default='tangential_arc')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__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(             0x000055b8724867d0,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "offset": SerField {                         key_py: Py(                             0x00007fc710620aa0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055b871d3eec0,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "unit": SerField {                                                     key_py: Py(                                                         0x00007fc70ed61a10,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Enum(                                                             EnumSerializer {                                                                 class: Py(                                                                     0x000055b872161d90,                                                                 ),                                                                 serializer: Some(                                                                     Str(                                                                         StrSerializer,                                                                     ),                                                                 ),                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "value": SerField {                                                     key_py: Py(                                                         0x00007fc710622a48,                                                     ),                                                     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,                     },                     "radius": SerField {                         key_py: Py(                             0x00007fc70b9f1260,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Float(                                 FloatSerializer {                                     inf_nan_mode: Null,                                 },                             ),                         ),                         required: true,                     },                     "type": SerField {                         key_py: Py(                             0x00007fc710622880,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fc70b9f5c30,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "tangential_arc",                                             },                                             expected_py: None,                                             name: "literal['tangential_arc']",                                         },                                     ),                                 },                             ),                         ),                         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",     }, ), definitions=[])

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

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionTangentialArc", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "offset",                         lookup_key: Simple {                             key: "offset",                             py_key: Py(                                 0x00007fc70bafbea0,                             ),                             path: LookupPath(                                 [                                     S(                                         "offset",                                         Py(                                             0x00007fc70b9a11d0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc710620aa0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "unit",                                                 lookup_key: Simple {                                                     key: "unit",                                                     py_key: Py(                                                         0x00007fc70bafbed0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "unit",                                                                 Py(                                                                     0x00007fc70bafbf00,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc70ed61a10,                                                 ),                                                 validator: StrEnum(                                                     EnumValidator {                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                         class: Py(                                                             0x000055b872161d90,                                                         ),                                                         lookup: LiteralLookup {                                                             expected_bool: None,                                                             expected_int: None,                                                             expected_str: Some(                                                                 {                                                                     "degrees": 0,                                                                     "radians": 1,                                                                 },                                                             ),                                                             expected_py_dict: None,                                                             expected_py_values: None,                                                             expected_py_primitives: Some(                                                                 Py(                                                                     0x00007fc70b9f4840,                                                                 ),                                                             ),                                                             values: [                                                                 Py(                                                                     0x00007fc70bd734d0,                                                                 ),                                                                 Py(                                                                     0x00007fc70bd73530,                                                                 ),                                                             ],                                                         },                                                         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(                                                         0x00007fc70bafbde0,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "value",                                                                 Py(                                                                     0x00007fc70bafbe70,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710622a48,                                                 ),                                                 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(                                     0x000055b871d3eec0,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                                 name: "Angle",                             },                         ),                         frozen: false,                     },                     Field {                         name: "radius",                         lookup_key: Simple {                             key: "radius",                             py_key: Py(                                 0x00007fc70b9a0e40,                             ),                             path: LookupPath(                                 [                                     S(                                         "radius",                                         Py(                                             0x00007fc70b9a0e70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70b9f1260,                         ),                         validator: FunctionAfter(                             FunctionAfterValidator {                                 validator: Float(                                     FloatValidator {                                         strict: false,                                         allow_inf_nan: true,                                     },                                 ),                                 func: Py(                                     0x000055b87230c5c0,                                 ),                                 config: Py(                                     0x00007fc70b9f5940,                                 ),                                 name: "function-after[LengthUnit(), float]",                                 field_name: None,                                 info_arg: false,                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fc70b9a0e10,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fc70b9a0de0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc710622880,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fc70b9f5c30,                                     ),                                 ),                                 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,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007fc70b9f4b80,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007fc70b9f5c30,                                                 ),                                             ],                                         },                                         expected_repr: "'tangential_arc'",                                         name: "literal['tangential_arc']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['tangential_arc']]",                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionTangentialArc",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055b8724867d0,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fc70e4ea3d0,         ),         name: "OptionTangentialArc",     }, ), definitions=[], cache_strings=True)

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

__replace__(**changes)

Return type:

Self

__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_recursion__(object)

Returns the string representation of a recursive object.

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 (*, offset: kittycad.models.angle.Angle, radius: kittycad.models.length_unit.LengthUnit, type: Literal['tangential_arc'] = 'tangential_arc') -> 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:

`python {test="skip" lint="skip"} 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]] = {}

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/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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]] = {'offset': FieldInfo(annotation=Angle, required=True), 'radius': FieldInfo(annotation=LengthUnit, required=True), 'type': FieldInfo(annotation=Literal['tangential_arc'], required=False, default='tangential_arc')}

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 (Optional[Mapping[str, Any]]) – 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/2.10/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.

offset: Angle

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

type: Literal['tangential_arc']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self

class kittycad.models.path_segment.OptionTangentialArcTo(**data)

Adds a tangent arc from current pen position to the new position. Arcs will choose a clockwise or counter-clockwise direction based on the arc end position.

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_computed_fields__': 'ClassVar[Dict[str, ComputedFieldInfo]]', '__pydantic_core_schema__': 'ClassVar[CoreSchema]', '__pydantic_custom_init__': 'ClassVar[bool]', '__pydantic_decorators__': 'ClassVar[_decorators.DecoratorInfos]', '__pydantic_extra__': 'dict[str, Any] | None', '__pydantic_fields__': 'ClassVar[Dict[str, FieldInfo]]', '__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_snap_increment': typing.Optional[kittycad.models.angle.Angle], 'model_computed_fields': 'ClassVar[dict[str, ComputedFieldInfo]]', 'model_config': 'ClassVar[ConfigDict]', 'model_fields': 'ClassVar[dict[str, FieldInfo]]', 'to': <class 'kittycad.models.point3d.Point3d'>, 'type': typing.Literal['tangential_arc_to']}

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[InvalidSchema, 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[InvalidSchema, 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.path_segment'

__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_computed_fields__: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_core_schema__: ClassVar[CoreSchema] = {'cls': <class 'kittycad.models.path_segment.OptionTangentialArcTo'>, 'config': {'title': 'OptionTangentialArcTo'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.path_segment.OptionTangentialArcTo'>>]}, 'ref': 'kittycad.models.path_segment.OptionTangentialArcTo:94250679705472', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'angle_snap_increment': {'metadata': {}, 'schema': {'default': None, 'schema': {'schema': {'cls': <class 'kittycad.models.angle.Angle'>, 'config': {'title': 'Angle'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.angle.Angle'>>]}, 'ref': 'kittycad.models.angle.Angle:94250672058048', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'unit': {'metadata': {}, '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:94250676395408', 'sub_type': 'str', 'type': 'enum'}, 'type': 'model-field'}, 'value': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Angle', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'nullable'}, 'type': 'default'}, 'type': 'model-field'}, 'to': {'metadata': {}, 'schema': {'cls': <class 'kittycad.models.point3d.Point3d'>, 'config': {'title': 'Point3d'}, 'custom_init': False, 'metadata': {'pydantic_js_functions': [<bound method BaseModel.__get_pydantic_json_schema__ of <class 'kittycad.models.point3d.Point3d'>>]}, 'ref': 'kittycad.models.point3d.Point3d:94250662434656', 'root_model': False, 'schema': {'computed_fields': [], 'fields': {'x': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'y': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}, 'z': {'metadata': {}, 'schema': {'type': 'float'}, 'type': 'model-field'}}, 'model_name': 'Point3d', 'type': 'model-fields'}, 'type': 'model'}, 'type': 'model-field'}, 'type': {'metadata': {}, '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'}

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__: ClassVar[Dict[str, FieldInfo]] = {'angle_snap_increment': FieldInfo(annotation=Union[Angle, NoneType], required=False, default=None), 'to': FieldInfo(annotation=Point3d, required=True), 'type': FieldInfo(annotation=Literal['tangential_arc_to'], required=False, default='tangential_arc_to')}

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects. This replaces Model.__fields__ from Pydantic V1.

__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(             0x000055b872489f80,         ),         serializer: Fields(             GeneralFieldsSerializer {                 fields: {                     "to": SerField {                         key_py: Py(                             0x00007fc70f78b1e0,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             Model(                                 ModelSerializer {                                     class: Py(                                         0x000055b871411760,                                     ),                                     serializer: Fields(                                         GeneralFieldsSerializer {                                             fields: {                                                 "x": SerField {                                                     key_py: Py(                                                         0x00007fc710624420,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "y": SerField {                                                     key_py: Py(                                                         0x00007fc710624450,                                                     ),                                                     alias: None,                                                     alias_py: None,                                                     serializer: Some(                                                         Float(                                                             FloatSerializer {                                                                 inf_nan_mode: Null,                                                             },                                                         ),                                                     ),                                                     required: true,                                                 },                                                 "z": SerField {                                                     key_py: Py(                                                         0x00007fc710624480,                                                     ),                                                     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,                     },                     "type": SerField {                         key_py: Py(                             0x00007fc710622880,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fc70b83d930,                                         ),                                     ),                                     serializer: Literal(                                         LiteralSerializer {                                             expected_int: {},                                             expected_str: {                                                 "tangential_arc_to",                                             },                                             expected_py: None,                                             name: "literal['tangential_arc_to']",                                         },                                     ),                                 },                             ),                         ),                         required: true,                     },                     "angle_snap_increment": SerField {                         key_py: Py(                             0x00007fc70b9f5d70,                         ),                         alias: None,                         alias_py: None,                         serializer: Some(                             WithDefault(                                 WithDefaultSerializer {                                     default: Default(                                         Py(                                             0x00007fc71052d100,                                         ),                                     ),                                     serializer: Nullable(                                         NullableSerializer {                                             serializer: Model(                                                 ModelSerializer {                                                     class: Py(                                                         0x000055b871d3eec0,                                                     ),                                                     serializer: Fields(                                                         GeneralFieldsSerializer {                                                             fields: {                                                                 "value": SerField {                                                                     key_py: Py(                                                                         0x00007fc710622a48,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Float(                                                                             FloatSerializer {                                                                                 inf_nan_mode: Null,                                                                             },                                                                         ),                                                                     ),                                                                     required: true,                                                                 },                                                                 "unit": SerField {                                                                     key_py: Py(                                                                         0x00007fc70ed61a10,                                                                     ),                                                                     alias: None,                                                                     alias_py: None,                                                                     serializer: Some(                                                                         Enum(                                                                             EnumSerializer {                                                                                 class: Py(                                                                                     0x000055b872161d90,                                                                                 ),                                                                                 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,                     },                 },                 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",     }, ), definitions=[])

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

__pydantic_validator__: ClassVar[SchemaValidator | PluggableSchemaValidator] = SchemaValidator(title="OptionTangentialArcTo", validator=Model(     ModelValidator {         revalidate: Never,         validator: ModelFields(             ModelFieldsValidator {                 fields: [                     Field {                         name: "angle_snap_increment",                         lookup_key: Simple {                             key: "angle_snap_increment",                             py_key: Py(                                 0x00007fc70b83cd30,                             ),                             path: LookupPath(                                 [                                     S(                                         "angle_snap_increment",                                         Py(                                             0x00007fc70b83cd70,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70b9f5d70,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fc71052d100,                                     ),                                 ),                                 on_error: Raise,                                 validator: Nullable(                                     NullableValidator {                                         validator: Model(                                             ModelValidator {                                                 revalidate: Never,                                                 validator: ModelFields(                                                     ModelFieldsValidator {                                                         fields: [                                                             Field {                                                                 name: "unit",                                                                 lookup_key: Simple {                                                                     key: "unit",                                                                     py_key: Py(                                                                         0x00007fc70b9a06c0,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "unit",                                                                                 Py(                                                                                     0x00007fc70b9a0690,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fc70ed61a10,                                                                 ),                                                                 validator: StrEnum(                                                                     EnumValidator {                                                                         phantom: PhantomData<_pydantic_core::validators::enum_::StrEnumValidator>,                                                                         class: Py(                                                                             0x000055b872161d90,                                                                         ),                                                                         lookup: LiteralLookup {                                                                             expected_bool: None,                                                                             expected_int: None,                                                                             expected_str: Some(                                                                                 {                                                                                     "degrees": 0,                                                                                     "radians": 1,                                                                                 },                                                                             ),                                                                             expected_py_dict: None,                                                                             expected_py_values: None,                                                                             expected_py_primitives: Some(                                                                                 Py(                                                                                     0x00007fc70b83ce00,                                                                                 ),                                                                             ),                                                                             values: [                                                                                 Py(                                                                                     0x00007fc70bd734d0,                                                                                 ),                                                                                 Py(                                                                                     0x00007fc70bd73530,                                                                                 ),                                                                             ],                                                                         },                                                                         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(                                                                         0x00007fc70b9a0420,                                                                     ),                                                                     path: LookupPath(                                                                         [                                                                             S(                                                                                 "value",                                                                                 Py(                                                                                     0x00007fc70b9a0450,                                                                                 ),                                                                             ),                                                                         ],                                                                     ),                                                                 },                                                                 name_py: Py(                                                                     0x00007fc710622a48,                                                                 ),                                                                 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(                                                     0x000055b871d3eec0,                                                 ),                                                 generic_origin: None,                                                 post_init: None,                                                 frozen: false,                                                 custom_init: false,                                                 root_model: false,                                                 undefined: Py(                                                     0x00007fc70e4ea3d0,                                                 ),                                                 name: "Angle",                                             },                                         ),                                         name: "nullable[Angle]",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[nullable[Angle]]",                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                             },                         ),                         frozen: false,                     },                     Field {                         name: "to",                         lookup_key: Simple {                             key: "to",                             py_key: Py(                                 0x00007fc70b9a03f0,                             ),                             path: LookupPath(                                 [                                     S(                                         "to",                                         Py(                                             0x00007fc70b9a03c0,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc70f78b1e0,                         ),                         validator: Model(                             ModelValidator {                                 revalidate: Never,                                 validator: ModelFields(                                     ModelFieldsValidator {                                         fields: [                                             Field {                                                 name: "x",                                                 lookup_key: Simple {                                                     key: "x",                                                     py_key: Py(                                                         0x00007fc710624420,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "x",                                                                 Py(                                                                     0x00007fc710624420,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710624420,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "y",                                                 lookup_key: Simple {                                                     key: "y",                                                     py_key: Py(                                                         0x00007fc710624450,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "y",                                                                 Py(                                                                     0x00007fc710624450,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710624450,                                                 ),                                                 validator: Float(                                                     FloatValidator {                                                         strict: false,                                                         allow_inf_nan: true,                                                     },                                                 ),                                                 frozen: false,                                             },                                             Field {                                                 name: "z",                                                 lookup_key: Simple {                                                     key: "z",                                                     py_key: Py(                                                         0x00007fc710624480,                                                     ),                                                     path: LookupPath(                                                         [                                                             S(                                                                 "z",                                                                 Py(                                                                     0x00007fc710624480,                                                                 ),                                                             ),                                                         ],                                                     ),                                                 },                                                 name_py: Py(                                                     0x00007fc710624480,                                                 ),                                                 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(                                     0x000055b871411760,                                 ),                                 generic_origin: None,                                 post_init: None,                                 frozen: false,                                 custom_init: false,                                 root_model: false,                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                                 name: "Point3d",                             },                         ),                         frozen: false,                     },                     Field {                         name: "type",                         lookup_key: Simple {                             key: "type",                             py_key: Py(                                 0x00007fc70b9a0390,                             ),                             path: LookupPath(                                 [                                     S(                                         "type",                                         Py(                                             0x00007fc70b9a0480,                                         ),                                     ),                                 ],                             ),                         },                         name_py: Py(                             0x00007fc710622880,                         ),                         validator: WithDefault(                             WithDefaultValidator {                                 default: Default(                                     Py(                                         0x00007fc70b83d930,                                     ),                                 ),                                 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,                                             expected_py_primitives: Some(                                                 Py(                                                     0x00007fc70b83cd00,                                                 ),                                             ),                                             values: [                                                 Py(                                                     0x00007fc70b83d930,                                                 ),                                             ],                                         },                                         expected_repr: "'tangential_arc_to'",                                         name: "literal['tangential_arc_to']",                                     },                                 ),                                 validate_default: false,                                 copy_default: false,                                 name: "default[literal['tangential_arc_to']]",                                 undefined: Py(                                     0x00007fc70e4ea3d0,                                 ),                             },                         ),                         frozen: false,                     },                 ],                 model_name: "OptionTangentialArcTo",                 extra_behavior: Ignore,                 extras_validator: None,                 strict: false,                 from_attributes: false,                 loc_by_alias: true,             },         ),         class: Py(             0x000055b872489f80,         ),         generic_origin: None,         post_init: None,         frozen: false,         custom_init: false,         root_model: false,         undefined: Py(             0x00007fc70e4ea3d0,         ),         name: "OptionTangentialArcTo",     }, ), definitions=[], cache_strings=True)

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

__replace__(**changes)

Return type:

Self

__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_recursion__(object)

Returns the string representation of a recursive object.

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_snap_increment: Optional[kittycad.models.angle.Angle] = None, to: kittycad.models.point3d.Point3d, type: Literal['tangential_arc_to'] = 'tangential_arc_to') -> 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_snap_increment: Optional[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:

`python {test="skip" lint="skip"} 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]] = {}

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/2.10/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

• update (Optional[Mapping[str, Any]]) – 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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/2.10/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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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, bool]], Mapping[str, Union[IncEx, bool]], bool]], Mapping[str, Union[Set[int], Set[str], Mapping[int, Union[IncEx, bool]], Mapping[str, Union[IncEx, bool]], bool]], 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_snap_increment': FieldInfo(annotation=Union[Angle, NoneType], required=False, default=None), 'to': FieldInfo(annotation=Point3d, required=True), 'type': FieldInfo(annotation=Literal['tangential_arc_to'], required=False, default='tangential_arc_to')}

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 (Optional[Mapping[str, Any]]) – 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/2.10/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

to: Point3d

type: Literal['tangential_arc_to']

classmethod update_forward_refs(**localns)

Return type:

None

classmethod validate(value)

Return type:

Self