Module transpiler_mate.ogcapi_records.ogcapi_records_models

Classes

Address

class Address(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Concept

class Concept(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Contact1

class Contact1(
    /,
    **data: 'Any'
)

Identification of, and means of communication with, person responsible

for the resource.

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Contact2

class Contact2(
    /,
    **data: 'Any'
)

Identification of, and means of communication with, person responsible

for the resource.

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Coordinate

class Coordinate(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

Usage Documentation

RootModel and Custom Root Types

A Pydantic BaseModel for the root object of the model.

Attributes

Name	Type	Description	Default
root	None	The root object of the model.	None
pydantic_root_model	None	Whether the model is a RootModel.	None
pydantic_private	None	Private fields in the model.	None
pydantic_extra	None	Extra fields in the model.	None

Ancestors (in MRO)

• pydantic.root_model.RootModel[List[float]]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Coordinate2

class Coordinate2(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

Usage Documentation

RootModel and Custom Root Types

A Pydantic BaseModel for the root object of the model.

Attributes

Name	Type	Description	Default
root	None	The root object of the model.	None
pydantic_root_model	None	Whether the model is a RootModel.	None
pydantic_private	None	Private fields in the model.	None
pydantic_extra	None	Extra fields in the model.	None

Ancestors (in MRO)

• pydantic.root_model.RootModel[List[Coordinate2Item]]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Coordinate2Item

class Coordinate2Item(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

Usage Documentation

RootModel and Custom Root Types

A Pydantic BaseModel for the root object of the model.

Attributes

Name	Type	Description	Default
root	None	The root object of the model.	None
pydantic_root_model	None	Whether the model is a RootModel.	None
pydantic_private	None	Private fields in the model.	None
pydantic_extra	None	Extra fields in the model.	None

Ancestors (in MRO)

• pydantic.root_model.RootModel[List[float]]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Coordinate3

class Coordinate3(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

Usage Documentation

RootModel and Custom Root Types

A Pydantic BaseModel for the root object of the model.

Attributes

Name	Type	Description	Default
root	None	The root object of the model.	None
pydantic_root_model	None	Whether the model is a RootModel.	None
pydantic_private	None	Private fields in the model.	None
pydantic_extra	None	Extra fields in the model.	None

Ancestors (in MRO)

• pydantic.root_model.RootModel[List[Coordinate3Item]]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Coordinate3Item

class Coordinate3Item(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

Usage Documentation

RootModel and Custom Root Types

A Pydantic BaseModel for the root object of the model.

Attributes

Name	Type	Description	Default
root	None	The root object of the model.	None
pydantic_root_model	None	Whether the model is a RootModel.	None
pydantic_private	None	Private fields in the model.	None
pydantic_extra	None	Extra fields in the model.	None

Ancestors (in MRO)

• pydantic.root_model.RootModel[List[float]]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Coordinate4

class Coordinate4(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

Usage Documentation

RootModel and Custom Root Types

A Pydantic BaseModel for the root object of the model.

Attributes

Name	Type	Description	Default
root	None	The root object of the model.	None
pydantic_root_model	None	Whether the model is a RootModel.	None
pydantic_private	None	Private fields in the model.	None
pydantic_extra	None	Extra fields in the model.	None

Ancestors (in MRO)

• pydantic.root_model.RootModel[List[float]]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Dir

class Dir(
    /,
    *args,
    **kwargs
)

The direction for text in this language. The default, ltr (left-to-right), represents the most common situation. However, care should be taken to set the value of dir appropriately if the language direction is not ltr. Other values supported are rtl (right-to-left), ttb (top-to-bottom), and btt (bottom-to-top).

Ancestors (in MRO)

• enum.Enum

Class variables

BTT

LTR

RTL

TTB

name

value

Email

class Email(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

ExternalId

class ExternalId(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Format1

class Format1(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Format2

class Format2(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Geometry

class Geometry(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

NONE_TYPE_NONE

name

value

GeometrycollectionGeoJSON

class GeometrycollectionGeoJSON(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Interval

class Interval(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

Usage Documentation

RootModel and Custom Root Types

A Pydantic BaseModel for the root object of the model.

Attributes

Name	Type	Description	Default
root	None	The root object of the model.	None
pydantic_root_model	None	Whether the model is a RootModel.	None
pydantic_private	None	Private fields in the model.	None
pydantic_extra	None	Extra fields in the model.	None

Ancestors (in MRO)

• pydantic.root_model.RootModel[str]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Interval1

class Interval1(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

Usage Documentation

RootModel and Custom Root Types

A Pydantic BaseModel for the root object of the model.

Attributes

Name	Type	Description	Default
root	None	The root object of the model.	None
pydantic_root_model	None	Whether the model is a RootModel.	None
pydantic_private	None	Private fields in the model.	None
pydantic_extra	None	Extra fields in the model.	None

Ancestors (in MRO)

• pydantic.root_model.RootModel[str]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Interval2

class Interval2(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

FIELD__

name

value

Language

class Language(
    /,
    **data: 'Any'
)

The language used for textual values in this record.

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

LinestringGeoJSON

class LinestringGeoJSON(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Link

class Link(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.ogcapi_records.ogcapi_records_models.LinkBase
• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Descendants

• transpiler_mate.ogcapi_records.ogcapi_records_models.Logo
• transpiler_mate.ogcapi_records.ogcapi_records_models.Logo1

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

LinkBase

class LinkBase(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Descendants

• transpiler_mate.ogcapi_records.ogcapi_records_models.Link
• transpiler_mate.ogcapi_records.ogcapi_records_models.LinkTemplate

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

LinkTemplate

class LinkTemplate(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.ogcapi_records.ogcapi_records_models.LinkBase
• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Logo

class Logo(
    /,
    **data: 'Any'
)

Graphic identifying a contact. The link relation should be icon and the media type should be an image media type.

Ancestors (in MRO)

• transpiler_mate.ogcapi_records.ogcapi_records_models.Link
• transpiler_mate.ogcapi_records.ogcapi_records_models.LinkBase
• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Logo1

class Logo1(
    /,
    **data: 'Any'
)

Graphic identifying a contact. The link relation should be icon and the media type should be an image media type.

Ancestors (in MRO)

• transpiler_mate.ogcapi_records.ogcapi_records_models.Link
• transpiler_mate.ogcapi_records.ogcapi_records_models.LinkBase
• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

MultilinestringGeoJSON

class MultilinestringGeoJSON(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

MultipointGeoJSON

class MultipointGeoJSON(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

MultipolygonGeoJSON

class MultipolygonGeoJSON(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Phone

class Phone(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

PointGeoJSON

class PointGeoJSON(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

PolygonGeoJSON

class PolygonGeoJSON(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

RecordCommonProperties

class RecordCommonProperties(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

RecordGeoJSON

class RecordGeoJSON(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Rel

class Rel(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

ICON

name

value

Roles

class Roles(
    /,
    root: 'RootModelRootType' = PydanticUndefined,
    **data
)

The list of duties, job functions or permissions assigned by the system and associated with the context of this member.

Ancestors (in MRO)

• pydantic.root_model.RootModel[List[str]]
• pydantic.root_model.RootModel
• pydantic.main.BaseModel
• typing.Generic

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    root: 'RootModelRootType',
    _fields_set: 'set[str] | None' = None
) -> 'Self'

Create a new model using the provided root object and update fields set.

Parameters:

Name	Type	Description	Default
root	None	The root object of the model.	None
_fields_set	None	The set of fields to be updated.	None

Returns:

Type	Description
None	The new model.

Raises:

Type	Description
NotImplemented	If the model is not a subclass of RootModel.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal['json', 'python'] | str" = 'python',
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    ensure_ascii: 'bool' = False,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    exclude_computed_fields: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal['none', 'warn', 'error']" = True,
    fallback: 'Callable[[Any], Any] | None' = None,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Theme

class Theme(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Time

class Time(
    /,
    **data: 'Any'
)

Usage Documentation

Models

A base class for creating Pydantic models.

Attributes

Name	Type	Description	Default
class_vars	None	The names of the class variables defined on the model.	None
private_attributes	None	Metadata about the private attributes of the model.	None
signature	None	The synthesized __init__ [Signature][inspect.Signature] of the model.	None
pydantic_complete	None	Whether model building is completed, or if there are still undefined fields.	None
pydantic_core_schema	None	The core schema of the model.	None
pydantic_custom_init	None	Whether the model has a custom __init__ function.	None
pydantic_decorators	None	Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.	None
pydantic_generic_metadata	None	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.	None
pydantic_parent_namespace	None	Parent namespace of the model, used for automatic rebuilding of models.	None
pydantic_post_init	None	The name of the post-init method for the model, if defined.	None
pydantic_root_model	None	Whether the model is a [RootModel][pydantic.root_model.RootModel].	None
pydantic_serializer	None	The pydantic-core SchemaSerializer used to dump instances of the model.	None
pydantic_validator	None	The pydantic-core SchemaValidator used to validate instances of the model.	None
pydantic_fields	None	A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.	None
pydantic_computed_fields	None	A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.	None
pydantic_extra	None	A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to 'allow'.	None
pydantic_fields_set	None	The names of fields explicitly set during instantiation.	None
pydantic_private	None	Values of private attributes set on the model instance.	None

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Class variables

model_computed_fields

model_config

model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Self'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Self'

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:

Name	Type	Description	Default
_fields_set	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.	None
values	None	Trusted or pre-validated data dictionary.	None

Returns:

Type	Description
None	A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation',
    *,
    union_format: "Literal['any_of', 'primitive_type_array']" = 'any_of'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name	Type	Description	Default
by_alias	None	Whether to use attribute aliases or not.	None
ref_template	None	The reference template.	None
union_format	None	The format to use when combining schemas from unions together. Can be one of: - 'any_of': Use the anyOf keyword to combine schemas (the default). - 'primitive_type_array': Use the type keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.	None
schema_generator	None	To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications	None
mode	None	The mode in which to generate the schema.	None

Returns:

Type	Description
None	The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

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

Parameters:

Name	Type	Description	Default
params	None	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.	None

Returns:

Type	Description
None	String representing the new class where params are passed to cls as type variables.

Raises:

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

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'MappingNamespace | None' = None
) -> 'bool | 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:

Name	Type	Description	Default
force	None	Whether to force the rebuilding of the model schema, defaults to False.	None
raise_errors	None	Whether to raise errors, defaults to True.	None
_parent_namespace_depth	None	The depth level of the parent namespace, defaults to 2.	None
_types_namespace	None	The types namespace, defaults to None.	None

Returns:

Type	Description
None	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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Validate a pydantic model instance.

Parameters:

Name	Type	Description	Default
obj	None	The object to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
from_attributes	None	Whether to extract data from object attributes.	None
context	None	Additional context to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated model instance.

Raises:

Type	Description
ValidationError	If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

Usage Documentation

JSON Parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name	Type	Description	Default
json_data	None	The JSON data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

Raises:

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

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    extra: 'ExtraValues | None' = None,
    context: 'Any | None' = None,
    by_alias: 'bool | None' = None,
    by_name: 'bool | None' = None
) -> 'Self'

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

Parameters:

Name	Type	Description	Default
obj	None	The object containing string data to validate.	None
strict	None	Whether to enforce types strictly.	None
extra	None	Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.	None
context	None	Extra variables to pass to the validator.	None
by_alias	None	Whether to use the field's alias when validating against the provided input data.	None
by_name	None	Whether to use the field's name when validating against the provided input data.	None

Returns:

Type	Description
None	The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Self'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Self'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Self'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

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

Methods

copy

def copy(
    self,
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

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

Parameters:

Name	Type	Description	Default
include	None	Optional set or mapping specifying which fields to include in the copied model.	None
exclude	None	Optional set or mapping specifying which fields to exclude in the copied model.	None
update	None	Optional dictionary of field-value pairs to override field values in the copied model.	None
deep	None	If True, the values of fields that are Pydantic models will be deep-copied.	None

Returns:

Type	Description
None	A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx | None' = None,
    exclude: 'IncEx | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self,
    *,
    update: 'Mapping[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Self'

Usage Documentation

model_copy

Returns a copy of the model.

Note

The underlying instance's [__dict__][object.dict] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

Name	Type	Description	Default
update	None	Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.	None
deep	None	Set to True to make a deep copy of the model.	None

Returns:

Type	Description
None	New model instance.

model_dump

def model_dump(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump

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

Parameters:

Name	Type	Description	Default
mode	None	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.	None
include	None	A set of fields to include in the output.	None
exclude	None	A set of fields to exclude from the output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to use the field's alias in the dictionary key if defined.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *args,
    **kwargs
)

Usage Documentation

model_dump_json

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

Parameters:

Name	Type	Description	Default
indent	None	Indentation to use in the JSON output. If None is passed, the output will be compact.	None
ensure_ascii	None	If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.	None
include	None	Field(s) to include in the JSON output.	None
exclude	None	Field(s) to exclude from the JSON output.	None
context	None	Additional context to pass to the serializer.	None
by_alias	None	Whether to serialize using field aliases.	None
exclude_unset	None	Whether to exclude fields that have not been explicitly set.	None
exclude_defaults	None	Whether to exclude fields that are set to their default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
exclude_computed_fields	None	Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.	None
round_trip	None	If True, dumped values should be valid as input for non-idempotent types such as Json[T].	None
warnings	None	How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors, "error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].	None
fallback	None	A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.	None
serialize_as_any	None	Whether to serialize fields with duck-typing serialization behavior.	None

Returns:

Type	Description
None	A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    context: 'Any',
    /
) -> 'None'

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.

Time1

class Time1(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

NONE_TYPE_NONE

name

value

Type

class Type(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

POINT

name

value

Type1

class Type1(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

MULTI_POINT

name

value

Type2

class Type2(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

LINE_STRING

name

value

Type3

class Type3(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

MULTI_LINE_STRING

name

value

Type4

class Type4(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

POLYGON

name

value

Type5

class Type5(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

MULTI_POINT

name

value

Type6

class Type6(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

GEOMETRY_COLLECTION

name

value

Type7

class Type7(
    /,
    *args,
    **kwargs
)

Create a collection of name/value pairs.

Example enumeration:

class Color(Enum): ... RED = 1 ... BLUE = 2 ... GREEN = 3

Access them by:

• attribute access:

Color.RED

• value lookup:

Color(1)

• name lookup:

Color['RED']

Enumerations can be iterated over, and know how many members they have:

len(Color) 3

list(Color) [, , ]

Methods can be added to enumerations, and members can have their own attributes -- see the documentation for details.

Ancestors (in MRO)

• enum.Enum

Class variables

FEATURE

name

value