Module transpiler_mate.datacite.datacite_4_6_models

Classes

Affiliation

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

The organizational or institutional affiliation of the creator.

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.

AlternateIdentifier

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

An identifier other than the primary Identifier applied to the resource being registered.

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.

Contributor

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

The institution or person responsible for collecting, managing, distributing, or otherwise contributing to the development of the resource.

Ancestors (in MRO)

• transpiler_mate.datacite.datacite_4_6_models.Creator
• 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.

ContributorType

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

The type of contributor of the resource

Ancestors (in MRO)

• enum.Enum

Class variables

CONTACT_PERSON

DATA_COLLECTOR

DATA_CURATOR

DATA_MANAGER

DISTRIBUTOR

EDITOR

HOSTING_INSTITUTION

OTHER

PRODUCER

PROJECT_LEADER

PROJECT_MANAGER

PROJECT_MEMBER

REGISTRATION_AGENCY

REGISTRATION_AUTHORITY

RELATED_PERSON

RESEARCHER

RESEARCH_GROUP

RIGHTS_HOLDER

SPONSOR

SUPERVISOR

TRANSLATOR

WORK_PACKAGE_LEADER

name

value

Creator

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

The main researcher involved in producing the data, or the author of the publication.

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Descendants

• transpiler_mate.datacite.datacite_4_6_models.Contributor

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.

Data

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

TODO

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.

DataCiteAttributes

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

DataCite Metadata Schema

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.

DataCiteMetadata46

class DataCiteMetadata46(
    /,
    **data: 'Any'
)

DataCite Metadata Schema

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.

Date

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

Date relevant to the work.

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.

DateType

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

The type of date

Ancestors (in MRO)

• enum.Enum

Class variables

ACCEPTED

AVAILABLE

COLLECTED

COPYRIGHTED

COVERAGE

CREATED

ISSUED

OTHER

SUBMITTED

UPDATED

VALID

WITHDRAWN

name

value

Description

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

All additional information that does not fit in any of the other categories.

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.

DescriptionType

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

The type of the Description.

Ancestors (in MRO)

• enum.Enum

Class variables

ABSTRACT

METHODS

OTHER

SERIES_INFORMATION

TABLE_OF_CONTENTS

TECHNICAL_INFO

name

value

Event

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

Indicates a state-change action for the DOI

Ancestors (in MRO)

• enum.Enum

Class variables

HIDE

PUBLISH

REGISTER

name

value

FunderIdentifierType

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

The type of the funderIdentifier.

Ancestors (in MRO)

• enum.Enum

Class variables

CROSSREF_FUNDER_ID

GRID

ISNI

OTHER

ROR

name

value

FundingReference

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

Information about financial support (funding) for the resource being registered.

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.

GeoLocation

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

Spatial region or named place where the data was gathered or about which the data is focused.

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.

GeoLocationBox

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

The spatial limits of a box.

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.

GeoLocationPoint

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

A point location in space.

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.

GeoLocationPolygon

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

A drawn polygon area, defined by a set of points and lines connecting the points in a closed chain.

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.

Identifier

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

The Identifier is a unique string that identifies a 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.

Model

class Model(
    /,
    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[DataCiteMetadata46]
• 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.

NameIdentifier

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

Uniquely identifies an individual or legal entity, according to various schemes.

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.

NameType

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

The type of name.

Ancestors (in MRO)

• enum.Enum

Class variables

ORGANIZATIONAL

PERSONAL

name

value

NumberType

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

Type of the related item’s number, e.g., report number or article number.

Ancestors (in MRO)

• enum.Enum

Class variables

ARTICLE

CHAPTER

OTHER

REPORT

name

value

PublicationYear1

class PublicationYear1(
    /,
    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.

Publisher

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

The name of the entity that holds, archives, publishes, prints, distributes, releases, issues, or produces the resource. This property will be used to formulate the citation, so consider the prominence of the role.

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.

RelatedIdentifier

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

Identifier of related resources.

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.

RelatedIdentifierType

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

The type of the RelatedIdentifier.

Ancestors (in MRO)

• enum.Enum

Class variables

ARK

AR_XIV

BIBCODE

CSTR

DOI

EAN13

EISSN

HANDLE

IGSN

ISBN

ISSN

ISTC

LISSN

LSID

PMID

PURL

RRID

UPC

URL

URN

W3ID

name

value

RelatedItem

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

Information about a resource related to the one being registered.

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.

RelatedItemContributor

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

An institution or person identified as contributing to the development of the resource.

Ancestors (in MRO)

• transpiler_mate.datacite.datacite_4_6_models.RelatedItemCreator
• 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.

RelatedItemCreator

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

The institution or person responsible for creating the related resource.

Ancestors (in MRO)

• transpiler_mate.TranspilerBaseModel
• pydantic.main.BaseModel

Descendants

• transpiler_mate.datacite.datacite_4_6_models.RelatedItemContributor

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.

RelatedItemIdentifier

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

The identifier for the related item.

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.

RelatedItemTitle

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

Title of the related item.

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.

RelationType

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

Description of the relationship of the resource being registered (A) and the related resource (B).

Ancestors (in MRO)

• enum.Enum

Class variables

CITES

COLLECTS

COMPILES

CONTINUES

DESCRIBES

DOCUMENTS

HAS_METADATA

HAS_PART

HAS_TRANSLATION

HAS_VERSION

IS_CITED_BY

IS_COLLECTED_BY

IS_COMPILED_BY

IS_CONTINUED_BY

IS_DERIVED_FROM

IS_DESCRIBED_BY

IS_DOCUMENTED_BY

IS_IDENTICAL_TO

IS_METADATA_FOR

IS_NEW_VERSION_OF

IS_OBSOLETED_BY

IS_ORIGINAL_FORM_OF

IS_PART_OF

IS_PREVIOUS_VERSION_OF

IS_PUBLISHED_IN

IS_REFERENCED_BY

IS_REQUIRED_BY

IS_REVIEWED_BY

IS_SOURCE_OF

IS_SUPPLEMENTED_BY

IS_SUPPLEMENT_TO

IS_TRANSLATION_OF

IS_VARIANT_FORM_OF

IS_VERSION_OF

OBSOLETES

REFERENCES

REQUIRES

REVIEWS

name

value

ResourceType

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

A description of 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.

ResourceTypeGeneral

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

The general type of a resource.

Ancestors (in MRO)

• enum.Enum

Class variables

AUDIOVISUAL

AWARD

BOOK

BOOK_CHAPTER

COLLECTION

COMPUTATIONAL_NOTEBOOK

CONFERENCE_PAPER

CONFERENCE_PROCEEDING

DATASET

DATA_PAPER

DISSERTATION

EVENT

IMAGE

INSTRUMENT

INTERACTIVE_RESOURCE

JOURNAL

JOURNAL_ARTICLE

MODEL

OTHER

OUTPUT_MANAGEMENT_PLAN

PEER_REVIEW

PHYSICAL_OBJECT

PREPRINT

PROJECT

REPORT

SERVICE

SOFTWARE

SOUND

STANDARD

STUDY_REGISTRATION

TEXT

WORKFLOW

name

value

Right

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

Any right information for this 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.

Subject

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

Subject, keyword, classification code, or key phrase describing 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.

Title

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

A name or title by which a resource is known. May be the title of a dataset or the name of a piece of software or an instrument.

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.

TitleType

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

The type of Title (other than the Main Title).

Ancestors (in MRO)

• enum.Enum

Class variables

ALTERNATIVE_TITLE

OTHER

SUBTITLE

TRANSLATED_TITLE

name

value