Skip to content

Fields

Defining fields on models.

Field

Field(
    default=PydanticUndefined,
    *,
    default_factory=_Unset,
    alias=_Unset,
    alias_priority=_Unset,
    validation_alias=_Unset,
    serialization_alias=_Unset,
    title=_Unset,
    description=_Unset,
    examples=_Unset,
    exclude=_Unset,
    discriminator=_Unset,
    json_schema_extra=_Unset,
    frozen=_Unset,
    validate_default=_Unset,
    repr=_Unset,
    init=_Unset,
    init_var=_Unset,
    kw_only=_Unset,
    pattern=_Unset,
    strict=_Unset,
    gt=_Unset,
    ge=_Unset,
    lt=_Unset,
    le=_Unset,
    multiple_of=_Unset,
    allow_inf_nan=_Unset,
    max_digits=_Unset,
    decimal_places=_Unset,
    min_length=_Unset,
    max_length=_Unset,
    union_mode=_Unset,
    **extra
)

Usage Documentation

Fields

Create a field for objects that can be configured.

Used to provide extra information about a field, either for the model schema or complex validation. Some arguments apply only to number fields (int, float, Decimal) and some apply only to str.

Note
  • Any _Unset objects will be replaced by the corresponding value defined in the _DefaultValues dictionary. If a key for the _Unset object is not found in the _DefaultValues dictionary, it will default to None

Parameters:

Name Type Description Default
default Any

Default value if the field is not set.

PydanticUndefined
default_factory Callable[[], Any] | None

A callable to generate the default value, such as :func:~datetime.utcnow.

_Unset
alias str | None

The name to use for the attribute when validating or serializing by alias. This is often used for things like converting between snake and camel case.

_Unset
alias_priority int | None

Priority of the alias. This affects whether an alias generator is used.

_Unset
validation_alias str | AliasPath | AliasChoices | None

Like alias, but only affects validation, not serialization.

_Unset
serialization_alias str | None

Like alias, but only affects serialization, not validation.

_Unset
title str | None

Human-readable title.

_Unset
description str | None

Human-readable description.

_Unset
examples list[Any] | None

Example values for this field.

_Unset
exclude bool | None

Whether to exclude the field from the model serialization.

_Unset
discriminator str | Discriminator | None

Field name or Discriminator for discriminating the type in a tagged union.

_Unset
json_schema_extra JsonDict | Callable[[JsonDict], None] | None

A dict or callable to provide extra JSON schema properties.

_Unset
frozen bool | None

Whether the field is frozen. If true, attempts to change the value on an instance will raise an error.

_Unset
validate_default bool | None

If True, apply validation to the default value every time you create an instance. Otherwise, for performance reasons, the default value of the field is trusted and not validated.

_Unset
repr bool

A boolean indicating whether to include the field in the __repr__ output.

_Unset
init bool | None

Whether the field should be included in the constructor of the dataclass. (Only applies to dataclasses.)

_Unset
init_var bool | None

Whether the field should only be included in the constructor of the dataclass. (Only applies to dataclasses.)

_Unset
kw_only bool | None

Whether the field should be a keyword-only argument in the constructor of the dataclass. (Only applies to dataclasses.)

_Unset
strict bool | None

If True, strict validation is applied to the field. See Strict Mode for details.

_Unset
gt float | None

Greater than. If set, value must be greater than this. Only applicable to numbers.

_Unset
ge float | None

Greater than or equal. If set, value must be greater than or equal to this. Only applicable to numbers.

_Unset
lt float | None

Less than. If set, value must be less than this. Only applicable to numbers.

_Unset
le float | None

Less than or equal. If set, value must be less than or equal to this. Only applicable to numbers.

_Unset
multiple_of float | None

Value must be a multiple of this. Only applicable to numbers.

_Unset
min_length int | None

Minimum length for strings.

_Unset
max_length int | None

Maximum length for strings.

_Unset
pattern str | None

Pattern for strings (a regular expression).

_Unset
allow_inf_nan bool | None

Allow inf, -inf, nan. Only applicable to numbers.

_Unset
max_digits int | None

Maximum number of allow digits for strings.

_Unset
decimal_places int | None

Maximum number of decimal places allowed for numbers.

_Unset
union_mode Literal['smart', 'left_to_right']

The strategy to apply when validating a union. Can be smart (the default), or left_to_right. See Union Mode for details.

_Unset
extra Unpack[_EmptyKwargs]

(Deprecated) Extra fields that will be included in the JSON schema.

Warning

The extra kwargs is deprecated. Use json_schema_extra instead.

{}

Returns:

Type Description
Any

A new FieldInfo. The return annotation is Any so Field can be used on type-annotated fields without causing a type error.

Source code in pydantic/fields.py
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
def Field(  # noqa: C901
    default: Any = PydanticUndefined,
    *,
    default_factory: typing.Callable[[], Any] | None = _Unset,
    alias: str | None = _Unset,
    alias_priority: int | None = _Unset,
    validation_alias: str | AliasPath | AliasChoices | None = _Unset,
    serialization_alias: str | None = _Unset,
    title: str | None = _Unset,
    description: str | None = _Unset,
    examples: list[Any] | None = _Unset,
    exclude: bool | None = _Unset,
    discriminator: str | types.Discriminator | None = _Unset,
    json_schema_extra: JsonDict | typing.Callable[[JsonDict], None] | None = _Unset,
    frozen: bool | None = _Unset,
    validate_default: bool | None = _Unset,
    repr: bool = _Unset,
    init: bool | None = _Unset,
    init_var: bool | None = _Unset,
    kw_only: bool | None = _Unset,
    pattern: str | None = _Unset,
    strict: bool | None = _Unset,
    gt: float | None = _Unset,
    ge: float | None = _Unset,
    lt: float | None = _Unset,
    le: float | None = _Unset,
    multiple_of: float | None = _Unset,
    allow_inf_nan: bool | None = _Unset,
    max_digits: int | None = _Unset,
    decimal_places: int | None = _Unset,
    min_length: int | None = _Unset,
    max_length: int | None = _Unset,
    union_mode: Literal['smart', 'left_to_right'] = _Unset,
    **extra: Unpack[_EmptyKwargs],
) -> Any:
    """Usage docs: https://docs.pydantic.dev/2.6/concepts/fields

    Create a field for objects that can be configured.

    Used to provide extra information about a field, either for the model schema or complex validation. Some arguments
    apply only to number fields (`int`, `float`, `Decimal`) and some apply only to `str`.

    Note:
        - Any `_Unset` objects will be replaced by the corresponding value defined in the `_DefaultValues` dictionary. If a key for the `_Unset` object is not found in the `_DefaultValues` dictionary, it will default to `None`

    Args:
        default: Default value if the field is not set.
        default_factory: A callable to generate the default value, such as :func:`~datetime.utcnow`.
        alias: The name to use for the attribute when validating or serializing by alias.
            This is often used for things like converting between snake and camel case.
        alias_priority: Priority of the alias. This affects whether an alias generator is used.
        validation_alias: Like `alias`, but only affects validation, not serialization.
        serialization_alias: Like `alias`, but only affects serialization, not validation.
        title: Human-readable title.
        description: Human-readable description.
        examples: Example values for this field.
        exclude: Whether to exclude the field from the model serialization.
        discriminator: Field name or Discriminator for discriminating the type in a tagged union.
        json_schema_extra: A dict or callable to provide extra JSON schema properties.
        frozen: Whether the field is frozen. If true, attempts to change the value on an instance will raise an error.
        validate_default: If `True`, apply validation to the default value every time you create an instance.
            Otherwise, for performance reasons, the default value of the field is trusted and not validated.
        repr: A boolean indicating whether to include the field in the `__repr__` output.
        init: Whether the field should be included in the constructor of the dataclass.
            (Only applies to dataclasses.)
        init_var: Whether the field should _only_ be included in the constructor of the dataclass.
            (Only applies to dataclasses.)
        kw_only: Whether the field should be a keyword-only argument in the constructor of the dataclass.
            (Only applies to dataclasses.)
        strict: If `True`, strict validation is applied to the field.
            See [Strict Mode](../concepts/strict_mode.md) for details.
        gt: Greater than. If set, value must be greater than this. Only applicable to numbers.
        ge: Greater than or equal. If set, value must be greater than or equal to this. Only applicable to numbers.
        lt: Less than. If set, value must be less than this. Only applicable to numbers.
        le: Less than or equal. If set, value must be less than or equal to this. Only applicable to numbers.
        multiple_of: Value must be a multiple of this. Only applicable to numbers.
        min_length: Minimum length for strings.
        max_length: Maximum length for strings.
        pattern: Pattern for strings (a regular expression).
        allow_inf_nan: Allow `inf`, `-inf`, `nan`. Only applicable to numbers.
        max_digits: Maximum number of allow digits for strings.
        decimal_places: Maximum number of decimal places allowed for numbers.
        union_mode: The strategy to apply when validating a union. Can be `smart` (the default), or `left_to_right`.
            See [Union Mode](standard_library_types.md#union-mode) for details.
        extra: (Deprecated) Extra fields that will be included in the JSON schema.

            !!! warning Deprecated
                The `extra` kwargs is deprecated. Use `json_schema_extra` instead.

    Returns:
        A new [`FieldInfo`][pydantic.fields.FieldInfo]. The return annotation is `Any` so `Field` can be used on
            type-annotated fields without causing a type error.
    """
    # Check deprecated and removed params from V1. This logic should eventually be removed.
    const = extra.pop('const', None)  # type: ignore
    if const is not None:
        raise PydanticUserError('`const` is removed, use `Literal` instead', code='removed-kwargs')

    min_items = extra.pop('min_items', None)  # type: ignore
    if min_items is not None:
        warn('`min_items` is deprecated and will be removed, use `min_length` instead', DeprecationWarning)
        if min_length in (None, _Unset):
            min_length = min_items  # type: ignore

    max_items = extra.pop('max_items', None)  # type: ignore
    if max_items is not None:
        warn('`max_items` is deprecated and will be removed, use `max_length` instead', DeprecationWarning)
        if max_length in (None, _Unset):
            max_length = max_items  # type: ignore

    unique_items = extra.pop('unique_items', None)  # type: ignore
    if unique_items is not None:
        raise PydanticUserError(
            (
                '`unique_items` is removed, use `Set` instead'
                '(this feature is discussed in https://github.com/pydantic/pydantic-core/issues/296)'
            ),
            code='removed-kwargs',
        )

    allow_mutation = extra.pop('allow_mutation', None)  # type: ignore
    if allow_mutation is not None:
        warn('`allow_mutation` is deprecated and will be removed. use `frozen` instead', DeprecationWarning)
        if allow_mutation is False:
            frozen = True

    regex = extra.pop('regex', None)  # type: ignore
    if regex is not None:
        raise PydanticUserError('`regex` is removed. use `pattern` instead', code='removed-kwargs')

    if extra:
        warn(
            'Using extra keyword arguments on `Field` is deprecated and will be removed.'
            ' Use `json_schema_extra` instead.'
            f' (Extra keys: {", ".join(k.__repr__() for k in extra.keys())})',
            DeprecationWarning,
        )
        if not json_schema_extra or json_schema_extra is _Unset:
            json_schema_extra = extra  # type: ignore

    if (
        validation_alias
        and validation_alias is not _Unset
        and not isinstance(validation_alias, (str, AliasChoices, AliasPath))
    ):
        raise TypeError('Invalid `validation_alias` type. it should be `str`, `AliasChoices`, or `AliasPath`')

    if serialization_alias in (_Unset, None) and isinstance(alias, str):
        serialization_alias = alias

    if validation_alias in (_Unset, None):
        validation_alias = alias

    include = extra.pop('include', None)  # type: ignore
    if include is not None:
        warn('`include` is deprecated and does nothing. It will be removed, use `exclude` instead', DeprecationWarning)

    return FieldInfo.from_field(
        default,
        default_factory=default_factory,
        alias=alias,
        alias_priority=alias_priority,
        validation_alias=validation_alias,
        serialization_alias=serialization_alias,
        title=title,
        description=description,
        examples=examples,
        exclude=exclude,
        discriminator=discriminator,
        json_schema_extra=json_schema_extra,
        frozen=frozen,
        pattern=pattern,
        validate_default=validate_default,
        repr=repr,
        init=init,
        init_var=init_var,
        kw_only=kw_only,
        strict=strict,
        gt=gt,
        ge=ge,
        lt=lt,
        le=le,
        multiple_of=multiple_of,
        min_length=min_length,
        max_length=max_length,
        allow_inf_nan=allow_inf_nan,
        max_digits=max_digits,
        decimal_places=decimal_places,
        union_mode=union_mode,
    )

FieldInfo

FieldInfo(**kwargs)

Bases: Representation

This class holds information about a field.

FieldInfo is used for any field definition regardless of whether the Field() function is explicitly used.

Warning

You generally shouldn't be creating FieldInfo directly, you'll only need to use it when accessing BaseModel .model_fields internals.

Attributes:

Name Type Description
annotation type[Any] | None

The type annotation of the field.

default Any

The default value of the field.

default_factory Callable[[], Any] | None

The factory function used to construct the default for the field.

alias str | None

The alias name of the field.

alias_priority int | None

The priority of the field's alias.

validation_alias str | AliasPath | AliasChoices | None

The validation alias of the field.

serialization_alias str | None

The serialization alias of the field.

title str | None

The title of the field.

description str | None

The description of the field.

examples list[Any] | None

List of examples of the field.

exclude bool | None

Whether to exclude the field from the model serialization.

discriminator str | Discriminator | None

Field name or Discriminator for discriminating the type in a tagged union.

json_schema_extra JsonDict | Callable[[JsonDict], None] | None

A dict or callable to provide extra JSON schema properties.

frozen bool | None

Whether the field is frozen.

validate_default bool | None

Whether to validate the default value of the field.

repr bool

Whether to include the field in representation of the model.

init bool | None

Whether the field should be included in the constructor of the dataclass.

init_var bool | None

Whether the field should only be included in the constructor of the dataclass, and not stored.

kw_only bool | None

Whether the field should be a keyword-only argument in the constructor of the dataclass.

metadata list[Any]

List of metadata constraints.

See the signature of pydantic.fields.Field for more details about the expected arguments.

Source code in pydantic/fields.py
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
def __init__(self, **kwargs: Unpack[_FieldInfoInputs]) -> None:
    """This class should generally not be initialized directly; instead, use the `pydantic.fields.Field` function
    or one of the constructor classmethods.

    See the signature of `pydantic.fields.Field` for more details about the expected arguments.
    """
    self._attributes_set = {k: v for k, v in kwargs.items() if v is not _Unset}
    kwargs = {k: _DefaultValues.get(k) if v is _Unset else v for k, v in kwargs.items()}  # type: ignore
    self.annotation, annotation_metadata = self._extract_metadata(kwargs.get('annotation'))

    default = kwargs.pop('default', PydanticUndefined)
    if default is Ellipsis:
        self.default = PydanticUndefined
    else:
        self.default = default

    self.default_factory = kwargs.pop('default_factory', None)

    if self.default is not PydanticUndefined and self.default_factory is not None:
        raise TypeError('cannot specify both default and default_factory')

    self.title = kwargs.pop('title', None)
    self.alias = kwargs.pop('alias', None)
    self.validation_alias = kwargs.pop('validation_alias', None)
    self.serialization_alias = kwargs.pop('serialization_alias', None)
    alias_is_set = any(alias is not None for alias in (self.alias, self.validation_alias, self.serialization_alias))
    self.alias_priority = kwargs.pop('alias_priority', None) or 2 if alias_is_set else None
    self.description = kwargs.pop('description', None)
    self.examples = kwargs.pop('examples', None)
    self.exclude = kwargs.pop('exclude', None)
    self.discriminator = kwargs.pop('discriminator', None)
    self.repr = kwargs.pop('repr', True)
    self.json_schema_extra = kwargs.pop('json_schema_extra', None)
    self.validate_default = kwargs.pop('validate_default', None)
    self.frozen = kwargs.pop('frozen', None)
    # currently only used on dataclasses
    self.init = kwargs.pop('init', None)
    self.init_var = kwargs.pop('init_var', None)
    self.kw_only = kwargs.pop('kw_only', None)

    self.metadata = self._collect_metadata(kwargs) + annotation_metadata  # type: ignore

from_field staticmethod

from_field(default=PydanticUndefined, **kwargs)

Create a new FieldInfo object with the Field function.

Parameters:

Name Type Description Default
default Any

The default value for the field. Defaults to Undefined.

PydanticUndefined
**kwargs Unpack[_FromFieldInfoInputs]

Additional arguments dictionary.

{}

Raises:

Type Description
TypeError

If 'annotation' is passed as a keyword argument.

Returns:

Type Description
FieldInfo

A new FieldInfo object with the given parameters.

Example

This is how you can create a field with default value like this:

import pydantic

class MyModel(pydantic.BaseModel):
    foo: int = pydantic.Field(4)
Source code in pydantic/fields.py
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
@staticmethod
def from_field(default: Any = PydanticUndefined, **kwargs: Unpack[_FromFieldInfoInputs]) -> FieldInfo:
    """Create a new `FieldInfo` object with the `Field` function.

    Args:
        default: The default value for the field. Defaults to Undefined.
        **kwargs: Additional arguments dictionary.

    Raises:
        TypeError: If 'annotation' is passed as a keyword argument.

    Returns:
        A new FieldInfo object with the given parameters.

    Example:
        This is how you can create a field with default value like this:

        ```python
        import pydantic

        class MyModel(pydantic.BaseModel):
            foo: int = pydantic.Field(4)
        ```
    """
    if 'annotation' in kwargs:
        raise TypeError('"annotation" is not permitted as a Field keyword argument')
    return FieldInfo(default=default, **kwargs)

from_annotation staticmethod

from_annotation(annotation)

Creates a FieldInfo instance from a bare annotation.

This function is used internally to create a FieldInfo from a bare annotation like this:

import pydantic

class MyModel(pydantic.BaseModel):
    foo: int  # <-- like this

We also account for the case where the annotation can be an instance of Annotated and where one of the (not first) arguments in Annotated is an instance of FieldInfo, e.g.:

import annotated_types
from typing_extensions import Annotated

import pydantic

class MyModel(pydantic.BaseModel):
    foo: Annotated[int, annotated_types.Gt(42)]
    bar: Annotated[int, pydantic.Field(gt=42)]

Parameters:

Name Type Description Default
annotation type[Any]

An annotation object.

required

Returns:

Type Description
FieldInfo

An instance of the field metadata.

Source code in pydantic/fields.py
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
@staticmethod
def from_annotation(annotation: type[Any]) -> FieldInfo:
    """Creates a `FieldInfo` instance from a bare annotation.

    This function is used internally to create a `FieldInfo` from a bare annotation like this:

    ```python
    import pydantic

    class MyModel(pydantic.BaseModel):
        foo: int  # <-- like this
    ```

    We also account for the case where the annotation can be an instance of `Annotated` and where
    one of the (not first) arguments in `Annotated` is an instance of `FieldInfo`, e.g.:

    ```python
    import annotated_types
    from typing_extensions import Annotated

    import pydantic

    class MyModel(pydantic.BaseModel):
        foo: Annotated[int, annotated_types.Gt(42)]
        bar: Annotated[int, pydantic.Field(gt=42)]
    ```

    Args:
        annotation: An annotation object.

    Returns:
        An instance of the field metadata.
    """
    final = False
    if _typing_extra.is_finalvar(annotation):
        final = True
        if annotation is not typing_extensions.Final:
            annotation = typing_extensions.get_args(annotation)[0]

    if _typing_extra.is_annotated(annotation):
        first_arg, *extra_args = typing_extensions.get_args(annotation)
        if _typing_extra.is_finalvar(first_arg):
            final = True
        field_info_annotations = [a for a in extra_args if isinstance(a, FieldInfo)]
        field_info = FieldInfo.merge_field_infos(*field_info_annotations, annotation=first_arg)
        if field_info:
            new_field_info = copy(field_info)
            new_field_info.annotation = first_arg
            new_field_info.frozen = final or field_info.frozen
            metadata: list[Any] = []
            for a in extra_args:
                if not isinstance(a, FieldInfo):
                    metadata.append(a)
                else:
                    metadata.extend(a.metadata)
            new_field_info.metadata = metadata
            return new_field_info

    return FieldInfo(annotation=annotation, frozen=final or None)

from_annotated_attribute staticmethod

from_annotated_attribute(annotation, default)

Create FieldInfo from an annotation with a default value.

This is used in cases like the following:

import annotated_types
from typing_extensions import Annotated

import pydantic

class MyModel(pydantic.BaseModel):
    foo: int = 4  # <-- like this
    bar: Annotated[int, annotated_types.Gt(4)] = 4  # <-- or this
    spam: Annotated[int, pydantic.Field(gt=4)] = 4  # <-- or this

Parameters:

Name Type Description Default
annotation type[Any]

The type annotation of the field.

required
default Any

The default value of the field.

required

Returns:

Type Description
FieldInfo

A field object with the passed values.

Source code in pydantic/fields.py
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
@staticmethod
def from_annotated_attribute(annotation: type[Any], default: Any) -> FieldInfo:
    """Create `FieldInfo` from an annotation with a default value.

    This is used in cases like the following:

    ```python
    import annotated_types
    from typing_extensions import Annotated

    import pydantic

    class MyModel(pydantic.BaseModel):
        foo: int = 4  # <-- like this
        bar: Annotated[int, annotated_types.Gt(4)] = 4  # <-- or this
        spam: Annotated[int, pydantic.Field(gt=4)] = 4  # <-- or this
    ```

    Args:
        annotation: The type annotation of the field.
        default: The default value of the field.

    Returns:
        A field object with the passed values.
    """
    if annotation is default:
        raise PydanticUserError(
            'Error when building FieldInfo from annotated attribute. '
            "Make sure you don't have any field name clashing with a type annotation ",
            code='unevaluable-type-annotation',
        )

    final = False
    if _typing_extra.is_finalvar(annotation):
        final = True
        if annotation is not typing_extensions.Final:
            annotation = typing_extensions.get_args(annotation)[0]

    if isinstance(default, FieldInfo):
        default.annotation, annotation_metadata = FieldInfo._extract_metadata(annotation)
        default.metadata += annotation_metadata
        default = default.merge_field_infos(
            *[x for x in annotation_metadata if isinstance(x, FieldInfo)], default, annotation=default.annotation
        )
        default.frozen = final or default.frozen
        return default
    elif isinstance(default, dataclasses.Field):
        init_var = False
        if annotation is dataclasses.InitVar:
            init_var = True
            annotation = Any
        elif isinstance(annotation, dataclasses.InitVar):
            init_var = True
            annotation = annotation.type
        pydantic_field = FieldInfo._from_dataclass_field(default)
        pydantic_field.annotation, annotation_metadata = FieldInfo._extract_metadata(annotation)
        pydantic_field.metadata += annotation_metadata
        pydantic_field = pydantic_field.merge_field_infos(
            *[x for x in annotation_metadata if isinstance(x, FieldInfo)],
            pydantic_field,
            annotation=pydantic_field.annotation,
        )
        pydantic_field.frozen = final or pydantic_field.frozen
        pydantic_field.init_var = init_var
        pydantic_field.init = getattr(default, 'init', None)
        pydantic_field.kw_only = getattr(default, 'kw_only', None)
        return pydantic_field
    else:
        if _typing_extra.is_annotated(annotation):
            first_arg, *extra_args = typing_extensions.get_args(annotation)
            field_infos = [a for a in extra_args if isinstance(a, FieldInfo)]
            field_info = FieldInfo.merge_field_infos(*field_infos, annotation=first_arg, default=default)
            metadata: list[Any] = []
            for a in extra_args:
                if not isinstance(a, FieldInfo):
                    metadata.append(a)
                else:
                    metadata.extend(a.metadata)
            field_info.metadata = metadata
            return field_info

        return FieldInfo(annotation=annotation, default=default, frozen=final or None)

merge_field_infos staticmethod

merge_field_infos(*field_infos, **overrides)

Merge FieldInfo instances keeping only explicitly set attributes.

Later FieldInfo instances override earlier ones.

Returns:

Name Type Description
FieldInfo FieldInfo

A merged FieldInfo instance.

Source code in pydantic/fields.py
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
@staticmethod
def merge_field_infos(*field_infos: FieldInfo, **overrides: Any) -> FieldInfo:
    """Merge `FieldInfo` instances keeping only explicitly set attributes.

    Later `FieldInfo` instances override earlier ones.

    Returns:
        FieldInfo: A merged FieldInfo instance.
    """
    flattened_field_infos: list[FieldInfo] = []
    for field_info in field_infos:
        flattened_field_infos.extend(x for x in field_info.metadata if isinstance(x, FieldInfo))
        flattened_field_infos.append(field_info)
    field_infos = tuple(flattened_field_infos)
    if len(field_infos) == 1:
        # No merging necessary, but we still need to make a copy and apply the overrides
        field_info = copy(field_infos[0])
        field_info._attributes_set.update(overrides)
        for k, v in overrides.items():
            setattr(field_info, k, v)
        return field_info  # type: ignore

    new_kwargs: dict[str, Any] = {}
    metadata = {}
    for field_info in field_infos:
        new_kwargs.update(field_info._attributes_set)
        for x in field_info.metadata:
            if not isinstance(x, FieldInfo):
                metadata[type(x)] = x
    new_kwargs.update(overrides)
    field_info = FieldInfo(**new_kwargs)
    field_info.metadata = list(metadata.values())
    return field_info

get_default

get_default(*, call_default_factory=False)

Get the default value.

We expose an option for whether to call the default_factory (if present), as calling it may result in side effects that we want to avoid. However, there are times when it really should be called (namely, when instantiating a model via model_construct).

Parameters:

Name Type Description Default
call_default_factory bool

Whether to call the default_factory or not. Defaults to False.

False

Returns:

Type Description
Any

The default value, calling the default factory if requested or None if not set.

Source code in pydantic/fields.py
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
def get_default(self, *, call_default_factory: bool = False) -> Any:
    """Get the default value.

    We expose an option for whether to call the default_factory (if present), as calling it may
    result in side effects that we want to avoid. However, there are times when it really should
    be called (namely, when instantiating a model via `model_construct`).

    Args:
        call_default_factory: Whether to call the default_factory or not. Defaults to `False`.

    Returns:
        The default value, calling the default factory if requested or `None` if not set.
    """
    if self.default_factory is None:
        return _utils.smart_deepcopy(self.default)
    elif call_default_factory:
        return self.default_factory()
    else:
        return None

is_required

is_required()

Check if the field is required (i.e., does not have a default value or factory).

Returns:

Type Description
bool

True if the field is required, False otherwise.

Source code in pydantic/fields.py
513
514
515
516
517
518
519
def is_required(self) -> bool:
    """Check if the field is required (i.e., does not have a default value or factory).

    Returns:
        `True` if the field is required, `False` otherwise.
    """
    return self.default is PydanticUndefined and self.default_factory is None

rebuild_annotation

rebuild_annotation()

Attempts to rebuild the original annotation for use in function signatures.

If metadata is present, it adds it to the original annotation using Annotated. Otherwise, it returns the original annotation as-is.

Note that because the metadata has been flattened, the original annotation may not be reconstructed exactly as originally provided, e.g. if the original type had unrecognized annotations, or was annotated with a call to pydantic.Field.

Returns:

Type Description
Any

The rebuilt annotation.

Source code in pydantic/fields.py
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
def rebuild_annotation(self) -> Any:
    """Attempts to rebuild the original annotation for use in function signatures.

    If metadata is present, it adds it to the original annotation using
    `Annotated`. Otherwise, it returns the original annotation as-is.

    Note that because the metadata has been flattened, the original annotation
    may not be reconstructed exactly as originally provided, e.g. if the original
    type had unrecognized annotations, or was annotated with a call to `pydantic.Field`.

    Returns:
        The rebuilt annotation.
    """
    if not self.metadata:
        return self.annotation
    else:
        # Annotated arguments must be a tuple
        return typing_extensions.Annotated[(self.annotation, *self.metadata)]  # type: ignore

apply_typevars_map

apply_typevars_map(typevars_map, types_namespace)

Apply a typevars_map to the annotation.

This method is used when analyzing parametrized generic types to replace typevars with their concrete types.

This method applies the typevars_map to the annotation in place.

Parameters:

Name Type Description Default
typevars_map dict[Any, Any] | None

A dictionary mapping type variables to their concrete types.

required
types_namespace dict | None

A dictionary containing related types to the annotated type.

required
See Also

pydantic._internal._generics.replace_types is used for replacing the typevars with their concrete types.

Source code in pydantic/fields.py
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
def apply_typevars_map(self, typevars_map: dict[Any, Any] | None, types_namespace: dict[str, Any] | None) -> None:
    """Apply a `typevars_map` to the annotation.

    This method is used when analyzing parametrized generic types to replace typevars with their concrete types.

    This method applies the `typevars_map` to the annotation in place.

    Args:
        typevars_map: A dictionary mapping type variables to their concrete types.
        types_namespace (dict | None): A dictionary containing related types to the annotated type.

    See Also:
        pydantic._internal._generics.replace_types is used for replacing the typevars with
            their concrete types.
    """
    annotation = _typing_extra.eval_type_lenient(self.annotation, types_namespace)
    self.annotation = _generics.replace_types(annotation, typevars_map)

PrivateAttr

PrivateAttr(
    default=PydanticUndefined, *, default_factory=None
)

Usage Documentation

Private model attributes

Indicates that an attribute is intended for private use and not handled during normal validation/serialization.

Private attributes are not validated by Pydantic, so it's up to you to ensure they are used in a type-safe manner.

Private attributes are stored in __private_attributes__ on the model.

Parameters:

Name Type Description Default
default Any

The attribute's default value. Defaults to Undefined.

PydanticUndefined
default_factory Callable[[], Any] | None

Callable that will be called when a default value is needed for this attribute. If both default and default_factory are set, an error will be raised.

None

Returns:

Type Description
Any

An instance of ModelPrivateAttr class.

Raises:

Type Description
ValueError

If both default and default_factory are set.

Source code in pydantic/fields.py
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
def PrivateAttr(
    default: Any = PydanticUndefined,
    *,
    default_factory: typing.Callable[[], Any] | None = None,
) -> Any:
    """Usage docs: https://docs.pydantic.dev/2.6/concepts/models/#private-model-attributes

    Indicates that an attribute is intended for private use and not handled during normal validation/serialization.

    Private attributes are not validated by Pydantic, so it's up to you to ensure they are used in a type-safe manner.

    Private attributes are stored in `__private_attributes__` on the model.

    Args:
        default: The attribute's default value. Defaults to Undefined.
        default_factory: Callable that will be
            called when a default value is needed for this attribute.
            If both `default` and `default_factory` are set, an error will be raised.

    Returns:
        An instance of [`ModelPrivateAttr`][pydantic.fields.ModelPrivateAttr] class.

    Raises:
        ValueError: If both `default` and `default_factory` are set.
    """
    if default is not PydanticUndefined and default_factory is not None:
        raise TypeError('cannot specify both default and default_factory')

    return ModelPrivateAttr(
        default,
        default_factory=default_factory,
    )

ModelPrivateAttr

ModelPrivateAttr(
    default=PydanticUndefined, *, default_factory=None
)

Bases: Representation

A descriptor for private attributes in class models.

Warning

You generally shouldn't be creating ModelPrivateAttr instances directly, instead use pydantic.fields.PrivateAttr. (This is similar to FieldInfo vs. Field.)

Attributes:

Name Type Description
default

The default value of the attribute if not provided.

default_factory

A callable function that generates the default value of the attribute if not provided.

Source code in pydantic/fields.py
834
835
836
837
838
def __init__(
    self, default: Any = PydanticUndefined, *, default_factory: typing.Callable[[], Any] | None = None
) -> None:
    self.default = default
    self.default_factory = default_factory

get_default

get_default()

Retrieve the default value of the object.

If self.default_factory is None, the method will return a deep copy of the self.default object.

If self.default_factory is not None, it will call self.default_factory and return the value returned.

Returns:

Type Description
Any

The default value of the object.

Source code in pydantic/fields.py
862
863
864
865
866
867
868
869
870
871
872
def get_default(self) -> Any:
    """Retrieve the default value of the object.

    If `self.default_factory` is `None`, the method will return a deep copy of the `self.default` object.

    If `self.default_factory` is not `None`, it will call `self.default_factory` and return the value returned.

    Returns:
        The default value of the object.
    """
    return _utils.smart_deepcopy(self.default) if self.default_factory is None else self.default_factory()

computed_field

computed_field(
    __f=None,
    *,
    alias=None,
    alias_priority=None,
    title=None,
    description=None,
    examples=None,
    json_schema_extra=None,
    repr=None,
    return_type=PydanticUndefined
)

Usage Documentation

The computed_field decorator

Decorator to include property and cached_property when serializing models or dataclasses.

This is useful for fields that are computed from other fields, or for fields that are expensive to compute and should be cached.

from pydantic import BaseModel, computed_field

class Rectangle(BaseModel):
    width: int
    length: int

    @computed_field
    @property
    def area(self) -> int:
        return self.width * self.length

print(Rectangle(width=3, length=2).model_dump())
#> {'width': 3, 'length': 2, 'area': 6}

If applied to functions not yet decorated with @property or @cached_property, the function is automatically wrapped with property. Although this is more concise, you will lose IntelliSense in your IDE, and confuse static type checkers, thus explicit use of @property is recommended.

Mypy Warning

Even with the @property or @cached_property applied to your function before @computed_field, mypy may throw a Decorated property not supported error. See mypy issue #1362, for more information. To avoid this error message, add # type: ignore[misc] to the @computed_field line.

pyright supports @computed_field without error.

import random

from pydantic import BaseModel, computed_field

class Square(BaseModel):
    width: float

    @computed_field
    def area(self) -> float:  # converted to a `property` by `computed_field`
        return round(self.width**2, 2)

    @area.setter
    def area(self, new_area: float) -> None:
        self.width = new_area**0.5

    @computed_field(alias='the magic number', repr=False)
    def random_number(self) -> int:
        return random.randint(0, 1_000)

square = Square(width=1.3)

# `random_number` does not appear in representation
print(repr(square))
#> Square(width=1.3, area=1.69)

print(square.random_number)
#> 3

square.area = 4

print(square.model_dump_json(by_alias=True))
#> {"width":2.0,"area":4.0,"the magic number":3}

Overriding with computed_field

You can't override a field from a parent class with a computed_field in the child class. mypy complains about this behavior if allowed, and dataclasses doesn't allow this pattern either. See the example below:

from pydantic import BaseModel, computed_field

class Parent(BaseModel):
    a: str

try:

    class Child(Parent):
        @computed_field
        @property
        def a(self) -> str:
            return 'new a'

except ValueError as e:
    print(repr(e))
    #> ValueError("you can't override a field with a computed field")

Private properties decorated with @computed_field have repr=False by default.

from functools import cached_property

from pydantic import BaseModel, computed_field

class Model(BaseModel):
    foo: int

    @computed_field
    @cached_property
    def _private_cached_property(self) -> int:
        return -self.foo

    @computed_field
    @property
    def _private_property(self) -> int:
        return -self.foo

m = Model(foo=1)
print(repr(m))
#> M(foo=1)

Parameters:

Name Type Description Default
__f PropertyT | None

the function to wrap.

None
alias str | None

alias to use when serializing this computed field, only used when by_alias=True

None
alias_priority int | None

priority of the alias. This affects whether an alias generator is used

None
title str | None

Title to use when including this computed field in JSON Schema

None
description str | None

Description to use when including this computed field in JSON Schema, defaults to the function's docstring

None
examples list[Any] | None

Example values to use when including this computed field in JSON Schema

None
json_schema_extra JsonDict | Callable[[JsonDict], None] | None

A dict or callable to provide extra JSON schema properties.

None
repr bool | None

whether to include this computed field in model repr. Default is False for private properties and True for public properties.

None
return_type Any

optional return for serialization logic to expect when serializing to JSON, if included this must be correct, otherwise a TypeError is raised. If you don't include a return type Any is used, which does runtime introspection to handle arbitrary objects.

PydanticUndefined

Returns:

Type Description
PropertyT | Callable[[PropertyT], PropertyT]

A proxy wrapper for the property.

Source code in pydantic/fields.py
 981
 982
 983
 984
 985
 986
 987
 988
 989
 990
 991
 992
 993
 994
 995
 996
 997
 998
 999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
def computed_field(
    __f: PropertyT | None = None,
    *,
    alias: str | None = None,
    alias_priority: int | None = None,
    title: str | None = None,
    description: str | None = None,
    examples: list[Any] | None = None,
    json_schema_extra: JsonDict | typing.Callable[[JsonDict], None] | None = None,
    repr: bool | None = None,
    return_type: Any = PydanticUndefined,
) -> PropertyT | typing.Callable[[PropertyT], PropertyT]:
    """Usage docs: https://docs.pydantic.dev/2.6/concepts/fields#the-computed_field-decorator

    Decorator to include `property` and `cached_property` when serializing models or dataclasses.

    This is useful for fields that are computed from other fields, or for fields that are expensive to compute and should be cached.

    ```py
    from pydantic import BaseModel, computed_field

    class Rectangle(BaseModel):
        width: int
        length: int

        @computed_field
        @property
        def area(self) -> int:
            return self.width * self.length

    print(Rectangle(width=3, length=2).model_dump())
    #> {'width': 3, 'length': 2, 'area': 6}
    ```

    If applied to functions not yet decorated with `@property` or `@cached_property`, the function is
    automatically wrapped with `property`. Although this is more concise, you will lose IntelliSense in your IDE,
    and confuse static type checkers, thus explicit use of `@property` is recommended.

    !!! warning "Mypy Warning"
        Even with the `@property` or `@cached_property` applied to your function before `@computed_field`,
        mypy may throw a `Decorated property not supported` error.
        See [mypy issue #1362](https://github.com/python/mypy/issues/1362), for more information.
        To avoid this error message, add `# type: ignore[misc]` to the `@computed_field` line.

        [pyright](https://github.com/microsoft/pyright) supports `@computed_field` without error.

    ```py
    import random

    from pydantic import BaseModel, computed_field

    class Square(BaseModel):
        width: float

        @computed_field
        def area(self) -> float:  # converted to a `property` by `computed_field`
            return round(self.width**2, 2)

        @area.setter
        def area(self, new_area: float) -> None:
            self.width = new_area**0.5

        @computed_field(alias='the magic number', repr=False)
        def random_number(self) -> int:
            return random.randint(0, 1_000)

    square = Square(width=1.3)

    # `random_number` does not appear in representation
    print(repr(square))
    #> Square(width=1.3, area=1.69)

    print(square.random_number)
    #> 3

    square.area = 4

    print(square.model_dump_json(by_alias=True))
    #> {"width":2.0,"area":4.0,"the magic number":3}
    ```

    !!! warning "Overriding with `computed_field`"
        You can't override a field from a parent class with a `computed_field` in the child class.
        `mypy` complains about this behavior if allowed, and `dataclasses` doesn't allow this pattern either.
        See the example below:

    ```py
    from pydantic import BaseModel, computed_field

    class Parent(BaseModel):
        a: str

    try:

        class Child(Parent):
            @computed_field
            @property
            def a(self) -> str:
                return 'new a'

    except ValueError as e:
        print(repr(e))
        #> ValueError("you can't override a field with a computed field")
    ```

    Private properties decorated with `@computed_field` have `repr=False` by default.

    ```py
    from functools import cached_property

    from pydantic import BaseModel, computed_field

    class Model(BaseModel):
        foo: int

        @computed_field
        @cached_property
        def _private_cached_property(self) -> int:
            return -self.foo

        @computed_field
        @property
        def _private_property(self) -> int:
            return -self.foo

    m = Model(foo=1)
    print(repr(m))
    #> M(foo=1)
    ```

    Args:
        __f: the function to wrap.
        alias: alias to use when serializing this computed field, only used when `by_alias=True`
        alias_priority: priority of the alias. This affects whether an alias generator is used
        title: Title to use when including this computed field in JSON Schema
        description: Description to use when including this computed field in JSON Schema, defaults to the function's
            docstring
        examples: Example values to use when including this computed field in JSON Schema
        json_schema_extra: A dict or callable to provide extra JSON schema properties.
        repr: whether to include this computed field in model repr.
            Default is `False` for private properties and `True` for public properties.
        return_type: optional return for serialization logic to expect when serializing to JSON, if included
            this must be correct, otherwise a `TypeError` is raised.
            If you don't include a return type Any is used, which does runtime introspection to handle arbitrary
            objects.

    Returns:
        A proxy wrapper for the property.
    """

    def dec(f: Any) -> Any:
        nonlocal description, return_type, alias_priority
        unwrapped = _decorators.unwrap_wrapped_function(f)
        if description is None and unwrapped.__doc__:
            description = inspect.cleandoc(unwrapped.__doc__)

        # if the function isn't already decorated with `@property` (or another descriptor), then we wrap it now
        f = _decorators.ensure_property(f)
        alias_priority = (alias_priority or 2) if alias is not None else None

        if repr is None:
            repr_: bool = False if _wrapped_property_is_private(property_=f) else True
        else:
            repr_ = repr

        dec_info = ComputedFieldInfo(
            f, return_type, alias, alias_priority, title, description, examples, json_schema_extra, repr_
        )
        return _decorators.PydanticDescriptorProxy(f, dec_info)

    if __f is None:
        return dec
    else:
        return dec(__f)

ComputedFieldInfo dataclass

A container for data from @computed_field so that we can access it while building the pydantic-core schema.

Attributes:

Name Type Description
decorator_repr str

A class variable representing the decorator string, '@computed_field'.

wrapped_property property

The wrapped computed field property.

return_type Any

The type of the computed field property's return value.

alias str | None

The alias of the property to be used during serialization.

alias_priority int | None

The priority of the alias. This affects whether an alias generator is used.

title str | None

Title of the computed field to include in the serialization JSON schema.

description str | None

Description of the computed field to include in the serialization JSON schema.

examples list[Any] | None

Example values of the computed field to include in the serialization JSON schema.

json_schema_extra JsonDict | Callable[[JsonDict], None] | None

A dict or callable to provide extra JSON schema properties.

repr bool

A boolean indicating whether to include the field in the repr output.