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__module__� __qualname__�__doc__�__annotations__� � �[C:\Users\noahv\Documents\GitHub\clickup-operator\.venv\Lib\site-packages\pydantic/fields.pyr, r, 1 s� � �e� � �O�O� �� � �;�;�#�#� ��A�A��� � �
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< ded< ded< ded< ded< ded< ded< ded< ded< ded < ded < ded < d ed < ded!< ded"< ded#< d$ed%< d&Zej ej ej ej ej ej ej ej d'd'd'd'd'd'ej d(�Zd)ed*< d@d+�ZeefdAd,�� ZedBd-�� ZedCd.�� ZedDd/�� ZedEd0�� ZedFd1�� ZedGd2�� Ze dHd3�� Z e d'd4� dId5�� Z e d6d7�dJd8�� Z d9d'd:�dKd;�Z dLd<�Z dMd=�Z! dN dOd>�Z"dPd?�Z#y')Q� FieldInfoa� This class holds information about a field.
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!!! warning
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[`BaseModel`][pydantic.main.BaseModel] `.model_fields` internals.
Attributes:
annotation: The type annotation of the field.
default: The default value of the field.
default_factory: A callable to generate the default value. The callable can either take 0 arguments
(in which case it is called as is) or a single argument containing the already validated data.
alias: The alias name of the field.
alias_priority: The priority of the field's alias.
validation_alias: The validation alias of the field.
serialization_alias: The serialization alias of the field.
title: The title of the field.
field_title_generator: A callable that takes a field name and returns title for it.
description: The description of the field.
examples: List of examples of the field.
exclude: Whether to exclude the field from the model serialization.
discriminator: Field name or Discriminator for discriminating the type in a tagged union.
deprecated: A deprecation message, an instance of `warnings.deprecated` or the `typing_extensions.deprecated` backport,
or a boolean. If `True`, a default deprecation message will be emitted when accessing the field.
json_schema_extra: A dict or callable to provide extra JSON schema properties.
frozen: Whether the field is frozen.
validate_default: Whether to validate the default value of the field.
repr: Whether to include the field in representation of the model.
init: Whether the field should be included in the constructor of the dataclass.
init_var: Whether the field should _only_ be included in the constructor of the dataclass, and not stored.
kw_only: Whether the field should be a keyword-only argument in the constructor of the dataclass.
metadata: List of metadata constraints.
r- r. r rm r/ r0 r1 r2 r3 r4 r5 r6 r7 r8 r9 r: r; r< r= r> r? rS rT rU r rV rW rX rY rZ r[ r\ r] r^ � list[Any]�metadata)r. � evaluatedrm r0 r2 r4 r6 r7 r8 r: r; r= r? rT r rW rX rY r[ r\ r] r^ rq �_attributes_setN)rJ rA rC rE rG rI rK rL rN rO rP rQ rR r_ r` z7ClassVar[dict[str, typing.Callable[[Any], Any] | None]]�metadata_lookupc �r � |j � D ��ci c] \ }}|t us�||�� c}}| _ |j � D ��ci c]% \ }}||t u rt j |� n|��' }}}| j |j d� � \ | _ }d| _ |j dt � }|t u r(t | _ | j j dd� n|| _ |j dd� | _ | j t ur| j � t d� �|j dd� | _ |j dd� | _ |j d d� | _ t# d
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or one of the constructor classmethods.
See the signature of `pydantic.fields.Field` for more details about the expected arguments.
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��U T��\s �L-�L-�*L3c �: � d|v r t d� �t dd| i|��S )a~ 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)
```
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from_fieldzFieldInfo.from_field� s+ � �0 �6� !�� W�X� X��3��3�F�3�3rh c �� � d}t j | � r,d}| t j urt j | � d } t j
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|t � s�|�� }}t j |d|i�}|r�t |� }||_
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|t � s|j |� �L|j! |j" � �h ||_ |S t | |xs d�� S c c}w )a� 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.
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a� 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.
z�Error when building FieldInfo from annotated attribute. Make sure you don't have any field name clashing with a type annotation zunevaluable-type-annotation��coder r. FTr\ Nr^ )r. rm )r. rm rX ) r! r r� r� r� r� r� ro r r. rq r� rX � dataclassesr �InitVar�typingr r �type�_from_dataclass_fieldr] r� r\ r^ r� r� r� r r� r� )
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�| �|d< t | � r!t dt � nt | � r| |d< |j |� |j" D ]! } t | t$ � r�| |t' | � < �# �� |j |� t% di |��}t) |j+ � � |_ |S # t $ r Y ��w xY w)z�Merge `FieldInfo` instances keeping only explicitly set attributes.
Later `FieldInfo` instances override earlier ones.
Returns:
FieldInfo: A merged FieldInfo instance.
r r rm rW z�Composing `dict` and `callable` type `json_schema_extra` is not supported.The `callable` type is being ignored.If you'd like support for this behavior, please open an issue on pydantic.rg )�lenr rs �updater� r r� rm r| �setattrr~ r� �dict�callabler
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� D ��ci c] \ }}|t v s�||�� }}}t d||| j d�|��S c c}}w )a] Return a new `FieldInfo` instance from a `dataclasses.Field` instance.
Args:
dc_field: The `dataclasses.Field` instance to convert.
Returns:
The corresponding `FieldInfo` instance.
Raises:
TypeError: If any of the `FieldInfo` kwargs does not match the `dataclass.Field` kwargs.
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rm r� �MISSINGr' r0 rq r| �_FIELD_ARG_NAMESr r[ )�dc_fieldrm r0 r� r� �dc_field_metadatas ri r� z FieldInfo._from_dataclass_field� s� � � �"�"�� �k�)�)� )� �G� � #� #�{�':�':� :� $�O� &� 6� 6�O� /7�.?�.?�.E�.E�.G� a�.G�d�a��1�P`�K`�Q��T�.G�� a��o�W�o�H�M�M�o�]n�o�o�� bs �1B#�B#c � � | �9t j | � r$t j | � ^}}|t |� fS | g fS )a/ Tries to extract metadata/constraints from an annotation if it uses `Annotated`.
Args:
annotation: The type hint annotation for which metadata has to be extracted.
Returns:
A tuple containing the extracted metadata type and the list of extra arguments.
)r r� r� r� r� )r. r� r� s ri r zFieldInfo._extract_metadata sG � � � !� �)�)�*�5�):�)C�)C�J�)O�&� �J� �$�z�"2�2�2��2�~� rh c �, � g }i }t | j � � D ]> \ }} t j | }| |= |�� |�|||< �(|j ||� � �@ |r$|j t
j di |��� |S # t $ r Y �tw xY w)a Collect annotations from kwargs.
Args:
kwargs: Keyword arguments passed to the function.
Returns:
A list of metadata objects - a combination of `annotated_types.BaseMetadata` and
`PydanticMetadata`.
rg )r� r| ro rt r� r� r �pydantic_general_metadata)r� rq �general_metadata�key�value�markers ri r� zFieldInfo._collect_metadata s� � � !�� �� �v�|�|�~�.�J�C��
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�s �B� B�Bc �� � | j �yt | j t � r| j rdS dS t | j t � r | j S | j j S �z<The deprecation message to be emitted, or `None` if not set.Nr �r r� rZ �strr� �r� s ri �deprecation_messagez FieldInfo.deprecation_message5 �V � � �?�?� "�� �d�o�o�t� ,�#'�?�?�<� <�� <�",�T�_�_�c�"B�t���_����H_�H_�_rh )�validated_datac � � y rx rg )r� �call_default_factoryr� s ri � get_defaultzFieldInfo.get_default> s � � rh .)r� c � � y rx rg )r� r� s ri r� zFieldInfo.get_defaultC s � �QTrh F)r� r� c �, � | j � t j | j � S |rgt j
| j � r |� t
d� �| j |� S t t g t f | j � } |� S y)a` 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.
validated_data: The already validated data to be passed to the default factory.
Returns:
The default value, calling the default factory if requested or `None` if not set.
NznThe default factory requires the 'validated_data' argument, which was not provided when calling 'get_default'.)
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!��4�4�T�5I�5I�J�!�)�$� I�� � �+�+�N�;�;��8�B��G�,�d�.B�.B�C���u� �rh c �F � | j t u xr | j du S )z�Check if the field is required (i.e., does not have a default value or factory).
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N)rm r r0 r� s ri � is_requiredzFieldInfo.is_requiredc s$ � � �|�|� 0�0�Q�T�5I�5I�T�5Q�Qrh c � � | j s | j S t j | j g| j �� S )a( Attempts to rebuild the original annotation for use in function signatures.
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`Annotated`. Otherwise, it returns the original annotation as-is.
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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.
)rq r. r� � Annotatedr� s ri �rebuild_annotationz FieldInfo.rebuild_annotationk s8 � � �}�}��?�?� "� %�.�.����/P�$�-�-�/P�Q� Qrh c � � t j | j ||� \ }}t j ||� | _ y)a� Apply a `typevars_map` to the annotation.
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Args:
typevars_map: A dictionary mapping type variables to their concrete types.
globalns: The globals namespace to use during type annotation evaluation.
localns: The locals namespace to use during type annotation evaluation.
See Also:
pydantic._internal._generics.replace_types is used for replacing the typevars with
their concrete types.
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rh c " � � y rx rg )#r0 r2 r4 r6 r7 r8 r: r; r= r? rT r rW rX rY r[ r\ r] r^ rN rJ r_ rA rC rE rG rI rO rP rQ rK rL rR r` r s# ri r r - r rh c ! � � y rx rg )"r2 r4 r6 r7 r8 r: r; r= r? rT r rW rX rY r[ r\ r] r^ rN rJ r_ rA rC rE rG rI rO rP rQ rK rL rR r` r s" ri r r T s � �J rh )"r0 r2 r4 r6 r7 r8 r: r; r= r? rT r rW rX rY r[ r\ r] r^ rN rJ r_ rA rC rE rG rI rO rP rQ rK rL rR r` c " �T � |#j dd� }$|$�
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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. The callable can either take 0 arguments
(in which case it is called as is) or a single argument containing the already validated data.
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.
field_title_generator: A callable that takes a field name and returns title for it.
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.
deprecated: A deprecation message, an instance of `warnings.deprecated` or the `typing_extensions.deprecated` backport,
or a boolean. If `True`, a default deprecation message will be emitted when accessing the field.
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.)
coerce_numbers_to_str: Whether to enable coercion of any `Number` type to `str` (not applicable in `strict` mode).
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 iterables.
max_length: Maximum length for iterables.
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](../concepts/unions.md#union-modes) for details.
fail_fast: If `True`, validation will stop on the first error. If `False`, all validation errors will be collected.
This option can be applied only to iterable types (list, tuple, set, and frozenset).
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.
�constNz)`const` is removed, use `Literal` insteadzremoved-kwargsr� � min_itemszG`min_items` is deprecated and will be removed, use `min_length` instead� max_itemszG`max_items` is deprecated and will be removed, use `max_length` instead� unique_itemsz`unique_items` is removed, use `Set` instead(this feature is discussed in https://github.com/pydantic/pydantic-core/issues/296)�allow_mutationzH`allow_mutation` is deprecated and will be removed. use `frozen` insteadFT�regexz)`regex` is removed. use `pattern` insteadzzUsing extra keyword arguments on `Field` is deprecated and will be removed. Use `json_schema_extra` instead. (Extra keys: z, c 3 �< K � | ] }|j � �� � y �wrx )�__repr__)ry r� s ri rz zField.<locals>.<genexpr> s � �� �&J�\��q�z�z�|�\�s � �)zSInvalid `validation_alias` type. it should be `str`, `AliasChoices`, or `AliasPath`�includezS`include` is deprecated and does nothing. It will be removed, use `exclude` insteadr0 r2 r4 r6 r7 r8 r: r; r= r? rT r rW rX rN rY r[ r\ r] r^ r_ rJ rA rC rE rG rI rK rL rO rP rQ rR r` )r� r! r
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!!! warning
You generally shouldn't be creating `ModelPrivateAttr` instances directly, instead use
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Attributes:
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.
)rm r0 N�r0 c �V � |t u rt | _ || _ y || _ || _ y rx )r� r rm r0 )r� rm r0 s ri r� zModelPrivateAttr.__init__\ s. � � �h� �,�D�L� /�� � #�D�L� .�� rh c � � |dv r,t | j |� rt | j |� S t t | � j
�d|��� �)z�This function improves compatibility with custom descriptors by ensuring delegation happens
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|||� yy)zMPreserve `__set_name__` protocol defined in https://peps.python.org/pep-0487.N� __set_name__)rm r r� r� )r� �cls�namerm �set_names ri r& z ModelPrivateAttr.__set_name__q s< � ��,�,�� �'� '� ��7�N�D�9�� �H� � �S�$� � rh c �x � | j � t j | j � S | j � S )aU 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.
)r0 r r� rm r� s ri r� z ModelPrivateAttr.get_defaultz s3 � � 7;�6J�6J�6R�v�$�$�T�\�\�2�n�X\�Xl�Xl�Xn�nrh c � � t || j � xr1 | j | j f|j |j fk( S rx )r� � __class__rm r0 )r� �others ri �__eq__zModelPrivateAttr.__eq__� sF � ��%�� � �0�
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|� t d� �t | |�� S )a� Usage docs: https://docs.pydantic.dev/2.10/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.
init: Whether the attribute should be included in the constructor of the dataclass. Always `False`.
Returns:
An instance of [`ModelPrivateAttr`][pydantic.fields.ModelPrivateAttr] class.
Raises:
ValueError: If both `default` and `default_factory` are set.
rv r )r r� r )rm r0 r\ s ri r% r% � s1 � �6 �'�'�O�,G��I�J�J� ��'� � rh c � � e Zd ZU dZdZded< ded< ded< d ed
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< ded< d ed< ded< ded< ded< ded< edd�� Zy) �ComputedFieldInfoa4 A container for data from `@computed_field` so that we can access it while building the pydantic-core schema.
Attributes:
decorator_repr: A class variable representing the decorator string, '@computed_field'.
wrapped_property: The wrapped computed field property.
return_type: The type of the computed field property's return value.
alias: The alias of the property to be used during serialization.
alias_priority: The priority of the alias. This affects whether an alias generator is used.
title: Title of the computed field to include in the serialization JSON schema.
field_title_generator: A callable that takes a field name and returns title for it.
description: Description of the computed field to include in the serialization JSON schema.
deprecated: A deprecation message, an instance of `warnings.deprecated` or the `typing_extensions.deprecated` backport,
or a boolean. If `True`, a default deprecation message will be emitted when accessing the field.
examples: Example values of the computed field to include in the serialization JSON schema.
json_schema_extra: A dict or callable to provide extra JSON schema properties.
repr: A boolean indicating whether to include the field in the __repr__ output.
z@computed_fieldz
ClassVar[str]�decorator_reprr �wrapped_propertyr � return_typer1 r2 r3 r4 r8 �5typing.Callable[[str, ComputedFieldInfo], str] | Noner: r; rU r r< r= �3JsonDict | typing.Callable[[JsonDict], None] | NonerW rZ r[ c �� � | j �yt | j t � r| j rdS dS t | j t � r | j S | j j S r� r� r� s ri r� z%ComputedFieldInfo.deprecation_message� r� rh Nr� )rb rc rd re r9 rf r r� rg rh ri r8 r8 � sh � ��$ %6�N�M�5� � ��� �� � � ��P�P���.�.� � �J�J�
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d� } | �| S | | � S )a# Usage docs: https://docs.pydantic.dev/2.10/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.
```python
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.
```python
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:
```python
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.
```python
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))
#> Model(foo=1)
```
Args:
func: 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
field_title_generator: A callable that takes a field name and returns title for it.
description: Description to use when including this computed field in JSON Schema, defaults to the function's
docstring
deprecated: A deprecation message (or an instance of `warnings.deprecated` or the `typing_extensions.deprecated` backport).
to be emitted when accessing the field. Or a boolean. This will automatically be set if the property is decorated with the
`deprecated` decorator.
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.
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