관리-도구
편집 파일: dataclasses.cpython-38.pyc
U /?�fU6 � @ s� d Z ddlmZ ddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZ ddlmZmZmZ ddlmZmZmZ ddlmZ dd lmZ dd lm Z dd l m Z dd l m Z m!Z!m"Z" er�dd l#m$Z$ dZ%e d�Z&ej'dk�r�eej(e e"fd�eddddddddddd� dddddddddddd� d d ���Z)eej(e e"fd�eddddddddddd� d ddddddddddd d � d!d ���Z)n�eej(e e"fd�eddddddddd"�dddddddddd#� d$d ���Z)eej(e e"fd�eddddddddd"�d ddddddddd d%� d&d ���Z)eej(e e"fd�d=ddddddddddd� d'ddddddddddd(d � d)d ��Z)ee*�Z+d*ej' k�r�d+k �r�n nd,d,d-d.�d/d0�Z,e,ej-_.ddd1dd2�d ddd3d4dd5�d6d7�Z/d8d9d:�d;d<�Z0dS )>z7Provide an enhanced dataclass that performs validation.� )� annotationsN)� TYPE_CHECKING�Any�Callable�Generic�NoReturn�TypeVar�overload)�Literal� TypeGuard�dataclass_transform� )�_config� _decorators� _typing_extra)� _dataclasses)�getattr_migration)� ConfigDict)�PydanticUserError)�Field� FieldInfo� PrivateAttr)�PydanticDataclass)� dataclass�rebuild_dataclass�_T�� � )�field_specifiersFT.� �init�repr�eq�order� unsafe_hash�frozen�config�validate_on_init�kw_only�slotszLiteral[False]�boolz ConfigDict | type[object] | Nonez bool | Nonez-Callable[[type[_T]], type[PydanticDataclass]]) r! r" r# r$ r% r& r' r( r) r* �returnc C s d S �N� r r. r. �B/opt/hc_python/lib/python3.8/site-packages/pydantic/dataclasses.pyr s r ztype[_T]�type[PydanticDataclass]) �_clsr! r" r# r$ r% r& r' r( r) r* r, c C s d S r- r. ) r1 r! r" r# r$ r% r& r' r( r) r* r. r. r/ r - s �r! r" r# r$ r% r& r' r( ) r! r" r# r$ r% r& r' r( r, c C s d S r- r. r2 r. r. r/ r @ s ) r1 r! r" r# r$ r% r& r' r( r, c C s d S r- r. ) r1 r! r" r# r$ r% r& r' r( r. r. r/ r O s ztype[_T] | NonezGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c s� |dkst d��|dk s t d��tjdkr8t| | d��ni �ddd�d d ��dd d�� �������fd d � } | dkrz| S | | �S )aS Usage docs: https://docs.pydantic.dev/2.8/concepts/dataclasses/ A decorator used to create a Pydantic-enhanced dataclass, similar to the standard Python `dataclass`, but with added validation. This function should be used similarly to `dataclasses.dataclass`. Args: _cls: The target `dataclass`. init: Included for signature compatibility with `dataclasses.dataclass`, and is passed through to `dataclasses.dataclass` when appropriate. If specified, must be set to `False`, as pydantic inserts its own `__init__` function. repr: A boolean indicating whether to include the field in the `__repr__` output. eq: Determines if a `__eq__` method should be generated for the class. order: Determines if comparison magic methods should be generated, such as `__lt__`, but not `__eq__`. unsafe_hash: Determines if a `__hash__` method should be included in the class, as in `dataclasses.dataclass`. frozen: Determines if the generated class should be a 'frozen' `dataclass`, which does not allow its attributes to be modified after it has been initialized. config: The Pydantic config to use for the `dataclass`. validate_on_init: A deprecated parameter included for backwards compatibility; in V2, all Pydantic dataclasses are validated on init. kw_only: Determines if `__init__` method parameters must be specified by keyword only. Defaults to `False`. slots: Determines if the generated class should be a 'slots' `dataclass`, which does not allow the addition of new attributes after instantiation. Returns: A decorator that accepts a class as its argument and returns a Pydantic `dataclass`. Raises: AssertionError: Raised if `init` is not `False` or `validate_on_init` is `False`. Fz7pydantic.dataclasses.dataclass only supports init=Falsez-validate_on_init=False is no longer supportedr )r) r* � type[Any]�None)�clsr, c S s� | j D ]�}t|dg �}|D ]�}t| |d�}t|t�s6qd|i}tjdkrV|jrVd|d< |jdk rj|j|d< t| |t j f |�� | j � d�dkr�i | _ || | j |< qqdS )a Make sure that stdlib `dataclasses` understands `Field` kwargs like `kw_only` To do that, we simply change `x: int = pydantic.Field(..., kw_only=True)` into `x: int = dataclasses.field(default=pydantic.Field(..., kw_only=True), kw_only=True)` �__annotations__N�defaultr Tr) r" )�__mro__�getattr� isinstancer �sys� version_infor) r" �setattr� dataclasses�field�__dict__�getr6 )r5 Zannotation_clsr � field_nameZ field_valueZ field_argsr. r. r/ � make_pydantic_fields_compatible� s z2dataclass.<locals>.make_pydantic_fields_compatibler0 c s ddl m} || �r*td| j� d�dd��| }� }|dkrRt| dd�}|dk rR|}t�|�}tj� | �}| j }t � | �r�d}| f}t | t�r�t| j } || f }t�| j|�} �| � tj| fd �����d ����} || _|| _ |j| _|j| _t j| |d dd �} | | _| S ) z�Create a Pydantic dataclass from a regular dataclass. Args: cls: The class to create the Pydantic dataclass from. Returns: A Pydantic dataclass. r )�is_model_classz(Cannot create a Pydantic dataclass from z" as it is already a Pydantic modelzdataclass-on-model)�codeN�__pydantic_config__T)r! r" r# r$ r% r& F�� raise_errors�types_namespace)Z_internal._utilsrD r �__name__r9 r � ConfigWrapperr ZDecoratorInfos�build�__doc__�_pydantic_dataclassesZis_builtin_dataclass� issubclassr �__parameters__�types� new_classr> r Z__pydantic_decorators__� __module__� __qualname__�complete_dataclass�__pydantic_complete__) r5 rD Z original_clsZ config_dictZ cls_configZconfig_wrapperZ decoratorsZ original_doc�bases� generic_baseZpydantic_complete�r' r# r& �kwargsrC r$ r" r% r. r/ �create_dataclass� s^ � �� � �z#dataclass.<locals>.create_dataclassN)�AssertionErrorr; r< �dict) r1 r! r" r# r$ r% r& r' r( r) r* r[ r. rY r/ r _ s . #"G)r � )r � r r )�argsrZ r, c O s t d��dS )a9 This function does nothing but raise an error that is as similar as possible to what you'd get if you were to try calling `InitVar[int]()` without this monkeypatch. The whole purpose is just to ensure typing._type_check does not error if the type hint evaluates to `InitVar[<parameter>]`. z 'InitVar' object is not callableN)� TypeError)r` rZ r. r. r/ � _call_initvar s rb � )�forcerH �_parent_namespace_depth�_types_namespace�intzdict[str, Any] | None)r5 rd rH re rf r, c C sp |s| j rdS |dk r |�� }n.|dkr>tj|d�p6i }|}ni }t�| |�}tj| tj| j dd�||d�S dS )ax Try to rebuild the pydantic-core schema for the dataclass. 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. This is analogous to `BaseModel.model_rebuild`. Args: cls: The class to rebuild the pydantic-core schema for. force: Whether to force the rebuilding of the schema, defaults to `False`. raise_errors: Whether to raise errors, defaults to `True`. _parent_namespace_depth: The depth level of the parent namespace, defaults to 2. _types_namespace: The types namespace, defaults to `None`. Returns: Returns `None` if the schema is already "complete" and rebuilding was not required. If rebuilding _was_ required, returns `True` if rebuilding was successful, otherwise `False`. Nr )Z parent_depthF)�checkrG ) rV �copyr Zparent_frame_namespaceZget_cls_types_namespacerN rU r rK rF )r5 rd rH re rf rI Zframe_parent_nsr. r. r/ r s �r r3 z"TypeGuard[type[PydanticDataclass]])�class_r, c C s2 zd| j kot�| �W S tk r, Y dS X dS )z�Whether a class is a pydantic dataclass. Args: class_: The class. Returns: `True` if the class is a pydantic dataclass, `False` otherwise. Z__pydantic_validator__FN)r@ r> � is_dataclass�AttributeError)rj r. r. r/ �is_pydantic_dataclassF s rm )N)1rM � __future__r Z _annotationsr> r; rQ �typingr r r r r r r �typing_extensionsr r r � _internalr r r r rN Z _migrationr r' r �errorsr �fieldsr r r Z_internal._dataclassesr �__all__r r< r? r rJ � __getattr__rb �InitVar�__call__r rm r. r. r. r/ �<module> s� $ �*�.�& �( ��* & � 1