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    #iV9                     @  s  d Z ddlmZ ddlZddlZddlZddlmZm	Z	m
Z
mZmZmZmZ ddlmZ ddlmZmZmZ ddlmZmZmZ dd	lmZ dd
lmZ ddlmZ ddlm Z  ddl!m"Z"m#Z#m$Z$ erddl%m&Z& dZ'edZ(ej)dkreej*e"e$fdeddddddddddd
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d'dZ+eej*e"e$fdd>ddddddddddd
d(ddddddddddd)d!d*dZ+ee,Z-d+ej)  krd,k rn nd-d-d.d/d0d1Z.e.ej/_0ddd2dd3d ddd4d5dd6d7d8Z1d9d:d;d<d=Z2dS )?z7Provide an enhanced dataclass that performs validation.    )annotationsN)TYPE_CHECKINGAnyCallableGenericNoReturnTypeVaroverload)warn)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slotszLiteral[False]boolz ConfigDict | type[object] | Nonezbool | Nonez-Callable[[type[_T]], type[PydanticDataclass]])r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   returnc        
   
      C  s   d S N r!   r/   r/   \/var/www/html/me.goteku.com/backend/venv/lib/python3.8/site-packages/pydantic/dataclasses.pyr      s    r   ztype[_T]type[PydanticDataclass])_clsr"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r-   c       
         C  s   d S r.   r/   )r2   r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r/   r/   r0   r   .   s    r"   r#   r$   r%   r&   r'   r(   r)   )	r"   r#   r$   r%   r&   r'   r(   r)   r-   c                 C  s   d S r.   r/   r3   r/   r/   r0   r   A   s    )
r2   r"   r#   r$   r%   r&   r'   r(   r)   r-   c          	      C  s   d S r.   r/   )	r2   r"   r#   r$   r%   r&   r'   r(   r)   r/   r/   r0   r   P   s    ztype[_T] | NonezGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c       
      	     s   |dkst d|dk	s t dtjdkr6|	|
dni dddd	d
ddd fdd}| dkrx|S || S )a  Usage docs: https://docs.pydantic.dev/2.9/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. If not set, the value from the provided `config` argument will be used (and will default to `False` otherwise).
        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|dg }|D ]}t| |d}t|ts6qd|i}tjdkrV|jrVd|d< |jdk	rj|j|d< t| |t	j
f | | jddkri | _|| | j|< qqdS )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__getr7   )r6   Zannotation_clsr   
field_nameZfield_valueZ
field_argsr/   r/   r0   make_pydantic_fields_compatible   s    



z2dataclass.<locals>.make_pydantic_fields_compatibler1   c           
   	     s8  ddl m} || r*td| j ddd| } dk	r: n
t| dd}t|}tj	| }| j
}t| rd}| f}t| trt| j }||f }t| j|} |  dk	rֈ}	|jrtd	| jd
tdd n
|jpd}	tj| fd|	d} || _|| _
|j| _|j| _d| _tj| |ddd | S )zCreate 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 modelzdataclass-on-model)codeN__pydantic_config__zN`frozen` is set via both the `dataclass` decorator and `config` for dataclass zW.This is not recommended. The `frozen` specification on `dataclass` will take priority.   )category
stacklevelFT)r"   r#   r$   r%   r&   r'   raise_errorstypes_namespace)Z_internal._utilsrE   r   __name__r:   r   ConfigWrapperr   ZDecoratorInfosbuild__doc___pydantic_dataclassesZis_builtin_dataclass
issubclassr   __parameters__types	new_classr'   r
   UserWarningr?   r   Z__pydantic_decorators__
__module____qualname____pydantic_complete__complete_dataclass)
r6   rE   Zoriginal_clsZconfig_dictZconfig_wrapperZ
decoratorsZoriginal_docbasesgeneric_baseZfrozen_r(   r$   r'   kwargsrD   r%   r#   r&   r/   r0   create_dataclass   s^    	





	z#dataclass.<locals>.create_dataclassN)AssertionErrorr<   r=   )r2   r"   r#   r$   r%   r&   r'   r(   r)   r*   r+   r`   r/   r^   r0   r   `   s    .
#"O)r      )r      r   r   )argsr_   r-   c                  O  s   t ddS )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)rd   r_   r/   r/   r0   _call_initvar  s    rf   rH   )forcerL   _parent_namespace_depth_types_namespaceintzdict[str, Any] | None)r6   rg   rL   rh   ri   r-   c                C  sp   |s| j rdS |dk	r | }n.|dkr>tj|dp6i }|}ni }t| |}tj| tj| j	dd||dS dS )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)checkrK   )
rZ   copyr   Zparent_frame_namespaceZmerge_cls_and_parent_nsrR   r[   r   rO   rG   )r6   rg   rL   rh   ri   rM   Zframe_parent_nsr/   r/   r0   r     s    

r   r4   z"TypeGuard[type[PydanticDataclass]])class_r-   c                C  s2   zd| j kot| W S  tk
r,   Y dS X dS )zWhether 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)rA   r?   is_dataclassAttributeError)rm   r/   r/   r0   is_pydantic_dataclassL  s    	rp   )N)3rQ   
__future__r   Z_annotationsr?   r<   rU   typingr   r   r   r   r   r   r	   warningsr
   typing_extensionsr   r   r   	_internalr   r   r   r   rR   Z
_migrationr   r(   r   errorsr   fieldsr   r   r   Z_internal._dataclassesr   __all__r   r=   r@   r   rN   __getattr__rf   InitVar__call__r   rp   r/   r/   r/   r0   <module>   s   $*.&( * +1