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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mZ dd	lmZ 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/Z0d,ej,  krd-k rn nd.d.d/d0d1d2Z1e1ej2_3ddd3dd4d!ddd5d6dd7d8d9Z4d:d;d<d=d>Z5dS )@z7Provide an enhanced dataclass that performs validation.    )annotationsN)TYPE_CHECKINGAnyCallableGenericNoReturnTypeVaroverload)warn)Literal	TypeGuarddataclass_transform   )_config_decorators_namespace_utils_typing_extra)_dataclasses)getattr_migration)
ConfigDict)PydanticUserError)Field	FieldInfoPrivateAttr)PydanticDataclass)MappingNamespace)	dataclassrebuild_dataclass_T   
   )Z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$   r%   r&   r'   r(   r)   r*   r+   r,   returnc        
   
      C  s   d S N r"   r0   r0   b/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/pydantic/dataclasses.pyr      s    r   ztype[_T]type[PydanticDataclass])_clsr#   r$   r%   r&   r'   r(   r)   r*   r+   r,   r.   c       
         C  s   d S r/   r0   )r3   r#   r$   r%   r&   r'   r(   r)   r*   r+   r,   r0   r0   r1   r   /   s    r#   r$   r%   r&   r'   r(   r)   r*   )	r#   r$   r%   r&   r'   r(   r)   r*   r.   c                 C  s   d S r/   r0   r4   r0   r0   r1   r   B   s    )
r3   r#   r$   r%   r&   r'   r(   r)   r*   r.   c          	      C  s   d S r/   r0   )	r3   r#   r$   r%   r&   r'   r(   r)   r*   r0   r0   r1   r   Q   s    ztype[_T] | NonezGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c       
      	     s   |du sJ d|dus J dt jdkr6|	|
dni dddd	d
ddd fdd}| du rx|S || S )a  Usage docs: https://docs.pydantic.dev/2.10/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urj|j|d< t| |t	j
f i | | jddu 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__getr8   )r7   Zannotation_clsr   
field_nameZfield_valueZ
field_argsr0   r0   r1   make_pydantic_fields_compatible   s    



z2dataclass.<locals>.make_pydantic_fields_compatibler2   c              	     s~  ddl m} || r*td| j ddd| }tdd | jD }|sp d	urpt| d
rptd| j dtdd  d	ur| n
t	| d
d	}t
|}tj| }| j}t| rd	}| f}t| trt| j }	||	f }t| j|} |  d	ur}
|jr(td| jdtdd n|jp&d}
tj| fd|
d} || _|| _|j| _|j| _d| _tj| |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)codec                 s  s   | ]}t |V  qd S r/   )r@   is_dataclass).0baser0   r0   r1   	<genexpr>       z6dataclass.<locals>.create_dataclass.<locals>.<genexpr>N__pydantic_config__z[`config` is set via both the `dataclass` decorator and `__pydantic_config__` for dataclass zK. The `config` specification from `dataclass` decorator will take priority.   )category
stacklevelzN`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.FT)r#   r$   r%   r&   r'   r(   )raise_errors)Z_internal._utilsrF   r   __name__any	__bases__hasattrr
   UserWarningr;   r   ConfigWrapperr   ZDecoratorInfosbuild__doc___pydantic_dataclassesZis_builtin_dataclass
issubclassr   __parameters__types	new_classr(   r@   r   Z__pydantic_decorators__
__module____qualname____pydantic_complete__complete_dataclass)r7   rF   Zoriginal_clsZhas_dataclass_baseZconfig_dictZconfig_wrapperZ
decoratorsZoriginal_docbasesZgeneric_baseZfrozen_r)   r%   r(   kwargsrE   r&   r$   r'   r0   r1   create_dataclass   sl    	





	z#dataclass.<locals>.create_dataclassN)r=   r>   )r3   r#   r$   r%   r&   r'   r(   r)   r*   r+   r,   rf   r0   rd   r1   r   a   s    .
#"])r       )r       r   r   )argsre   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)ri   re   r0   r0   r1   _call_initvar   s    rk   rN   )forcerQ   _parent_namespace_depth_types_namespaceintzMappingNamespace | None)r7   rl   rQ   rm   rn   r.   c                C  s|   |s| j rdS d| jv r"t| d |dur0|}n |dkrLtj|ddpHi }ni }tj|d}tj| t	j
| jdd||d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`.
    NZ__pydantic_core_schema__r   T)Zparent_depthrl   )Zparent_namespaceF)check)rQ   ns_resolverZ_force_build)ra   rB   delattrr   Zparent_frame_namespacer   Z
NsResolverrZ   rb   r   rW   rM   )r7   rl   rQ   rm   rn   Z
rebuild_nsrq   r0   r0   r1   r   *  s&    


r   r5   z"TypeGuard[type[PydanticDataclass]])class_r.   c                C  s0   zd| j v ot| W S  ty*   Y dS 0 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)rB   r@   rH   AttributeError)rs   r0   r0   r1   is_pydantic_dataclassb  s    	ru   )N)6rY   
__future__r   Z_annotationsr@   r=   r]   typingr   r   r   r   r   r   r	   warningsr
   Ztyping_extensionsr   r   r   	_internalr   r   r   r   r   rZ   Z
_migrationr   r)   r   errorsr   fieldsr   r   r   Z_internal._dataclassesr   Z_internal._namespace_utilsr   __all__r   r>   rA   r   rR   __getattr__rk   InitVar__call__r   ru   r0   r0   r0   r1   <module>   s   $*.&( * 98