
    dhQz                    F   U d Z ddlmZ ddlZddlZddlZddlmZ ddl	m
Z
 ddlmZmZmZmZmZmZmZmZmZ ddlmZmZ ddl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# ejH                  dk  rddlm%Z% nddlm%Z% ejL                  Z' ejP                  dOddiejR                   G d d             Z* ejP                  dOddiejR                   G d d             Z+ ejP                  dOddiejR                   G d d             Z, ejP                  dOddiejR                   G d d             Z-er G d de%      Z. G d de%      Z/ G d de%      Z0 G d  d!e%      Z1ee/ejd                  e.ejf                  f   Z4ee1ejj                  e0ejl                  f   Z7ee8eeef   e9eef   ee   f   Z:d"e;d#<    ed$ee4e:f   %      Z< ed&ee7e:f   %      Z=ed'   Z>d"e;d(<   ed)d)d*	 	 	 	 	 	 	 	 	 	 	 dPd+       Z?ed)d)d*	 	 	 	 	 	 	 	 	 	 	 dQd,       Z?ed)d)d-	 	 	 	 	 	 	 	 	 dRd.       Z?d/ded0	 	 	 	 	 	 	 	 	 	 	 dSd1Z? ed2      Z@ ed3d4      ZA G d5 d6ej                  e%eA         ZC G d7 d8e%e@         ZD G d9 d:e%e@         ZE G d; d<e%      ZF G d= d>e%      ZG G d? d@e%      ZH G dA dBe%      ZIee@ge@f   ZJ	 ee@ej                  e   ge@f   ZL	 eeEe@   eDe@   f   ZMeeHeIeFeGf   ZNeeLe@   eJe@   f   ZOe	 	 	 	 dTdC       ZPe	 	 	 	 dUdD       ZPe	 	 	 	 dVdE       ZP	 	 	 	 dWdFZP edG      ZQereeQd)f   ZRn) ejP                  dOi ejR                   G dH dI             ZRereeQd)f   ZSn) ejP                  dOi ejR                   G dJ dK             ZS edL      ZT G dM dN      ZUy)XzBThis module contains related classes and functions for validation.    )annotationsN)partialmethod)FunctionType)	TYPE_CHECKING	AnnotatedAnyCallableLiteralTypeVarUnioncastoverload)PydanticUndefinedcore_schema)Self	TypeAlias   )_decorators	_generics_internal_dataclass)GetCoreSchemaHandler)PydanticUserError)ArbitraryTypeWarning)      )ProtocolfrozenTc                  6    e Zd ZU dZded<   ddZedd       Zy)	AfterValidatoraT  !!! abstract "Usage Documentation"
        [field *after* validators](../concepts/validators.md#field-after-validator)

    A metadata class that indicates that a validation should be applied **after** the inner validation logic.

    Attributes:
        func: The validator function.

    Example:
        ```python
        from typing import Annotated

        from pydantic import AfterValidator, BaseModel, ValidationError

        MyInt = Annotated[int, AfterValidator(lambda v: v + 1)]

        class Model(BaseModel):
            a: MyInt

        print(Model(a=1).a)
        #> 2

        try:
            Model(a='a')
        except ValidationError as e:
            print(e.json(indent=2))
            '''
            [
              {
                "type": "int_parsing",
                "loc": [
                  "a"
                ],
                "msg": "Input should be a valid integer, unable to parse string as an integer",
                "input": "a",
                "url": "https://errors.pydantic.dev/2/v/int_parsing"
              }
            ]
            '''
        ```
    Kcore_schema.NoInfoValidatorFunction | core_schema.WithInfoValidatorFunctionfuncc                2    ||      }t        | j                  dd      }|r;t        t        j                  | j                        }t        j
                  ||      S t        t        j                  | j                        }t        j                  ||      S )Nafterfieldmodetypeschema)_inspect_validatorr!   r   r   WithInfoValidatorFunction"with_info_after_validator_functionNoInfoValidatorFunction no_info_after_validator_function)selfsource_typehandlerr)   info_argr!   s         Q/var/www/zara/venv/lib/python3.12/site-packages/pydantic/functional_validators.py__get_pydantic_core_schema__z+AfterValidator.__get_pydantic_core_schema__J   ss    %%diigGL==tyyIDAA$vVV;;TYYGD??VTT    c                (     | |j                         S )Nr!   r7   cls	decorators     r3   _from_decoratorzAfterValidator._from_decoratorT   s    	''r5   Nr0   r   r1   r   returncore_schema.CoreSchemar:   z>_decorators.Decorator[_decorators.FieldValidatorDecoratorInfo]r=   r   )__name__
__module____qualname____doc____annotations__r4   classmethodr;    r5   r3   r   r      s+    (T VUU ( (r5   r   c                  D    e Zd ZU dZded<   eZded<   d	dZed
d       Z	y)BeforeValidatora  !!! abstract "Usage Documentation"
        [field *before* validators](../concepts/validators.md#field-before-validator)

    A metadata class that indicates that a validation should be applied **before** the inner validation logic.

    Attributes:
        func: The validator function.
        json_schema_input_type: The input type used to generate the appropriate
            JSON Schema (in validation mode). The actual input type is `Any`.

    Example:
        ```python
        from typing import Annotated

        from pydantic import BaseModel, BeforeValidator

        MyInt = Annotated[int, BeforeValidator(lambda v: v + 1)]

        class Model(BaseModel):
            a: MyInt

        print(Model(a=1).a)
        #> 2

        try:
            Model(a='a')
        except TypeError as e:
            print(e)
            #> can only concatenate str (not "int") to str
        ```
    r    r!   r   json_schema_input_typec                    ||      }| j                   t        u rd n|j                  | j                         }t        | j                  dd      }|r<t        t        j                  | j                        }t        j                  |||      S t        t        j                  | j                        }t        j                  |||      S )Nbeforer$   r%   r)   json_schema_input_schema)rI   r   generate_schemar*   r!   r   r   r+   #with_info_before_validator_functionr-   !no_info_before_validator_functionr/   r0   r1   r)   input_schemar2   r!   s          r3   r4   z,BeforeValidator.__get_pydantic_core_schema__~   s    % **.?? (()D)DE 	 &diihWM==tyyIDBB)5  ;;TYYGD@@Vl r5   c                R     | |j                   |j                  j                        S N)r!   rI   r!   inforI   r8   s     r3   r;   zBeforeValidator._from_decorator   #    #,>>#H#H
 	
r5   Nr<   r?   
r@   rA   rB   rC   rD   r   rI   r4   rE   r;   rF   r5   r3   rH   rH   Y   s5    @ VU"3C3, 
 
r5   rH   c                  D    e Zd ZU dZded<   eZded<   d	dZed
d       Z	y)PlainValidatora  !!! abstract "Usage Documentation"
        [field *plain* validators](../concepts/validators.md#field-plain-validator)

    A metadata class that indicates that a validation should be applied **instead** of the inner validation logic.

    !!! note
        Before v2.9, `PlainValidator` wasn't always compatible with JSON Schema generation for `mode='validation'`.
        You can now use the `json_schema_input_type` argument to specify the input type of the function
        to be used in the JSON schema when `mode='validation'` (the default). See the example below for more details.

    Attributes:
        func: The validator function.
        json_schema_input_type: The input type used to generate the appropriate
            JSON Schema (in validation mode). The actual input type is `Any`.

    Example:
        ```python
        from typing import Annotated, Union

        from pydantic import BaseModel, PlainValidator

        def validate(v: object) -> int:
            if not isinstance(v, (int, str)):
                raise ValueError(f'Expected int or str, go {type(v)}')

            return int(v) + 1

        MyInt = Annotated[
            int,
            PlainValidator(validate, json_schema_input_type=Union[str, int]),  # (1)!
        ]

        class Model(BaseModel):
            a: MyInt

        print(Model(a='1').a)
        #> 2

        print(Model(a=1).a)
        #> 2
        ```

        1. In this example, we've specified the `json_schema_input_type` as `Union[str, int]` which indicates to the JSON schema
        generator that in validation mode, the input type for the `a` field can be either a [`str`][] or an [`int`][].
    r    r!   r   rI   c           
        ddl m} 	  ||      }|j                  dt        j                  d ||j                  |                  }|j                  | j                        }t        | j                  dd      }|r<t        t        j                  | j                        }t        j                  |||	      S t        t        j                  | j                        }t        j                  |||	      S # |$ r d }Y w xY w)
Nr   PydanticSchemaGenerationErrorserializationc                     ||       S NrF   vhs     r3   <lambda>z=PlainValidator.__get_pydantic_core_schema__.<locals>.<lambda>   
    !A$ r5   )functionr)   return_schemaplainr$   r%   )r^   rM   )pydanticr]   getr   #wrap_serializer_function_ser_schemarN   rI   r*   r!   r   r+   "with_info_plain_validator_functionr-    no_info_plain_validator_function)	r/   r0   r1   r]   r)   r^   rR   r2   r!   s	            r3   r4   z+PlainValidator.__get_pydantic_core_schema__   s     	;	![)F #JJ??.!")"9"9+"FM ..t/J/JK%diigGL==tyyIDAA+)5  ;;TYYGD??+)5  - 	! M	!s   A C5 5C?>C?c                R     | |j                   |j                  j                        S rT   rU   r8   s     r3   r;   zPlainValidator._from_decorator   rW   r5   Nr<   r?   )
r@   rA   rB   rC   rD   r   rI   r4   rE   r;   rF   r5   r3   rZ   rZ      s6    ,\ VU"%C%'R 
 
r5   rZ   c                  D    e Zd ZU dZded<   eZded<   d	dZed
d       Z	y)WrapValidatora  !!! abstract "Usage Documentation"
        [field *wrap* validators](../concepts/validators.md#field-wrap-validator)

    A metadata class that indicates that a validation should be applied **around** the inner validation logic.

    Attributes:
        func: The validator function.
        json_schema_input_type: The input type used to generate the appropriate
            JSON Schema (in validation mode). The actual input type is `Any`.

    ```python
    from datetime import datetime
    from typing import Annotated

    from pydantic import BaseModel, ValidationError, WrapValidator

    def validate_timestamp(v, handler):
        if v == 'now':
            # we don't want to bother with further validation, just return the new value
            return datetime.now()
        try:
            return handler(v)
        except ValidationError:
            # validation failed, in this case we want to return a default value
            return datetime(2000, 1, 1)

    MyTimestamp = Annotated[datetime, WrapValidator(validate_timestamp)]

    class Model(BaseModel):
        a: MyTimestamp

    print(Model(a='now').a)
    #> 2032-01-02 03:04:05.000006
    print(Model(a='invalid').a)
    #> 2000-01-01 00:00:00
    ```
    zScore_schema.NoInfoWrapValidatorFunction | core_schema.WithInfoWrapValidatorFunctionr!   r   rI   c                    ||      }| j                   t        u rd n|j                  | j                         }t        | j                  dd      }|r<t        t        j                  | j                        }t        j                  |||      S t        t        j                  | j                        }t        j                  |||      S )Nwrapr$   r%   rL   )rI   r   rN   r*   r!   r   r   WithInfoWrapValidatorFunction!with_info_wrap_validator_functionNoInfoWrapValidatorFunctionno_info_wrap_validator_functionrQ   s          r3   r4   z*WrapValidator.__get_pydantic_core_schema__+  s    % **.?? (()D)DE 	 &diif7KAA499MD@@)5  ??KD>>)5 r5   c                R     | |j                   |j                  j                        S rT   rU   r8   s     r3   r;   zWrapValidator._from_decoratorC  rW   r5   Nr<   r?   rX   rF   r5   r3   rp   rp      s5    $L ^]"3C30 
 
r5   rp   c                      e Zd ZddZy)_OnlyValueValidatorClsMethodc                    y r`   rF   r/   r9   values      r3   __call__z%_OnlyValueValidatorClsMethod.__call__N      r5   Nr9   r   r|   r   r=   r   r@   rA   rB   r}   rF   r5   r3   ry   ry   M  s    ?r5   ry   c                      e Zd ZddZy)_V2ValidatorClsMethodc                    y r`   rF   r/   r9   r|   rV   s       r3   r}   z_V2ValidatorClsMethod.__call__Q  r~   r5   Nr9   r   r|   r   rV   core_schema.ValidationInfo[Any]r=   r   r   rF   r5   r3   r   r   P  s    fr5   r   c                      e Zd ZddZy) _OnlyValueWrapValidatorClsMethodc                    y r`   rF   r/   r9   r|   r1   s       r3   r}   z)_OnlyValueWrapValidatorClsMethod.__call__T  r~   r5   N)r9   r   r|   r   r1   (core_schema.ValidatorFunctionWrapHandlerr=   r   r   rF   r5   r3   r   r   S  s    rr5   r   c                  (    e Zd Z	 	 	 	 	 	 	 	 	 	 ddZy)_V2WrapValidatorClsMethodc                    y r`   rF   r/   r9   r|   r1   rV   s        r3   r}   z"_V2WrapValidatorClsMethod.__call__W  s     r5   N)
r9   r   r|   r   r1   r   rV   r   r=   r   r   rF   r5   r3   r   r   V  s7    		 	 >		
 2	 	r5   r   r   _PartialClsOrStaticMethod"_V2BeforeAfterOrPlainValidatorType)bound_V2WrapValidatorType)rK   r#   rr   rh   FieldValidatorModes.)check_fieldsrI   c                   y r`   rF   r$   r&   r   rI   fieldss        r3   field_validatorr   y  s     >Ar5   c                   y r`   rF   r   s        r3   r   r     s	     Z]r5   )r&   r   c                   y r`   rF   )r$   r&   r   r   s       r3   r   r     s	     Z]r5   r#   )r&   r   rI   c              
   t        | t              rt        dd      dvrt        urt        dd      t        u rdk(  rt        | gt        d D              st        d	d
      	 	 	 	 dfd}|S )aO  !!! abstract "Usage Documentation"
        [field validators](../concepts/validators.md#field-validators)

    Decorate methods on the class indicating that they should be used to validate fields.

    Example usage:
    ```python
    from typing import Any

    from pydantic import (
        BaseModel,
        ValidationError,
        field_validator,
    )

    class Model(BaseModel):
        a: str

        @field_validator('a')
        @classmethod
        def ensure_foobar(cls, v: Any):
            if 'foobar' not in v:
                raise ValueError('"foobar" not found in a')
            return v

    print(repr(Model(a='this is foobar good')))
    #> Model(a='this is foobar good')

    try:
        Model(a='snap')
    except ValidationError as exc_info:
        print(exc_info)
        '''
        1 validation error for Model
        a
          Value error, "foobar" not found in a [type=value_error, input_value='snap', input_type=str]
        '''
    ```

    For more in depth examples, see [Field Validators](../concepts/validators.md#field-validators).

    Args:
        field: The first field the `field_validator` should be called on; this is separate
            from `fields` to ensure an error is raised if you don't pass at least one.
        *fields: Additional field(s) the `field_validator` should be called on.
        mode: Specifies whether to validate the fields before or after validation.
        check_fields: Whether to check that the fields actually exist on the model.
        json_schema_input_type: The input type of the function. This is only used to generate
            the appropriate JSON Schema (in validation mode) and can only specified
            when `mode` is either `'before'`, `'plain'` or `'wrap'`.

    Returns:
        A decorator that can be used to decorate a function to be used as a field_validator.

    Raises:
        PydanticUserError:
            - If `@field_validator` is used bare (with no fields).
            - If the args passed to `@field_validator` as fields are not strings.
            - If `@field_validator` applied to instance methods.
    z`@field_validator` should be used with fields and keyword arguments, not bare. E.g. usage should be `@validator('<field_name>', ...)`zvalidator-no-fieldscode)rK   rh   rr   z;`json_schema_input_type` can't be used when mode is set to zvalidator-input-typerh   c              3  <   K   | ]  }t        |t                y wr`   )
isinstancestr).0r$   s     r3   	<genexpr>z"field_validator.<locals>.<genexpr>  s     :%z%%:s   z`@field_validator` fields should be passed as separate string args. E.g. usage should be `@validator('<field_name_1>', '<field_name_2>', ...)`zvalidator-invalid-fieldsc                    t        j                  |       rt        dd      t        j                  |       } t        j                        }t        j
                  | |      S )Nz8`@field_validator` cannot be applied to instance methodszvalidator-instance-methodr   )r   r&   r   rI   )r   is_instance_method_from_sigr   %ensure_classmethod_based_on_signatureFieldValidatorDecoratorInfoPydanticDescriptorProxy)fdec_infor   r   rI   r&   s     r3   deczfield_validator.<locals>.dec  sg     2215#JQl 
 ==a@::<Xn
 221h??r5   )r   zHCallable[..., Any] | staticmethod[Any, Any] | classmethod[Any, Any, Any]r=   (_decorators.PydanticDescriptorProxy[Any])r   r   r   r   r   all)r$   r&   r   rI   r   r   s    ```` r3   r   r     s    H %&E&
 	
 ..3IQb3bI$R'
 	

 !22tw!$^V^F:6::Y+
 	
@S@	1@ @  Jr5   
_ModelType_ModelTypeCo)	covariantc                  &    e Zd ZdZ	 d	 	 	 	 	 ddZy)ModelWrapValidatorHandlerz]`@model_validator` decorated function handler argument type. This is used when `mode='wrap'`.Nc                    y r`   rF   )r/   r|   outer_locations      r3   r}   z"ModelWrapValidatorHandler.__call__  s     	r5   r`   )r|   r   r   zstr | int | Noner=   r   r@   rA   rB   rC   r}   rF   r5   r3   r   r     s+    g
 ,0 )
 
r5   r   c                  (    e Zd ZdZ	 	 	 	 	 	 	 	 ddZy)ModelWrapValidatorWithoutInfozA `@model_validator` decorated function signature.
    This is used when `mode='wrap'` and the function does not have info argument.
    c                    y r`   rF   r   s       r3   r}   z&ModelWrapValidatorWithoutInfo.__call__  s     r5   N)r9   type[_ModelType]r|   r   r1   %ModelWrapValidatorHandler[_ModelType]r=   r   r   rF   r5   r3   r   r     s2    		 	 7	 
	r5   r   c                  ,    e Zd ZdZ	 	 	 	 	 	 	 	 	 	 ddZy)ModelWrapValidatorzSA `@model_validator` decorated function signature. This is used when `mode='wrap'`.c                    y r`   rF   r   s        r3   r}   zModelWrapValidator.__call__,  s     r5   N)
r9   r   r|   r   r1   r   rV   zcore_schema.ValidationInfor=   r   r   rF   r5   r3   r   r   )  s:    ]

 
 7
 )
 

r5   r   c                       e Zd ZdZ	 	 	 	 ddZy)#FreeModelBeforeValidatorWithoutInfoA `@model_validator` decorated function signature.
    This is used when `mode='before'` and the function does not have info argument.
    c                    y r`   rF   )r/   r|   s     r3   r}   z,FreeModelBeforeValidatorWithoutInfo.__call__>  s     r5   N)r|   r   r=   r   r   rF   r5   r3   r   r   9  s     
  
r5   r   c                  $    e Zd ZdZ	 	 	 	 	 	 ddZy)ModelBeforeValidatorWithoutInfor   c                    y r`   rF   r{   s      r3   r}   z(ModelBeforeValidatorWithoutInfo.__call__M       r5   Nr   r   rF   r5   r3   r   r   H  s(      
r5   r   c                  $    e Zd ZdZ	 	 	 	 	 	 ddZy)FreeModelBeforeValidatorUA `@model_validator` decorated function signature. This is used when `mode='before'`.c                    y r`   rF   )r/   r|   rV   s      r3   r}   z!FreeModelBeforeValidator.__call__[  r   r5   N)r|   r   rV   r   r=   r   r   rF   r5   r3   r   r   X  s(    _
  . 
r5   r   c                  (    e Zd ZdZ	 	 	 	 	 	 	 	 ddZy)ModelBeforeValidatorr   c                    y r`   rF   r   s       r3   r}   zModelBeforeValidator.__call__i  s     r5   Nr   r   rF   r5   r3   r   r   f  s0    _		 	 .	 
	r5   r   c                     y r`   rF   r&   s    r3   model_validatorr          r5   c                     y r`   rF   r   s    r3   r   r     r   r5   c                     y r`   rF   r   s    r3   r   r     r   r5   c                     d fd}|S )a@  !!! abstract "Usage Documentation"
        [Model Validators](../concepts/validators.md#model-validators)

    Decorate model methods for validation purposes.

    Example usage:
    ```python
    from typing_extensions import Self

    from pydantic import BaseModel, ValidationError, model_validator

    class Square(BaseModel):
        width: float
        height: float

        @model_validator(mode='after')
        def verify_square(self) -> Self:
            if self.width != self.height:
                raise ValueError('width and height do not match')
            return self

    s = Square(width=1, height=1)
    print(repr(s))
    #> Square(width=1.0, height=1.0)

    try:
        Square(width=1, height=2)
    except ValidationError as e:
        print(e)
        '''
        1 validation error for Square
          Value error, width and height do not match [type=value_error, input_value={'width': 1, 'height': 2}, input_type=dict]
        '''
    ```

    For more in depth examples, see [Model Validators](../concepts/validators.md#model-validators).

    Args:
        mode: A required string literal that specifies the validation mode.
            It can be one of the following: 'wrap', 'before', or 'after'.

    Returns:
        A decorator that can be used to decorate a function to be used as a model validator.
    c                    dk7  rt        j                  |       } t        j                        }t        j                  | |      S )Nr#   r   )r   r   ModelValidatorDecoratorInfor   )r   r   r&   s     r3   r   zmodel_validator.<locals>.dec  s=    7?AA!DA::E221h??r5   )r   r   r=   r   rF   )r&   r   s   ` r3   r   r     s    b@ Jr5   AnyTypec                  L    e Zd ZdZedd       Zedd       Zej                  Zy)
InstanceOfu  Generic type for annotating a type that is an instance of a given class.

        Example:
            ```python
            from pydantic import BaseModel, InstanceOf

            class Foo:
                ...

            class Bar(BaseModel):
                foo: InstanceOf[Foo]

            Bar(foo=Foo())
            try:
                Bar(foo=42)
            except ValidationError as e:
                print(e)
                """
                [
                │   {
                │   │   'type': 'is_instance_of',
                │   │   'loc': ('foo',),
                │   │   'msg': 'Input should be an instance of Foo',
                │   │   'input': 42,
                │   │   'ctx': {'class': 'Foo'},
                │   │   'url': 'https://errors.pydantic.dev/0.38.0/v/is_instance_of'
                │   }
                ]
                """
            ```
        c                "    t         | |        f   S r`   )r   r9   items     r3   __class_getitem__zInstanceOf.__class_getitem__  s    T35[))r5   c                    ddl m} t        j                  t	        j
                  |      xs |      }	  ||      }t        j                  d |      |d<   t        j                  ||      S # |$ r |cY S w xY w)Nr   r\   c                     ||       S r`   rF   ra   s     r3   rd   z9InstanceOf.__get_pydantic_core_schema__.<locals>.<lambda>  re   r5   rf   r)   r^   )python_schemajson_schema)ri   r]   r   is_instance_schemar   
get_originrk   json_or_python_schema)r9   sourcer1   r]   instance_of_schemaoriginal_schemas         r3   r4   z'InstanceOf.__get_pydantic_core_schema__	  s    > "-!?!?	@T@TU[@\@f`f!gx")&/ 7B6e6e.7"?3 #88GYgvww 1 *))*s   A. .A87A8N)r   r   r=   r   r   r   r1   r   r=   r>   )	r@   rA   rB   rC   rE   r   r4   object__hash__rF   r5   r3   r   r     s=    	@ 
	* 
	* 
	x 
	x& ??r5   r   c                  B    e Zd ZdZddZedd       Zej                  Zy)SkipValidationa  If this is applied as an annotation (e.g., via `x: Annotated[int, SkipValidation]`), validation will be
            skipped. You can also use `SkipValidation[int]` as a shorthand for `Annotated[int, SkipValidation]`.

        This can be useful if you want to use a type annotation for documentation/IDE/type-checking purposes,
        and know that it is safe to skip validation for one or more of the fields.

        Because this converts the validation schema to `any_schema`, subsequent annotation-applied transformations
        may not have the expected effects. Therefore, when used, this annotation should generally be the final
        annotation applied to a type.
        c                (    t         |t               f   S r`   )r   r   r   s     r3   r   z SkipValidation.__class_getitem__1  s    T>#3344r5   c                   t        j                         5  t        j                  dt                ||      d d d        dfdgi}t	        j
                  |t	        j                  d             S # 1 sw Y   >xY w)Nignore pydantic_js_annotation_functionsc                     |      S r`   rF   )_crc   r   s     r3   rd   z=SkipValidation.__get_pydantic_core_schema__.<locals>.<lambda>9  s    1_K] r5   c                     ||       S r`   rF   ra   s     r3   rd   z=SkipValidation.__get_pydantic_core_schema__.<locals>.<lambda>=  re   r5   r   )metadatar^   )warningscatch_warningssimplefilterr   r   
any_schemark   )r9   r   r1   r   r   s       @r3   r4   z+SkipValidation.__get_pydantic_core_schema__4  sw    ((* 2%%h0DE")&/2 ;=]<^_H))!)MM. 	2 2s   #A66A?N)r   r   r=   r   r   )	r@   rA   rB   rC   r   rE   r4   r   r   rF   r5   r3   r   r   $  s+    			5 

	 

	 ??r5   r   
_FromTypeTc                       e Zd ZdZddZddZy)
ValidateAsa  A helper class to validate a custom type from a type that is natively supported by Pydantic.

    Args:
        from_type: The type natively supported by Pydantic to use to perform validation.
        instantiation_hook: A callable taking the validated type as an argument, and returning
            the populated custom type.

    Example:
        ```python {lint="skip"}
        from typing import Annotated

        from pydantic import BaseModel, TypeAdapter, ValidateAs

        class MyCls:
            def __init__(self, a: int) -> None:
                self.a = a

            def __repr__(self) -> str:
                return f"MyCls(a={self.a})"

        class Model(BaseModel):
            a: int


        ta = TypeAdapter(
            Annotated[MyCls, ValidateAs(Model, lambda v: MyCls(a=v.a))]
        )

        print(ta.validate_python({'a': 1}))
        #> MyCls(a=1)
        ```
    c                    || _         || _        y r`   )	from_typeinstantiation_hook)r/   r   r   s      r3   __init__zValidateAs.__init__j  s    ""4r5   c                h     || j                         }t        j                  | j                  |      S )Nr(   )r   r   r.   r   )r/   r   r1   r)   s       r3   r4   z'ValidateAs.__get_pydantic_core_schema__n  s/    (;;##
 	
r5   N)r   zCallable[[_FromTypeT], Any]r   ztype[_FromTypeT]r=   Noner   )r@   rA   rB   rC   r   r4   rF   r5   r3   r   r   G  s    D5
r5   r   rF   )r$   r   r   r   r&   Literal['wrap']r   bool | NonerI   r   r=   z6Callable[[_V2WrapValidatorType], _V2WrapValidatorType])r$   r   r   r   r&   zLiteral['before', 'plain']r   r  rI   r   r=   RCallable[[_V2BeforeAfterOrPlainValidatorType], _V2BeforeAfterOrPlainValidatorType])
r$   r   r   r   r&   Literal['after']r   r  r=   r  )r$   r   r   r   r&   r   r   r  rI   r   r=   zCallable[[Any], Any])r&   r  r=   z|Callable[[_AnyModelWrapValidator[_ModelType]], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]])r&   zLiteral['before']r=   zrCallable[[_AnyModelBeforeValidator], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]])r&   r  r=   z}Callable[[_AnyModelAfterValidator[_ModelType]], _decorators.PydanticDescriptorProxy[_decorators.ModelValidatorDecoratorInfo]])r&   z"Literal['wrap', 'before', 'after']r=   r   )VrC   
__future__r   _annotationsdataclassessysr   	functoolsr   typesr   typingr   r   r   r	   r
   r   r   r   r   pydantic_corer   r   typing_extensionsr   r   	_internalr   r   r   annotated_handlersr   errorsr   r   version_infor   inspect_validatorr*   	dataclass
slots_truer   rH   rZ   rp   ry   r   r   r   r+   r-   _V2Validatorrs   ru   _V2WrapValidatorrE   staticmethodr   rD   r   r   r   r   r   r   ValidatorFunctionWrapHandlerr   r   r   r   r   r   r   ModelAfterValidatorWithoutInfoValidationInfoModelAfterValidator_AnyModelWrapValidator_AnyModelBeforeValidator_AnyModelAfterValidatorr   r   r   r   r   r   rF   r5   r3   <module>r      s   H 2  
  #  c c c 8 - B B 4 % *g* 22  EdE&9&D&DE9( 9( F9(x EdE&9&D&DE?
 ?
 F?
D EdE&9&D&DE`
 `
 F`
F EdE&9&D&DEG
 G
 FG
T @x @g gs8 sH  --$++	-L !11(//	1 ,1S#s]1K\Z]_bZbMcersvew1w+xyx)0,L";;<*& ##9GWYrGrAst!()K!L Y L 
 !$"%AA A 	A
 A  A <A 
A 
 !$"%]] ] %	]
 ]  ] X] 
] 

 ! #]] ] 	]
 ] X] 
] !( $"3ll l 	l
 l  l l^ \"
~6	 H H(S_J` 	HZ$8 "*-  ( h  x 8  "*:,
*B!C  
K,F,Fs,KLjXY  Z1*=?\]g?hhi  24WYxx    3J ?A_`jAk kl  

 
 

 
 

 
8
,8 	8v )
 7C<(J [<0;;<9# 9# =9#x w|,N [<0;;<# # =#> \"
,
 ,
r5   