Class WrapValidator

pydantic/functional_validators.py:257–328

!!! 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_sch

@dataclasses.dataclass(frozen=True, **_internal_dataclass.slots_true)
class WrapValidator:
    """!!! 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
    ```
    """

    func: core_schema.NoInfoWrapValidatorFunction | core_schema.WithInfoWrapValidatorFunction
    json_schema_input_type: Any = PydanticUndefined

    def __get_pydantic_core_schema__(self, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema:
        schema = handler(source_type)
        input_schema = (
            None
            if self.json_schema_input_type is PydanticUndefined
            else handler.generate_schema(self.json_schema_input_type)
        )

        info_arg = _inspect_validator(self.func, mode='wrap', type='field')
        if info_arg:
            func = cast(core_schema.WithInfoWrapValidatorFunction, self.func)
            return core_schema.with_info_wrap_validator_function(
                func,
                schema=schema,
                json_schema_input_schema=input_schema,
            )