Class PlainSerializer

pydantic/functional_serializers.py:20–86

Plain serializers use a function to modify the output of serialization. This is particularly helpful when you want to customize the serialization for annotated types. Consider an input of `list`, which will be serialized into a space-delimited string. ```python from typing import A

@dataclasses.dataclass(**_internal_dataclass.slots_true, frozen=True)
class PlainSerializer:
    """Plain serializers use a function to modify the output of serialization.

    This is particularly helpful when you want to customize the serialization for annotated types.
    Consider an input of `list`, which will be serialized into a space-delimited string.

    ```python
    from typing import Annotated

    from pydantic import BaseModel, PlainSerializer

    CustomStr = Annotated[
        list, PlainSerializer(lambda x: ' '.join(x), return_type=str)
    ]

    class StudentModel(BaseModel):
        courses: CustomStr

    student = StudentModel(courses=['Math', 'Chemistry', 'English'])
    print(student.model_dump())
    #> {'courses': 'Math Chemistry English'}
    ```

    Attributes:
        func: The serializer function.
        return_type: The return type for the function. If omitted it will be inferred from the type annotation.
        when_used: Determines when this serializer should be used. Accepts a string with values `'always'`,
            `'unless-none'`, `'json'`, and `'json-unless-none'`. Defaults to 'always'.
    """

    func: core_schema.SerializerFunction
    return_type: Any = PydanticUndefined
    when_used: WhenUsed = 'always'

    def __get_pydantic_core_schema__(self, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema:
        """Gets the Pydantic core schema.

        Args:
            source_type: The source type.
            handler: The `GetCoreSchemaHandler` instance.

        Returns:
            The Pydantic core schema.
        """
        schema = handler(source_type)
        if self.return_type is not PydanticUndefined:
            return_type = self.return_type
        else:
            try:
                # Do not pass in globals as the function could be defined in a different module.
                # Instead, let `get_callable_return_type` infer the globals to use, but still pass
                # in locals that may contain a parent/rebuild namespace:
                return_type = _decorators.get_callable_return_type(
                    self.func,
                    localns=handler._get_types_namespace().locals,
                )
            except NameError as e:
                raise PydanticUndefinedAnnotation.from_name_error(e) from e