@field_serializer("a_uuid")
        def serialize_a_uuid(self, v):
            return str(v)

    @app.get("/get_custom_class")
    def return_some_user():
        # Test that the fix also works for custom pydantic classes
        return SomeCustomClass(a_uuid=MyUuid("b8799909-f914-42de-91bc-95c819218d01"))

    client = TestClient(app)

    with client:
        response_simple = client.get("/fast_uuid")

                                    "normal": {
                                        "summary": "A normal example",
                                        "description": "A **normal** item works correctly.",
                                        "value": {
                                            "name": "Foo",
                                            "description": "A very nice Item",

register_toolchains("@rules_ml_toolchain//cc:linux_aarch64_linux_aarch64_cuda")

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

* 💚 Fix disabling install of Material for MkDocs Insiders in forks, strike 1 ⚾. PR [#2340](https://github.com/tiangolo/fastapi/pull/2340) by [@tiangolo](https://github.com/tiangolo).
* 🐛 Fix disabling Material for MkDocs Insiders install in forks. PR [#2339](https://github.com/tiangolo/fastapi/pull/2339) by [@tiangolo](https://github.com/tiangolo).

        »»»

3.2) Do not apply rule 3 to the untranslated part of the heading inside curly brackets, which you shall not translate.


### German instructions, when to use and when not to use hyphens in words (written in first person, which is you)

#     mkl:          Enable full mkl support.
#     nogcp:        Disable GCS support.
#     nonccl:       Disable nccl support.
#
#
# Remote build execution options (only configured to work with TF team projects for now.)
#     rbe_base:                       General RBE options shared by all flavors.
#     rbe_linux:                      General RBE options used on all linux builds.

    """


class FastAPIDeprecationWarning(UserWarning):
    """
    A custom deprecation warning as DeprecationWarning is ignored
    Ref: https://sethmlarson.dev/deprecations-via-warnings-dont-work-for-python-libraries

        or hasattr(origin, "__get_pydantic_core_schema__")
    )


def field_annotation_is_scalar(annotation: Any) -> bool:
    # handle Ellipsis here to make tuple[int, ...] work nicely
    return annotation is Ellipsis or not field_annotation_is_complex(annotation)


def field_annotation_is_scalar_sequence(annotation: Union[type[Any], None]) -> bool:
    origin = get_origin(annotation)

        ```
        »»»

If there is an existing translation and its Mermaid diagram is in sync with the Mermaid diagram in the English source, except a few translated words, then use the Mermaid diagram of the existing translation. The human editor of the translation translated these words in the Mermaid diagram. Keep these translations, do not revert them back to the English source.

Example:

    Source (English):

        «««