# to build TensorFlow. Look at ci/official/envs to find which types of jobs
# push to the cache.  For macOS, use --config=tf_public_macos_cache
common:tf_public_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/january2024" --remote_upload_local_results=false
# Cache pushes are limited to TF's CI system.

También puedes combinar `dataclasses` con otras anotaciones de tipos para crear estructuras de datos anidadas.

En algunos casos, todavía podrías tener que usar la versión de `dataclasses` de Pydantic. Por ejemplo, si tienes errores con la documentación de la API generada automáticamente.

///

## Aprende Más { #learn-more }

Puedes aprender más sobre **GraphQL** en la <a href="https://graphql.org/" class="external-link" target="_blank">documentación oficial de GraphQL</a>.

        by_alias: bool = True,
        exclude_unset: bool = False,
        exclude_defaults: bool = False,
        exclude_none: bool = False,
    ) -> Any:
        # What calls this code passes a value that already called
        # self._type_adapter.validate_python(value)
        return self._type_adapter.dump_python(
            value,
            mode=mode,
            include=include,

        examples: Optional[list[Any]] = None,
        example: Annotated[
            Optional[Any],
            deprecated(
                "Deprecated in OpenAPI 3.1.0 that now uses JSON Schema 2020-12, "
                "although still supported. Use examples instead."
            ),
        ] = _Unset,
        openapi_examples: Optional[dict[str, Example]] = None,

    print("Pushing branch")
    subprocess.run(["git", "push", "origin", branch_name], check=True)
    print("Creating PR")
    g = Github(github_token)
    gh_repo = g.get_repo(github_repository)
    body = (
        message
        + "\n\nThis PR was created automatically using LLMs."
        + f"\n\nIt uses the prompt file https://github.com/fastapi/fastapi/blob/master/docs/{language}/llm-prompt.md."

            Example values for this field.
            """
        ),
    ] = None,
    example: Annotated[
        Optional[Any],
        deprecated(
            "Deprecated in OpenAPI 3.1.0 that now uses JSON Schema 2020-12, "
            "although still supported. Use examples instead."
        ),
    ] = _Unset,
    openapi_examples: Annotated[
        Optional[dict[str, Example]],
        Doc(
            """

7. Here the `response_model` is using a type annotation of a list of `Author` dataclasses.

    Again, you can combine `dataclasses` with standard type annotations.

8. Notice that this *path operation function* uses regular `def` instead of `async def`.

    As always, in FastAPI you can combine `def` and `async def` as needed.

</p>
<p align="center">
<a href="https://github.com/fastapi/fastapi/actions?query=workflow%3ATest+event%3Apush+branch%3Amaster" target="_blank">
    <img src="https://github.com/fastapi/fastapi/actions/workflows/test.yml/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">

## 0.120.0

There are no major nor breaking changes in this release. ☕️

The internal reference documentation now uses `annotated_doc.Doc` instead of `typing_extensions.Doc`, this adds a new (very small) dependency on [`annotated-doc`](https://github.com/fastapi/annotated-doc), a package made just to provide that `Doc` documentation utility class.