So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.

And of course, it supports the same:

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

    encoded as JSON before it is sent to the client.

    You can also use it yourself, for example to convert objects before saving them
    in a database that supports only JSON.

    Read more about it in the
    [FastAPI docs for JSON Compatible Encoder](https://fastapi.tiangolo.com/tutorial/encoder/).
    """
    custom_encoder = custom_encoder or {}
    if custom_encoder:

* ⬆️ Upgrade OpenAI model for translations to gpt-5.2. PR [#14579](https://github.com/fastapi/fastapi/pull/14579) by [@tiangolo](https://github.com/tiangolo).

## 0.126.0

### Upgrades

* ➖ Drop support for Pydantic v1, keeping short temporary support for Pydantic v2's `pydantic.v1`. PR [#14575](https://github.com/fastapi/fastapi/pull/14575) by [@tiangolo](https://github.com/tiangolo).
    * The minimum version of Pydantic installed is now `pydantic >=2.7.0`.

    # to support it as a first class "feature"
    assert is_bytes_sequence_annotation(Union[list[str], list[bytes]])


def test_is_uploadfile_sequence_annotation():
    # For coverage
    # TODO: in theory this would allow declaring types that could be lists of UploadFile
    # and other types, but I'm not even sure it's a good idea to support it as a first
    # class "feature"

            """
            OpenAPI-specific examples.

            It will be added to the generated OpenAPI (e.g. visible at `/docs`).

            Swagger UI (that provides the `/docs` interface) has better support for the
            OpenAPI-specific examples than the JSON Schema `examples`, that's the main
            use case for this.

            Read more about it in the

Make sure you evaluate if the **benefits** for your use case compensate the **drawbacks**. 🤓

///

## GraphQL Libraries { #graphql-libraries }

Here are some of the **GraphQL** libraries that have **ASGI** support. You could use them with **FastAPI**:

* <a href="https://strawberry.rocks/" class="external-link" target="_blank">Strawberry</a> 🍓

* **Fast to code**: Increase the speed to develop features by about 200% to 300%. *
* **Fewer bugs**: Reduce about 40% of human (developer) induced errors. *
* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
* **Easy**: Designed to be easy to use and learn. Less time reading docs.

    )

RequiredParam = PydanticUndefined
Undefined = PydanticUndefined
UndefinedType = PydanticUndefinedType
evaluate_forwardref = eval_type_lenient
Validator = Any

# TODO: remove when dropping support for Pydantic < v2.12.3
_Attrs = {
    "default": ...,
    "default_factory": None,
    "alias": None,
    "alias_priority": None,
    "validation_alias": None,
    "serialization_alias": None,
    "title": None,

* **Fast to code**: Increase the speed to develop features by about 200% to 300%. *
* **Fewer bugs**: Reduce about 40% of human (developer) induced errors. *
* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
* **Easy**: Designed to be easy to use and learn. Less time reading docs.

Pydantic unterstützt das Lesen dieser Dateitypen mithilfe einer externen Bibliothek. Weitere Informationen finden Sie unter <a href="https://docs.pydantic.dev/latest/concepts/pydantic_settings/#dotenv-env-support" class="external-link" target="_blank">Pydantic Settings: Dotenv (.env) support</a>.

/// tip | Tipp

Damit das funktioniert, müssen Sie `pip install python-dotenv` ausführen.

///

### Die `.env`-Datei { #the-env-file }