因此，即便上述代码没有显式使用 Pydantic，FastAPI 仍会使用 Pydantic 把标准数据类转换为 Pydantic 数据类（`dataclasses`）。

并且，它仍然支持以下功能：

* 数据验证
* 数据序列化
* 数据存档等

数据类的和运作方式与 Pydantic 模型相同。实际上，它的底层使用的也是 Pydantic。

/// info | "说明"

注意，数据类不支持 Pydantic 模型的所有功能。

因此，开发时仍需要使用 Pydantic 模型。

但如果数据类很多，这一技巧能给 FastAPI 开发 Web API 增添不少助力。🤓

///

## `response_model` 使用数据类

在 `response_model` 参数中使用 `dataclasses`：

If you have a group of **query parameters** that are related, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

## Query Parameters with a Pydantic Model

If you use <a href="https://www.jetbrains.com/pycharm/" class="external-link" target="_blank">PyCharm</a> as your editor, you can use the <a href="https://github.com/koxudaxi/pydantic-pycharm-plugin/" class="external-link" target="_blank">Pydantic PyCharm Plugin</a>.

It improves editor support for Pydantic models, with:

* auto-completion
* type checks
* refactoring
* searching
* inspections

///

## Use the model

/// tip | "팁"

만약 <a href="https://www.jetbrains.com/pycharm/" class="external-link" target="_blank">PyCharm</a>를 편집기로 사용한다면, <a href="https://github.com/koxudaxi/pydantic-pycharm-plugin/" class="external-link" target="_blank">Pydantic PyCharm Plugin</a>을 사용할 수 있습니다.

다음 사항을 포함해 Pydantic 모델에 대한 편집기 지원을 향상시킵니다:

* 자동 완성
* 타입 확인
* 리팩토링
* 검색
* 점검

///

## 모델 사용하기

함수 안에서 모델 객체의 모든 어트리뷰트에 직접 접근 가능합니다:

## Pydantic `Settings`

Glücklicherweise bietet Pydantic ein großartiges Werkzeug zur Verarbeitung dieser Einstellungen, die von Umgebungsvariablen stammen, mit <a href="https://docs.pydantic.dev/latest/concepts/pydantic_settings/" class="external-link" target="_blank">Pydantic: Settings Management</a>.

### `pydantic-settings` installieren

//// tab | Pydantic v2

```Python hl_lines="17-22  24"
{!> ../../docs_src/path_operation_advanced_configuration/tutorial007.py!}
```

////

//// tab | Pydantic v1

```Python hl_lines="17-22  24"

        # TODO: remove when deprecating Pydantic v1
        "Param(Ellipsis)",
    )


def test_param_repr_number():
    assert repr(Param(1)) == "Param(1)"


def test_param_repr_list():
    assert repr(Param([])) == "Param([])"


def test_path_repr():
    assert repr(Path()) == IsOneOf(
        "Path(PydanticUndefined)",
        # TODO: remove when deprecating Pydantic v1
        "Path(Ellipsis)",
    )

    "name": "Foo",
    "price": 50.2
}
```

/// info

In Pydantic v1 hieß diese Methode `.dict()`, in Pydantic v2 wurde sie deprecated (aber immer noch unterstützt) und in `.model_dump()` umbenannt.

Die Beispiele hier verwenden `.dict()` für die Kompatibilität mit Pydantic v1, Sie sollten jedoch stattdessen `.model_dump()` verwenden, wenn Sie Pydantic v2 verwenden können.

///

/// info

    "price": 50.2
}
```

/// info

In Pydantic v1 the method was called `.dict()`, it was deprecated (but still supported) in Pydantic v2, and renamed to `.model_dump()`.

The examples here use `.dict()` for compatibility with Pydantic v1, but you should use `.model_dump()` instead if you can use Pydantic v2.

///

/// info

* 100 % Testabdeckung.
* 100 % Typen annotierte Codebasis.

## Pydantic's Merkmale

**FastAPI** ist vollkommen kompatibel (und basiert auf) <a href="https://docs.pydantic.dev/" class="external-link" target="_blank"><strong>Pydantic</strong></a>. Das bedeutet, wenn Sie eigenen Pydantic Quellcode haben, funktioniert der.