Dessa forma, seu esquema aparecerá na interface de documentação da API:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses em Estruturas de Dados Aninhadas { #dataclasses-in-nested-data-structures }

Você também pode combinar `dataclasses` com outras anotações de tipo para criar estruturas de dados aninhadas.

This way, its schema will show up in the API docs user interface:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses in Nested Data Structures { #dataclasses-in-nested-data-structures }

You can also combine `dataclasses` with other type annotations to make nested data structures.

def test_nested_router():
    app = FastAPI()

    router = APIRouter(prefix="/nested")

    @router.get("/test")
    async def test(var: Annotated[str, Query()] = "bar"):
        return {"foo": var}

    app.include_router(router)

    client = TestClient(app)

    response = client.get("/nested/test")
    assert response.status_code == 200
    assert response.json() == {"foo": "bar"}

De esta manera, su esquema aparecerá en la interfaz de usuario de la documentación de la API:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses en Estructuras de Datos Anidadas { #dataclasses-in-nested-data-structures }

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

Таким образом, его схема появится в интерфейсе документации API:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses во вложенных структурах данных { #dataclasses-in-nested-data-structures }

Вы также можете комбинировать `dataclasses` с другими аннотациями типов, чтобы создавать вложенные структуры данных.

Auf diese Weise wird deren Schema in der Benutzeroberfläche der API-Dokumentation angezeigt:

<img src="/img/tutorial/dataclasses/image01.png">

## Datenklassen in verschachtelten Datenstrukturen { #dataclasses-in-nested-data-structures }

Sie können `dataclasses` auch mit anderen Typannotationen kombinieren, um verschachtelte Datenstrukturen zu erstellen.

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.

* Editor support, including:
    * Completion.
    * Type checks.
* Validation of data:
    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.

    "docs_src/dependencies/tutorial013_an_py310.py",  # temporary code example?
    "docs_src/dependencies/tutorial014_an_py310.py",  # temporary code example?
    # Pydantic v1 migration, no longer tested
    "docs_src/pydantic_v1_in_v2/tutorial001_an_py310.py",
    "docs_src/pydantic_v1_in_v2/tutorial001_an_py39.py",
    "docs_src/pydantic_v1_in_v2/tutorial002_an_py310.py",

* 📝 Fix example code with sets in Tutorial - Body - Nested Models 3. PR [#2054](https://github.com/tiangolo/fastapi/pull/2054) by [@hitrust](https://github.com/hitrust).
* 📝 Fix example code with sets in Tutorial - Body - Nested Models 2. PR [#2053](https://github.com/tiangolo/fastapi/pull/2053) by [@hitrust](https://github.com/hitrust).