{
  "performanceTests" : [ {
    "testId" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslConfigurationPerformanceTest.configure",
    "groups" : [ {
      "testProject" : "largeEmptyMultiProjectDeclarativeDsl",
      "coverage" : {
        "per_commit" : [ "linux", "macOs", "windows" ]
      }
    } ]
  }, {
    "testId" : "org.gradle.performance.experiment.declarativedsl.DeclarativeDslFirstUsePerformanceTest.clean checkout",

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"}

        api("com.thoughtworks.qdox:qdox:2.0.3")
        api("com.uwyn:jhighlight:1.0")
        api("com.vladsch.flexmark:flexmark-all:0.34.60") {
            because("Higher versions tested are either incompatible (0.62.2) or bring additional unwanted dependencies (0.36.8)")
        }
        api("org.apache.pdfbox:pdfbox:2.0.24") {
            because("Flexmark 0.34.60 brings in a vulnerable version of pdfbox")

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.

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.