}
```

/// info | Información

Nota cómo la clave `images` ahora tiene una lista de objetos de imagen.

///

## Modelos anidados profundamente { #deeply-nested-models }

Puedes definir modelos anidados tan profundamente como desees:

{* ../../docs_src/body_nested_models/tutorial007_py310.py hl[7,12,18,21,25] *}

/// info | Información

# Body – Verschachtelte Modelle { #body-nested-models }

Mit **FastAPI** können Sie (dank Pydantic) beliebig tief verschachtelte Modelle definieren, validieren, dokumentieren und verwenden.

## Listen als Felder { #list-fields }

Sie können ein Attribut als Kindtyp definieren, zum Beispiel eine Python-`list`.

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

# Corpo - Modelos aninhados { #body-nested-models }

Com o **FastAPI**, você pode definir, validar, documentar e usar modelos arbitrariamente e profundamente aninhados (graças ao Pydantic).

## Campos do tipo Lista { #list-fields }

Você pode definir um atributo como um subtipo. Por exemplo, uma `list` do Python:

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

And it will be annotated / documented accordingly too.

## Nested Models { #nested-models }

Each attribute of a Pydantic model has a type.

But that type can itself be another Pydantic model.

So, you can declare deeply nested JSON "objects" with specific attribute names, types and validations.

All that, arbitrarily nested.

### Define a submodel { #define-a-submodel }

# Body - Вложенные модели { #body-nested-models }

С помощью **FastAPI** вы можете определять, валидировать, документировать и использовать модели произвольной глубины вложенности (благодаря Pydantic).

## Поля-списки { #list-fields }

Вы можете определить атрибут как подтип. Например, Python-тип `list`:

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

*PrivateKey { fipsSelfTest() fips140.RecordApproved() var seed [32]byte drbg.Read(seed[:]) priv := newPrivateKey(&seed, params44) fipsPCT(priv) return priv } func GenerateKey65() *PrivateKey { fipsSelfTest() fips140.RecordApproved() var seed [32]byte drbg.Read(seed[:]) priv := newPrivateKey(&seed, params65) fipsPCT(priv) return priv } func GenerateKey87() *PrivateKey { fipsSelfTest() fips140.RecordApproved() var seed [32]byte drbg.Read(seed[:]) priv := newPrivateKey(&seed, params87) fipsPCT(priv)...

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"}

    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <!--
    Some tests need reflective access to the internals of these packages. It is only the
    tests themselves and not the code being tested that needs that access, though there's no
    obvious way to ensure that.

    We could consider arranging things so that only the tests we know need this would get

    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <!--
    Some tests need reflective access to the internals of these packages. It is only the
    tests themselves and not the code being tested that needs that access, though there's no
    obvious way to ensure that.

    We could consider arranging things so that only the tests we know need this would get