"paths": {
            "/authors/{author_id}/items/": {
                "post": {
                    "summary": "Create Author Items",
                    "operationId": "create_author_items_authors__author_id__items__post",
                    "parameters": [
                        {
                            "required": True,
                            "schema": {"title": "Author Id", "type": "string"},

@dataclass
class Author:
    name: str
    items: list[Item] = field(default_factory=list)  # (3)


app = FastAPI()


@app.post("/authors/{author_id}/items/", response_model=Author)  # (4)
async def create_author_items(author_id: str, items: list[Item]):  # (5)
    return {"name": author_id, "items": items}  # (6)


@app.get("/authors/", response_model=list[Author])  # (7)

@dataclass
class Author:
    name: str
    items: list[Item] = field(default_factory=list)  # (3)


app = FastAPI()


@app.post("/authors/{author_id}/items/", response_model=Author)  # (4)
async def create_author_items(author_id: str, items: list[Item]):  # (5)
    return {"name": author_id, "items": items}  # (6)


@app.get("/authors/", response_model=list[Author])  # (7)

1. Wir importieren `field` weiterhin von Standard-`dataclasses`.

2. `pydantic.dataclasses` ist ein direkter Ersatz für `dataclasses`.

3. Die Datenklasse `Author` enthält eine Liste von `Item`-Datenklassen.

4. Die Datenklasse `Author` wird im `response_model`-Parameter verwendet.

5. Sie können andere Standard-Typannotationen mit Datenklassen als Requestbody verwenden.

1. We still import `field` from standard `dataclasses`.

2. `pydantic.dataclasses` is a drop-in replacement for `dataclasses`.

3. The `Author` dataclass includes a list of `Item` dataclasses.

4. The `Author` dataclass is used as the `response_model` parameter.

5. You can use other standard type annotations with dataclasses as the request body.

1. Ainda importamos `field` das `dataclasses` padrão.

2. `pydantic.dataclasses` é um substituto direto para `dataclasses`.

3. A dataclass `Author` inclui uma lista de dataclasses `Item`.

4. A dataclass `Author` é usada como o parâmetro `response_model`.

5. Você pode usar outras anotações de tipo padrão com dataclasses como o corpo da requisição.

    Neste caso, é uma lista de dataclasses `Item`.

1. Todavía importamos `field` de los `dataclasses` estándar.

2. `pydantic.dataclasses` es un reemplazo directo para `dataclasses`.

3. El dataclass `Author` incluye una lista de dataclasses `Item`.

4. El dataclass `Author` se usa como el parámetro `response_model`.

5. Puedes usar otras anotaciones de tipos estándar con dataclasses como el request body.

    En este caso, es una lista de dataclasses `Item`.

2. 使用 `pydantic.dataclasses` 直接替换 `dataclasses`；

3. `Author` 数据类包含 `Item` 数据类列表；

4. `Author` 数据类用于 `response_model` 参数；

5. 其它带有数据类的标准类型注解也可以作为请求体；

    本例使用的是 `Item` 数据类列表；

6. 这行代码返回的是包含 `items` 的字典，`items` 是数据类列表；

    FastAPI 仍能把数据<abbr title="把数据转换为可以传输的格式">序列化</abbr>为 JSON；

7. 这行代码中，`response_model` 的类型注解是 `Author` 数据类列表；

    再一次，可以把 `dataclasses` 与标准类型注解一起使用；

1. Мы по-прежнему импортируем `field` из стандартных `dataclasses`.

2. `pydantic.dataclasses` — полностью совместимая замена (drop-in replacement) для `dataclasses`.

3. Dataclass `Author` содержит список dataclass `Item`.

4. Dataclass `Author` используется в параметре `response_model`.

5. Вы можете использовать и другие стандартные аннотации типов вместе с dataclasses в качестве тела запроса.

```

</div>

That's it! Now you can access your app at that URL. ✨

#### About FastAPI Cloud

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It streamlines the process of **building**, **deploying**, and **accessing** an API with minimal effort.