### `response_model_include` 和 `response_model_exclude`

你还可以使用*路径操作装饰器*的 `response_model_include` 和 `response_model_exclude` 参数。

它们接收一个由属性名称 `str` 组成的 `set` 来包含（忽略其他的）或者排除（包含其他的）这些属性。

如果你只有一个 Pydantic 模型，并且想要从输出中移除一些数据，则可以使用这种快捷方法。

!!! tip
    但是依然建议你使用上面提到的主意，使用多个类而不是这些参数。

```Python hl_lines="9 11 16"
{!../../../docs_src/response_model/tutorial003.py!}
```

ここでは、*path operation関数*がパスワードを含む同じ入力ユーザーを返しているにもかかわらず:

```Python hl_lines="24"
{!../../../docs_src/response_model/tutorial003.py!}
```

...`response_model`を`UserOut`と宣言したことで、パスワードが含まれていません:

```Python hl_lines="22"
{!../../../docs_src/response_model/tutorial003.py!}
```

```Python hl_lines="9  11  16"
{!../../../docs_src/response_model/tutorial003.py!}
```

여기서 *경로 작동 함수*가 비밀번호를 포함하는 동일한 입력 사용자를 반환할지라도:

```Python hl_lines="24"
{!../../../docs_src/response_model/tutorial003.py!}
```

...`response_model`을 `UserOut` 모델로 선언했기 때문에 비밀번호를 포함하지 않습니다:

```Python hl_lines="22"
{!../../../docs_src/response_model/tutorial003.py!}
```

            return name

    async def get_model_c() -> ModelC:
        return ModelC(username="test-user", password="test-password")

    @app.get("/model/{name}", response_model=ModelA)
    async def get_model_a(name: str, model_c=Depends(get_model_c)):
        return {"name": name, "description": "model-a-desc", "foo": model_c}

    client = TestClient(app)
    return client


@needs_pydanticv2

            "field (e.g. Union[Response, dict, None]) you can disable generating the "
            "response model from the type annotation with the path operation decorator "
            "parameter response_model=None. Read more: "
            "https://fastapi.tiangolo.com/tutorial/response-model/"
        ) from None


def create_cloned_field(
    field: ModelField,
    *,

But you are not restricted to using some specific data model, class or type.

Do you want to have an `id` and `email` and not have any `username` in your model? Sure. You can use these same tools.

Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

```Python hl_lines="1  7-13  19"
{!../../../docs_src/dataclasses/tutorial002.py!}
```

The dataclass will be automatically converted to a Pydantic dataclass.

## Réponse supplémentaire avec `model`

Vous pouvez ajouter à votre décorateur de *paramètre de chemin* un paramètre `responses`.

Il prend comme valeur un `dict` dont les clés sont des codes HTTP pour chaque réponse, comme `200`, et la valeur de ces clés sont d'autres `dict` avec des informations pour chacun d'eux.

Chacun de ces `dict` de réponse peut avoir une clé `model`, contenant un modèle Pydantic, tout comme `response_model`.

            "content": {"application/x-yaml": {"schema": Item.model_json_schema()}},
            "required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.model_validate(data)
    except ValidationError as e:

@app.get("/items/{item_id}", response_model=Item)
async def read_main(item_id: str, x_token: str = Header()):
    if x_token != fake_secret_token:
        raise HTTPException(status_code=400, detail="Invalid X-Token header")
    if item_id not in fake_db:
        raise HTTPException(status_code=404, detail="Item not found")
    return fake_db[item_id]


@app.post("/items/", response_model=Item)