### `response_model` Priority

If you declare both a return type and a `response_model`, the `response_model` will take priority and be used by FastAPI.

### `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!}
```

### Приоритет `response_model`

Если одновременно указать аннотацию типа для ответа функции и параметр `response_model` - последний будет иметь больший приоритет и FastAPI будет использовать именно его.

### `response_model`-Priorität

Wenn sowohl Rückgabetyp als auch `response_model` deklariert sind, hat `response_model` die Priorität und wird von FastAPI bevorzugt verwendet.

    👉 ✔ `response_model_by_alias` 👈 👷 ➡.

=== "🐍 3️⃣.6️⃣ & 🔛"

    ```Python hl_lines="31  37"
    {!> ../../../docs_src/response_model/tutorial005.py!}
    ```

=== "🐍 3️⃣.1️⃣0️⃣ & 🔛"

    ```Python hl_lines="29  35"
    {!> ../../../docs_src/response_model/tutorial005_py310.py!}
    ```

!!! tip

```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

    {!> ../../../docs_src/extra_models/tutorial001_py310.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="9  11  16  22  24  29-30  33-35  40-41"
    {!> ../../../docs_src/extra_models/tutorial001.py!}
    ```

!!! info
    In Pydantic v1 hieß diese Methode `.dict()`, in Pydantic v2 wurde sie deprecated (aber immer noch unterstützt) und in `.model_dump()` umbenannt.

# Extra Models

Continuing with the previous example, it will be common to have more than one related model.

This is especially the case for user models, because:

* The **input model** needs to be able to have a password.
* The **output model** should not have a password.
* The **database model** would probably need to have a hashed password.

!!! danger
    Never store user's plaintext passwords. Always store a "secure hash" that you can then verify.