### 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.

# Build state model

The Gradle daemon tracks state for various elements. These are arranged in a hierarchy:

```mermaid
  graph TD

  process["build process"]
  
  session["build session"]
  process --> session
  
  build_tree["build tree"]
  session --> build_tree
  
  build1["root build"]
  build_tree --> build1
  
  project1["root project"]
  build1 --> project1
  
  project2["project"]
  build1 --> project2

    {!> ../../../docs_src/response_model/tutorial001_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="17  22  24-27"
    {!> ../../../docs_src/response_model/tutorial001.py!}
    ```

!!! note "Hinweis"
    Beachten Sie, dass `response_model` ein Parameter der „Dekorator“-Methode ist (`get`, `post`, usw.). Nicht der *Pfadoperation-Funktion*, so wie die anderen Parameter.

    👉 ✔ `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

### `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。

import jetbrains.buildServer.configs.kotlin.Project
import model.CIBuildModel
import model.PerformanceTestBucketProvider
import model.PerformanceTestCoverage
import model.PerformanceTestProjectSpec
import model.Stage

abstract class PerformanceTestProject(model: CIBuildModel, val spec: PerformanceTestProjectSpec, val performanceTests: List<PerformanceTest>) : Project({
    this.id(spec.asConfigurationId(model))
    this.name = spec.asName()
}) {
    init {

```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!}
```

1)  Reference [TensorFlow Model Colab](https://colab.research.google.com/gist/ymodak/e96a4270b953201d5362c61c1e8b78aa/tensorflow-datasets.ipynb?authuser=1): Demonstrate how to build your TF model.

```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!}
```