</mxCell>
                <mxCell id="6" value="" style="rounded=0;whiteSpace=wrap;html=1;fontStyle=1;strokeWidth=4;fillColor=#dae8fc;strokeColor=#6c8ebf;" parent="1" vertex="1">
                    <mxGeometry x="1110" y="410" width="190" height="500" as="geometry"/>
                </mxCell>

    {!> ../../../docs_src/response_model/tutorial004_py310.py!}
    ```

=== "Python 3.9+"

    ```Python hl_lines="11  13-14"
    {!> ../../../docs_src/response_model/tutorial004_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="11  13-14"
    {!> ../../../docs_src/response_model/tutorial004.py!}
    ```

=== "Python 3.9+"

    ```Python hl_lines="7-9  12-13  16-17  21"
    {!> ../../../docs_src/generate_clients/tutorial001_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="9-11  14-15  18  19  23"
    {!> ../../../docs_src/generate_clients/tutorial001.py!}
    ```

导入之前的`models`（SQLAlchemy 模型）和`schemas`（Pydantic*模型*/模式）。

创建一些实用函数来完成：

* 通过 ID 和电子邮件查询单个用户。
* 查询多个用户。
* 查询多个项目。

```Python hl_lines="1  3  6-7  10-11  14-15  27-28"
{!../../../docs_src/sql_databases/sql_app/crud.py!}
```

!!! tip
    通过创建仅专用于与数据库交互（获取用户或项目）的函数，独立于*路径操作函数*，您可以更轻松地在多个部分中重用它们，并为它们添加单元测试。

### 创建数据

现在创建实用程序函数来创建数据。

它的步骤是：

                <mxCell id="111" value="" style="edgeStyle=orthogonalEdgeStyle;rounded=0;orthogonalLoop=1;jettySize=auto;html=1;startArrow=none;startFill=0;endArrow=none;endFill=1;strokeWidth=3;" edge="1" parent="1" source="6" target="84">
                    <mxGeometry relative="1" as="geometry">
                        <mxPoint x="850" y="390" as="sourcePoint"/>
                        <mxPoint x="1190" y="700" as="targetPoint"/>

    {!> ../../../docs_src/response_model/tutorial004_py310.py!}
    ```

=== "Python 3.9+"

    ```Python hl_lines="11  13-14"
    {!> ../../../docs_src/response_model/tutorial004_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="11  13-14"
    {!> ../../../docs_src/response_model/tutorial004.py!}
    ```

## 📨 🏷 🔢 🔢

👆 📨 🏷 💪 ✔️ 🔢 💲, 💖:

=== "🐍 3️⃣.6️⃣ & 🔛"

    ```Python hl_lines="11  13-14"
    {!> ../../../docs_src/response_model/tutorial004.py!}
    ```

=== "🐍 3️⃣.9️⃣ & 🔛"

    ```Python hl_lines="11  13-14"
    {!> ../../../docs_src/response_model/tutorial004_py39.py!}
    ```

=== "🐍 3️⃣.1️⃣0️⃣ & 🔛"

=== "Python 3.9+"

    ```Python hl_lines="7-9  12-13  16-17  21"
    {!> ../../../docs_src/generate_clients/tutorial001_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="9-11  14-15  18  19  23"
    {!> ../../../docs_src/generate_clients/tutorial001.py!}
    ```

    `"json_schema_extra"`를 생성된 JSON 스키마에서 보여주고 싶은 별도의 데이터와 `examples`를 포함하는 `dict`으로 설정할 수 있습니다.

=== "Pydantic v1"

    Pydantic v1에서 <a href="https://docs.pydantic.dev/1.10/usage/schema/#schema-customization" class="external-link" target="_blank">Pydantic 공식 문서: Schema customization</a>에서 설명하는 것처럼, 내부 클래스인 `Config`와 `schema_extra`를 사용할 것입니다.

=== "Python 3.9+"

    ```Python hl_lines="1  11"
    {!> ../../../docs_src/settings/app03_an_py39/main.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="1  11"
    {!> ../../../docs_src/settings/app03_an/main.py!}
    ```

=== "Python 3.8+ nicht annotiert"

    !!! tip "Tipp"