* Use the `templates` you created to render and return a `TemplateResponse`, pass the name of the template, the request object, and a "context" dictionary with key-value pairs to be used inside of the Jinja2 template.

```Python hl_lines="4  11  15-18"
{!../../docs_src/templates/tutorial001.py!}
```

/// note

Before FastAPI 0.108.0, Starlette 0.29.0, the `name` was the first parameter.

</div>

## 使用 `Jinja2Templates`

* 导入 `Jinja2Templates`
* 创建可复用的 `templates` 对象
* 在返回模板的*路径操作*中声明 `Request` 参数
* 使用 `templates` 渲染并返回 `TemplateResponse`， 传递模板的名称、request对象以及一个包含多个键值对（用于Jinja2模板）的"context"字典，

```Python hl_lines="4  11  15-16"
{!../../docs_src/templates/tutorial001.py!}
```

/// note | "笔记"

在FastAPI 0.108.0，Starlette 0.29.0之前，`name`是第一个参数。
并且，在此之前，`request`对象是作为context的一部分以键值对的形式传递的。

///

首先，创建主（顶层）**FastAPI** 应用及其*路径操作*：

```Python hl_lines="3  6-8"
{!../../docs_src/sub_applications/tutorial001.py!}
```

### 子应用

接下来，创建子应用及其*路径操作*。

子应用只是另一个标准 FastAPI 应用，但这个应用是被**挂载**的应用：

```Python hl_lines="11  14-16"
{!../../docs_src/sub_applications/tutorial001.py!}
```

### 挂载子应用

在顶层应用 `app` 中，挂载子应用 `subapi`。

本例的子应用挂载在 `/subapi` 路径下：

```Python hl_lines="11  19"

```Python hl_lines="6-9"
{!../../docs_src/background_tasks/tutorial001.py!}
```

## Ajouter une tâche d'arrière-plan

Dans votre *fonction de chemin*, passez votre fonction de tâche à l'objet de type `BackgroundTasks` (`background_tasks` ici) grâce à la méthode `.add_task()` :


```Python hl_lines="14"
{!../../docs_src/background_tasks/tutorial001.py!}
```

      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: '3.9'
      - name: Setup uv
        uses: astral-sh/setup-uv@v3
        with:
          version: "0.4.15"
          enable-cache: true
          cache-dependency-glob: |

    * Con <a href="https://tartiflette.github.io/tartiflette-asgi/" class="external-link" target="_blank">Tartiflette ASGI</a> para proveer integración con ASGI
* <a href="https://graphene-python.org/" class="external-link" target="_blank">Graphene</a>
    * Con <a href="https://github.com/ciscorn/starlette-graphene3" class="external-link" target="_blank">starlette-graphene3</a>

## GraphQL con Strawberry

    * With <a href="https://tartiflette.github.io/tartiflette-asgi/" class="external-link" target="_blank">Tartiflette ASGI</a> to provide ASGI integration
* <a href="https://graphene-python.org/" class="external-link" target="_blank">Graphene</a>
    * With <a href="https://github.com/ciscorn/starlette-graphene3" class="external-link" target="_blank">starlette-graphene3</a>

## GraphQL with Strawberry

# Check and rename wheels with auditwheel. Inserts the platform tags like
# "manylinux_xyz" into the wheel filename.
set -euxo pipefail

for wheel in /tf/pkg/*.whl; do
  echo "Checking and renaming $wheel..."
  time python3 -m auditwheel repair --plat manylinux2014_aarch64 "$wheel" --wheel-dir /tf/pkg 2>&1 | tee check.txt

  # We don't need the original wheel if it was renamed

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_cpu"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=tensorflow/build:2.18-python${TFCI_PYTHON_VERSION}
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--build-arg PYTHON_VERSION=python$TFCI_PYTHON_VERSION --target=devel tensorflow/tools/tf_sig_build_dockerfiles"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-x86_64"
TFCI_OUTPUT_DIR=build_output

## `Header` 임포트

먼저 `Header`를 임포트합니다:

```Python hl_lines="3"
{!../../docs_src/header_params/tutorial001.py!}
```

## `Header` 매개변수 선언

`Path`, `Query` 그리고 `Cookie`를 사용한 동일한 구조를 이용하여 헤더 매개변수를 선언합니다.

첫 번째 값은 기본값이며, 추가 검증이나 어노테이션 매개변수 모두 전달할 수 있습니다:

```Python hl_lines="9"
{!../../docs_src/header_params/tutorial001.py!}
```

/// note | "기술 세부사항"