</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。

///

# 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

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```

## FastAPI全栈模板 - 技术栈和特性

- ⚡ [**FastAPI**](https://fastapi.tiangolo.com) 用于Python后端API.
    - 🧰 [SQLModel](https://sqlmodel.tiangolo.com) 用于Python和SQL数据库的集成（ORM）。
    - 🔍 [Pydantic](https://docs.pydantic.dev) FastAPI的依赖项之一，用于数据验证和配置管理。
    - 💾 [PostgreSQL](https://www.postgresql.org) 作为SQL数据库。
- 🚀 [React](https://react.dev) 用于前端。

## 開発

すでにリポジトリをクローンし、コードを詳しく調べる必要があるとわかっている場合に、環境構築のためのガイドラインをいくつか紹介します。

### `venv`を使用した仮想環境

Pythonの`venv`モジュールを使用して、ディレクトリに仮想環境を作成します:

<div class="termy">

```console
$ python -m venv env
```

</div>

これにより、Pythonバイナリを含む`./env/`ディレクトリが作成され、その隔離された環境にパッケージのインストールが可能になります。

### 仮想環境の有効化

新しい環境を有効化するには:

//// tab | Linux, macOS

<div class="termy">

load(
    "//tensorflow/python/tools/api/generator:api_gen.bzl",
    "get_compat_files",
    "get_nested_compat_files",
)
load(
    "//tensorflow/python/tools/api/generator:api_init_files.bzl",
    "TENSORFLOW_API_INIT_FILES",
)
load(
    "//tensorflow/python/tools/api/generator:api_init_files_v1.bzl",
    "TENSORFLOW_API_INIT_FILES_V1",
)

///

## 이름을 기억하는 쉬운 방법

상기 예시 참고:

```Python hl_lines="6"
{!../../docs_src/response_status_code/tutorial001.py!}
```

`201` 은 "생성됨"를 의미하는 상태 코드입니다.

하지만 모든 상태 코드들이 무엇을 의미하는지 외울 필요는 없습니다.

`fastapi.status` 의 편의 변수를 사용할 수 있습니다.

```Python hl_lines="1  6"
{!../../docs_src/response_status_code/tutorial002.py!}
```

# Testando WebSockets

Você pode usar o mesmo `TestClient` para testar WebSockets.

Para isso, você utiliza o `TestClient` dentro de uma instrução `with`, conectando com o WebSocket:

```Python hl_lines="27-31"
{!../../docs_src/app_testing/tutorial002.py!}
```

/// note | "Nota"

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

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

### Sub-application

Then, create your sub-application, and its *path operations*.

This sub-application is just another standard FastAPI application, but this is the one that will be "mounted":

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