```

### Cache the OpenAPI schema

You can use the property `.openapi_schema` as a "cache", to store your generated schema.

That way, your application won't have to generate the schema every time a user opens your API docs.

It will be generated only once, and then the same cached schema will be used for the next requests.

```Python hl_lines="13-14  25-26"
{!../../../docs_src/extending_openapi/tutorial001.py!}

* **セキュアなパスワード** ハッシュ化 (デフォルトで)。
* **JWTトークン** 認証。
* **SQLAlchemy** モデル (Flask用の拡張と独立しているので、Celeryワーカーと直接的に併用できます)。
* 基本的なユーザーモデル (任意の修正や削除が可能)。
* **Alembic** マイグレーション。
* **CORS** (Cross Origin Resource Sharing (オリジン間リソース共有))。
* **Celery** ワーカー。バックエンドの残りの部分からモデルとコードを選択的にインポートし、使用可能。

如果您需要执行繁重的后台计算，并且不一定需要由同一进程运行（例如，您不需要共享内存、变量等），那么使用其他更大的工具（如 <a href="https://docs.celeryq.dev" class="external-link" target="_blank">Celery</a>）可能更好。

它们往往需要更复杂的配置，即消息/作业队列管理器，如RabbitMQ或Redis，但它们允许您在多个进程中运行后台任务，甚至是在多个服务器中。

要查看示例，查阅 [Project Generators](../project-generation.md){.internal-link target=_blank}，它们都包括已经配置的Celery。

但是，如果您需要从同一个**FastAPI**应用程序访问变量和对象，或者您需要执行小型后台任务（如发送电子邮件通知），您只需使用 `BackgroundTasks` 即可。

## 回顾

For large responses, returning a `Response` directly is much faster than returning a dictionary.

## Returning a custom `Response`

The example above shows all the parts you need, but it's not very useful yet, as you could have just returned the `item` directly, and **FastAPI** would put it in a `JSONResponse` for you, converting it to a `dict`, etc. All that by default.

## CRUD utils

Now let's see the file `sql_app/crud.py`.

### Create all the CRUD utils

Create all the same CRUD utils as in the SQLAlchemy tutorial, all the code is very similar:

```Python hl_lines="1  4-5  8-9  12-13  16-20  23-24  27-30"
{!../../../docs_src/sql_databases_peewee/sql_app/crud.py!}
```

There are some differences with the code for the SQLAlchemy tutorial.

OAuth2 with scopes is the mechanism used by many big authentication providers, like Facebook, Google, GitHub, Microsoft, Twitter, etc. They use it to provide specific permissions to users and applications.

Every time you "log in with" Facebook, Google, GitHub, Microsoft, Twitter, that application is using OAuth2 with scopes.

    ```

### Check the password

At this point we have the user data from our database, but we haven't checked the password.

Let's put that data in the Pydantic `UserInDB` model first.

You should never save plaintext passwords, so, we'll use the (fake) password hashing system.

If the passwords don't match, we return the same error.

#### Password hashing

---

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints.

The key features are:

* **Fast**: Very high performance, on par with **NodeJS** and **Go** (thanks to Starlette and Pydantic). [One of the fastest Python frameworks available](#performance).
* **Fast to code**: Increase the speed to develop features by about 200% to 300%. *

Ensuite, vous pouvez servir cela avec le commandement `serve`:

<div class="termy">

```console
// Use the command "serve" after running "build-all"
$ python ./scripts/docs.py serve

Warning: this is a very simple server. For development, use mkdocs serve instead.
This is here only to preview a site with translations already built.
Make sure you run the build-all command first.
Serving at: http://127.0.0.1:8008
```