They are, more or less, at opposite ends, complementing each other.

Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable.

That's why, as said in the official website:

> Requests is one of the most downloaded Python packages of all time

The way you use it is very simple. For example, to do a `GET` request, you would write:

```Python

<div class="termy">

```console
$ python -m pip install --upgrade pip

---> 100%
```

</div>

!!! tip
    Every time you install a new package with `pip` under that environment, activate the environment again.

# Middleware

You can add middleware to **FastAPI** applications.

A "middleware" is a function that works with every **request** before it is processed by any specific *path operation*. And also with every **response** before returning it.

* It takes each **request** that comes to your application.
* It can then do something to that **request** or run any needed code.

In this case, it might not be a problem, because it's the same user sending the password.

But if we use the same model for another *path operation*, we could be sending our user's passwords to every client.

!!! danger
    Never store the plain password of a user or send it in a response like this, unless you know all the caveats and you know what you are doing.

## Add an output model

* **JWT-Token**-Authentifizierung.
* **SQLAlchemy**-Modelle (unabhängig von Flask-Erweiterungen, sodass sie direkt mit Celery-Workern verwendet werden können).
* Grundlegende Startmodelle für Benutzer (ändern und entfernen Sie nach Bedarf).
* **Alembic**-Migrationen.
* **CORS** (Cross Origin Resource Sharing).
* **Celery**-Worker, welche Modelle und Code aus dem Rest des Backends selektiv importieren und verwenden können.

name: Test

on:
  push:
    branches:
      - master
  pull_request:
    types:
      - opened
      - synchronize
  schedule:
    # cron every week on monday
    - cron: "0 0 * * 1"

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v4

これらは、より複雑な構成、RabbitMQ や Redis などのメッセージ/ジョブキューマネージャーを必要とする傾向がありますが、複数のプロセス、特に複数のサーバーでバックグラウンドタスクを実行できます。

例を確認するには、[Project Generators](../project-generation.md){.internal-link target=_blank} を参照してください。これらにはすべて、Celery が構築済みです。

    c = TestClient(app)
    return c


@needs_py310
def test_foo_needy_very(client: TestClient):
    response = client.get("/items/foo?needy=very")
    assert response.status_code == 200
    assert response.json() == {
        "item_id": "foo",
        "needy": "very",
        "skip": 0,
        "limit": None,
    }


@needs_py310
def test_foo_no_needy(client: TestClient):

There are many tools to generate clients from **OpenAPI**.

A common tool is <a href="https://openapi-generator.tech/" class="external-link" target="_blank">OpenAPI Generator</a>.

If you are building a **frontend**, a very interesting alternative is <a href="https://github.com/hey-api/openapi-ts" class="external-link" target="_blank">openapi-ts</a>.

## Client and SDK Generators - Sponsor

    ...
```

!!! info
    如果您需要异步连接到关系数据库，请参阅[Async SQL (Relational) Databases](https://fastapi.tiangolo.com/zh/advanced/async-sql-databases/)

!!! note "Very Technical Details"
    如果您很好奇并且拥有深厚的技术知识，您可以在[Async](https://fastapi.tiangolo.com/zh/async/#very-technical-details)文档中查看有关如何处理 `async def`于`def`差别的技术细节。

## 迁移

因为我们直接使用 SQLAlchemy，并且我们不需要任何类型的插件来使用**FastAPI**，所以我们可以直接将数据库迁移至[Alembic](https://alembic.sqlalchemy.org/)进行集成。