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

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

If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly).

### Examples of Replication Tools and Strategies

Then wrap the WSGI (e.g. Flask) app with the middleware.

And then mount that under a path.

```Python hl_lines="2-3  23"
{!../../../docs_src/wsgi/tutorial001.py!}
```

## Check it

Now, every request under the path `/v1/` will be handled by the Flask application.

And the rest will be handled by **FastAPI**.

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

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

It is based on <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a>, which in turn is designed based on Requests, so it's very familiar and intuitive.

With it, you can use <a href="https://docs.pytest.org/" class="external-link" target="_blank">pytest</a> directly with **FastAPI**.

## Using `TestClient`

!!! info

    ...
```

!!! 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。

Reading a file from disk is normally a costly (slow) operation, so you probably want to do it only once and then re-use the same settings object, instead of reading it for each request.

But every time we do:

```Python
Settings()
```

a new `Settings` object would be created, and at creation it would read the `.env` file again.

If the dependency function was just like:

```Python

To see how to achieve this parallelism in production see the section about [Deployment](deployment/index.md){.internal-link target=_blank}.

## `async` and `await`