</p>
<p align="center">
<a href="https://github.com/tiangolo/fastapi/actions?query=workflow%3ATest+event%3Apush+branch%3Amaster" target="_blank">
    <img src="https://github.com/tiangolo/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://codecov.io/gh/tiangolo/fastapi" target="_blank">

</p>
<p align="center">
<a href="https://github.com/tiangolo/fastapi/actions?query=workflow%3ATest+event%3Apush+branch%3Amaster" target="_blank">
    <img src="https://github.com/tiangolo/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/tiangolo/fastapi" target="_blank">

It has:

* Seriously impressive performance.
* WebSocket support.
* In-process background tasks.
* Startup and shutdown events.
* Test client built on HTTPX.
* CORS, GZip, Static Files, Streaming responses.
* Session and Cookie support.
* 100% test coverage.
* 100% type annotated codebase.
* Few hard dependencies.

### `response_model` Priority

If you declare both a return type and a `response_model`, the `response_model` will take priority and be used by FastAPI.

This way you can add correct type annotations to your functions even when you are returning a type different than the response model, to be used by the editor and tools like mypy. And still you can have FastAPI do the data validation, documentation, etc. using the `response_model`.

In this case, the original path `/app` would actually be served at `/api/v1/app`.

Even though all your code is written assuming there's just `/app`.

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

* Hỗ trợ **WebSocket**.
* In-process background tasks.
* Startup and shutdown events.
* Client cho kiểm thử xây dựng trên HTTPX.
* **CORS**, GZip, Static Files, Streaming responses.
* Hỗ trợ **Session and Cookie**.
* 100% test coverage.
* 100% type annotated codebase.

## Tính năng của Pydantic

    This is a special class that you can define in a parameter in a dependency to
    obtain the OAuth2 scopes required by all the dependencies in the same chain.

    This way, multiple dependencies can have different scopes, even when used in the
    same *path operation*. And with this, you can access all the scopes required in
    all those dependencies in a single place.

    Read more about it in the

</p>
<p align="center">
<a href="https://github.com/tiangolo/fastapi/actions?query=workflow%3ATest+event%3Apush+branch%3Amaster" target="_blank">
    <img src="https://github.com/tiangolo/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/tiangolo/fastapi" target="_blank">

</p>
<p align="center">
<a href="https://github.com/tiangolo/fastapi/actions?query=workflow%3ATest+event%3Apush+branch%3Amaster" target="_blank">
    <img src="https://github.com/tiangolo/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/tiangolo/fastapi" target="_blank">

Mas antes disso, controlar código assíncrono era bem mais complexo e difícil.

Nas versões anteriores do Python, você poderia utilizar threads ou <a href="http://www.gevent.org/" class="external-link" target="_blank">Gevent</a>. Mas o código é um pouco mais complexo de entender, debugar, e pensar sobre.