## Learn More

You can learn more about **GraphQL** in the <a href="https://graphql.org/" class="external-link" target="_blank">official GraphQL documentation</a>.

That demonstrates how the Proxy (Traefik) uses the path prefix and how the server (Uvicorn) uses the `root_path` from the option `--root-path`.

### Check the docs UI

But here's the fun part. ✨

In those cases, you can use the **official Docker image** that includes **Gunicorn** as a process manager running multiple **Uvicorn worker processes**, and some default settings to adjust the number of workers based on the current CPU cores automatically. I'll tell you more about it below in [Official Docker Image with Gunicorn - Uvicorn](#official-docker-image-with-gunicorn-uvicorn).

# Learn

Here are the introductory sections and the tutorials to learn **FastAPI**.

In the case of Spanish, the 2-letter code is `es`. So, the directory for Spanish translations is located at `docs/es/`.

!!! tip
    The main ("official") language is English, located at `docs/en/`.

Now run the live server for the docs in Spanish:

<div class="termy">

```console
// Use the command "live" and pass the language code as a CLI argument

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

```Python
    uvicorn.run(app, host="0.0.0.0", port=8000)
```

will not be executed.

!!! info
    For more information, check <a href="https://docs.python.org/3/library/__main__.html" class="external-link" target="_blank">the official Python docs</a>.

## Run your code with your debugger

Because you are running the Uvicorn server directly from your code, you can call your Python program (your FastAPI application) directly from the debugger.

---

在FastAPI中仍然可以单独使用 `BackgroundTask`，但您必须在代码中创建对象，并返回包含它的Starlette `Response`。

更多细节查看 <a href="https://www.starlette.io/background/" class="external-link" target="_blank">Starlette's official docs for Background Tasks</a>.

## 告诫

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。

You can see more details in <a href="https://www.starlette.io/background/" class="external-link" target="_blank">Starlette's official docs for Background Tasks</a>.

## Caveat

## `Request` documentation

You can read more details about the <a href="https://www.starlette.io/requests/" class="external-link" target="_blank">`Request` object in the official Starlette documentation site</a>.

!!! note "Technical Details"
    You could also use `from starlette.requests import Request`.