With **FastAPI** you get all of **Pydantic**'s features (as FastAPI is based on Pydantic for all the data handling):

* **No brainfuck**:
    * No new schema definition micro-language to learn.
    * If you know Python types you know how to use Pydantic.

# WebSockets

You can use <a href="https://developer.mozilla.org/en-US/docs/Web/API/WebSockets_API" class="external-link" target="_blank">WebSockets</a> with **FastAPI**.

## Install `WebSockets`

First you need to install `WebSockets`:

<div class="termy">

```console
$ pip install websockets

---> 100%
```

</div>

## WebSockets client

### In production

In most cases you would (and should) have a "termination proxy" handling HTTPS for you on top, this will depend on how you deploy your application, your provider might do this for you, or you might need to set it up yourself.

!!! tip

    Temporarily adopting this point of view (of the *external developer*) can help you feel like it's more obvious where to put the parameters, the Pydantic model for the body, for the response, etc. for that *external API*.

### Create a callback `APIRouter`

* <a href="https://github.com/esnme/ultrajson" target="_blank"><code>ujson</code></a> - Required if you want to use `UJSONResponse`.
* `fastapi-cli` - to provide the `fastapi` command.

When you install `fastapi` it comes these standard dependencies.

## `fastapi-slim`

---

"_If you're looking to learn one **modern framework** for building REST APIs, check out **FastAPI** [...] It's fast, easy to use and easy to learn [...]_"

"_We've switched over to **FastAPI** for our **APIs** [...] I think you'll like it [...]_"

If your application is **simple**, this will probably **not be a problem**, and you might not need to specify hard memory limits. But if you are **using a lot of memory** (for example with **machine learning** models), you should check how much memory you are consuming and adjust the **number of containers** that runs in **each machine** (and maybe add more machines to your cluster).

Next it will convert and validate the data. So, when you use that `settings` object, you will have data of the types you declared (e.g. `items_per_user` will be an `int`).

### Use the `settings`

Then you can use the new `settings` object in your application:

```Python hl_lines="18-20"
{!../../../docs_src/settings/tutorial001.py!}
```

### Run the server

# Including WSGI - Flask, Django, others

You can mount WSGI applications as you saw with [Sub Applications - Mounts](sub-applications.md){.internal-link target=_blank}, [Behind a Proxy](behind-a-proxy.md){.internal-link target=_blank}.

For that, you can use the `WSGIMiddleware` and use it to wrap your WSGI application, for example, Flask, Django, etc.

## Using `WSGIMiddleware`

You need to import `WSGIMiddleware`.

# Tutorial - User Guide

This tutorial shows you how to use **FastAPI** with most of its features, step by step.

Each section gradually builds on the previous ones, but it's structured to separate topics, so that you can go directly to any specific one to solve your specific API needs.

It is also built to work as a future reference.

So you can come back and see exactly what you need.

## Run the code