After that, you would need to **install** FastAPI and any other **packages** you want to use.

To install packages you would normally use the `pip` command that comes with Python (or similar alternatives).

Nevertheless, if you just use `pip` directly, the packages would be installed in your **global Python environment** (the global installation of Python).

You could have turns as in the burgers example, first the living room, then the kitchen, but as you are not waiting 🕙 for anything, just cleaning and cleaning, the turns wouldn't affect anything.

It would take the same amount of time to finish with or without turns (concurrency) and you would have done the same amount of work.

For example, you could want to **return a dictionary** or a database object, but **declare it as a Pydantic model**. This way the Pydantic model would do all the data documentation, validation, etc. for the object that you returned (e.g. a dictionary or database object).

  //   system scheduling and as such we could either miss our deadline, or unpark() could be delayed
  //   so that it looks like we timed out even though we didn't. For comparison FutureTask respects
  //   completion preferably and AQS is non-deterministic (depends on where in the queue the waiter
  //   is). If we wanted to be strict about it, we could store the unpark() time in the Waiter node

	n++
}
i := *p
*q = 1
</pre>

<p>
If <code>list</code> pointed to a cyclic list,
then the original program would never access <code>*p</code> or <code>*q</code>,
but the rewritten program would.
(Moving `*p` ahead would be safe if the compiler can prove `*p` will not panic;
moving `*q` ahead would also require the compiler proving that no other
goroutine can access `*q`.)
</p>

<p>

  //   system scheduling and as such we could either miss our deadline, or unpark() could be delayed
  //   so that it looks like we timed out even though we didn't. For comparison FutureTask respects
  //   completion preferably and AQS is non-deterministic (depends on where in the queue the waiter
  //   is). If we wanted to be strict about it, we could store the unpark() time in the Waiter node

You import it and create an "instance" the same way you would with the class `FastAPI`:

```Python hl_lines="1  3" title="app/routers/users.py"
{!../../docs_src/bigger_applications/app/routers/users.py!}
```

### *Path operations* with `APIRouter` { #path-operations-with-apirouter }

And then you use it to declare your *path operations*.

Use it the same way you would use the `FastAPI` class:

The OpenAPI schema is what powers the two interactive documentation systems included.

And there are dozens of alternatives, all based on OpenAPI. You could easily add any of those alternatives to your application built with **FastAPI**.

You could also use it to generate code automatically, for clients that communicate with your API. For example, frontend, mobile or IoT applications.

Now, let's see how you could use that to return a custom response.

Let's say that you want to return an <a href="https://en.wikipedia.org/wiki/XML" class="external-link" target="_blank">XML</a> response.

`OAuth2PasswordBearer` makes **FastAPI** know that it is a security scheme. So it is added that way to OpenAPI.

But `OAuth2PasswordRequestForm` is just a class dependency that you could have written yourself, or you could have declared `Form` parameters directly.

But as it's a common use case, it is provided by **FastAPI** directly, just to make it easier.

///

### Use the form data { #use-the-form-data }