# Advanced User Guide { #advanced-user-guide }

## Additional Features { #additional-features }

The main [Tutorial - User Guide](../tutorial/index.md){.internal-link target=_blank} should be enough to give you a tour through all the main features of **FastAPI**.

In the next sections you will see other options, configurations, and additional features.

/// tip

The next sections are **not necessarily "advanced"**.

I'll tell you a bit more about these **concepts** here, and that would hopefully give you the **intuition** you would need to decide how to deploy your API in very different environments, possibly even in **future** ones that don't exist yet.

By considering these concepts, you will be able to **evaluate and design** the best way to deploy **your own APIs**.

In the next chapters, I'll give you more **concrete recipes** to deploy FastAPI applications.

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** will **extract** the data for **each field** from the **query parameters** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the query parameters in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/query-param-models/image01.png">

            },
            directExecutor());

    // Wait for the first task to be started in the background. It will block until we explicitly
    // stop it.
    blockingCallable.waitForStart();

    // Give the second task a chance to (incorrectly) start up while the first task is running.
    assertThat(future2.isDone()).isFalse();

    // Stop the first task. The second task should then run.
    blockingCallable.stop();

* Convert the corresponding types (if needed).
* Validate the data.
    * If the data is invalid, it will return a nice and clear error, indicating exactly where and what was the incorrect data.
* Give you the received data in the parameter `item`.
    * As you declared it in the function to be of type `Item`, you will also have all the editor support (completion, etc) for all of the attributes and their types.

{* ../../docs_src/request_form_models/tutorial001_an_py39.py hl[9:11,15] *}

**FastAPI** will **extract** the data for **each field** from the **form data** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can verify it in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/request-form-models/image01.png">
</div>

            @Throws(IOException::class)
            override fun authenticate(route: Route?, response: Response): Request? {
              if (response.request.header("Authorization") != null) {
                return null // Give up, we've already attempted to authenticate.
              }

              println("Authenticating for response: $response")
              println("Challenges: ${response.challenges()}")

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

**FastAPI** will **extract** the data for **each field** from the **headers** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the required headers in the docs UI at `/docs`:

<div class="screenshot">

{* ../../docs_src/cookie_param_models/tutorial001_an_py310.py hl[9:12,16] *}

**FastAPI** will **extract** the data for **each field** from the **cookies** received in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the defined cookies in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/cookie-param-models/image01.png">

By declaring types for your variables, editors and tools can give you better support.

This is just a **quick tutorial / refresher** about Python type hints. It covers only the minimum necessary to use them with **FastAPI**... which is actually very little.

**FastAPI** is all based on these type hints, they give it many advantages and benefits.