* You wouldn't write an application in Uvicorn directly. That would mean that your code would have to include more or less, at least, all the code provided by Starlette (or **FastAPI**). And if you did that, your final application would have the same overhead as having used a framework and minimizing your app code and bugs.

```

that would mean that you would use exactly the version `0.45.0`.

Or you could also pin it with:

```txt
fastapi>=0.45.0,<0.46.0
```

that would mean that you would use the versions `0.45.0` or above, but less than `0.46.0`, for example, a version `0.45.2` would still be accepted.

And you can use any model or data for the security requirements (in this case, a Pydantic model `User`).

But you are not restricted to using some specific data model, class or type.

Do you want to have an `id` and `email` and not have any `username` in your model? Sure. You can use these same tools.

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

!!! tip

## `HTTPSRedirectMiddleware`

Enforces that all incoming requests must either be `https` or `wss`.

Any incoming requests to `http` or `ws` will be redirected to the secure scheme instead.

```Python hl_lines="2  6"
{!../../../docs_src/advanced_middleware/tutorial001.py!}
```

## `TrustedHostMiddleware`

# How To - Recipes

Here you will see different recipes or "how to" guides for **several topics**.

Most of these ideas would be more or less **independent**, and in most cases you should only need to study them if they apply directly to **your project**.

If something seems interesting and useful to your project, go ahead and check it, but otherwise, you might probably just skip them.

!!! tip

    Aber **FastAPI** wird wissen, dass es zuerst `query_extractor` auflösen muss, um dessen Resultat `query_or_cookie_extractor` zu übergeben, wenn dieses aufgerufen wird.

```mermaid
graph TB

query_extractor(["query_extractor"])
query_or_cookie_extractor(["query_or_cookie_extractor"])

read_query["/items/"]

* It takes each **request** that comes to your application.
* It can then do something to that **request** or run any needed code.
* Then it passes the **request** to be processed by the rest of the application (by some *path operation*).
* It then takes the **response** generated by the application (by some *path operation*).
* It can do something to that **response** or run any needed code.
* Then it returns the **response**.

!!! note "Technical Details"

FastAPI uses a standard for building Python web frameworks and servers called <abbr title="Asynchronous Server Gateway Interface">ASGI</abbr>. FastAPI is an ASGI web framework.

The main thing you need to run a **FastAPI** application (or any other ASGI application) in a remote server machine is an ASGI server program like **Uvicorn**, this is the one that comes by default in the `fastapi` command.

There are several alternatives, including:

# Background Tasks - `BackgroundTasks`

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```