## Erstellung einer Middleware

Um eine Middleware zu erstellen, verwenden Sie den Dekorator `@app.middleware("http")` über einer Funktion.

Die Middleware-Funktion erhält:

* Den `request`.
* Eine Funktion `call_next`, die den `request` als Parameter erhält.
    * Diese Funktion gibt den `request` an die entsprechende *Pfadoperation* weiter.

---

# FastAPI İnsanlar

FastAPI-ın bütün mənşəli insanları qəbul edən heyrətamiz icması var.



## Yaradıcı - İcraçı

Salam! 👋

Bu mənəm:

{% if people %}
<div class="user-list user-list-center">
{% for user in people.maintainers %}

---

# FastAPI Topluluğu

FastAPI, her kökenden insanı ağırlayan harika bir topluluğa sahip.

## Yazan - Geliştiren

Merhaba! 👋

İşte bu benim:

{% if people %}
<div class="user-list user-list-center">
{% for user in people.maintainers %}

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server
    * **Starlette**: (uses Uvicorn) a web microframework

## `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!}
```

* Der *Pfad* kann einen <a href="https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.1.0.md#key-expression" class="external-link" target="_blank">OpenAPI-3-Ausdruck</a> enthalten (mehr dazu weiter unten), wo er Variablen mit Parametern und Teilen des ursprünglichen Requests verwenden kann, der an *Ihre API* gesendet wurde.

### Der Callback-Pfadausdruck

Weitere Informationen hierzu finden Sie in der Dokumentation des Repos.

## Full Stack FastAPI MongoDB

... könnte später kommen, abhängig von meiner verfügbaren Zeit und anderen Faktoren. 😅 🎉

## Modelle für maschinelles Lernen mit spaCy und FastAPI

```console
$ hypercorn main:app --worker-class trio
```

</div>

And that will start Hypercorn with your app using Trio as the backend.

Now you can use Trio internally in your app. Or even better, you can use AnyIO, to keep your code compatible with both Trio and asyncio. 🎉

## Deployment Concepts

}

.user .title {
  text-align: center;
}

.user .count {
  font-size: 80%;
  text-align: center;
}

a.announce-link:link,
a.announce-link:visited {
  color: #fff;
}

a.announce-link:hover {
  color: var(--md-accent-fg-color);
}

.announce-wrapper {
  display: flex;
  justify-content: space-between;
  flex-wrap: wrap;
  align-items: center;
}

.announce-wrapper div.item {

  - navigation
---

# FastAPI People

FastAPI has an amazing community that welcomes people from all backgrounds.

## Creator

Hey! 👋

This is me:

{% if people %}
<div class="user-list user-list-center">
{% for user in people.maintainers %}