Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

Let's imagine that loading the model can **take quite some time**, because it has to read a lot of **data from disk**. So you don't want to do it for every request.

Stellen wir uns vor, wir möchten eine Abhängigkeit haben, die prüft, ob ein Query-Parameter `q` einen vordefinierten Inhalt hat.

Aber wir wollen diesen vordefinierten Inhalt per Parameter festlegen können.

## Eine „aufrufbare“ Instanz

In Python gibt es eine Möglichkeit, eine Instanz einer Klasse „aufrufbar“ („callable“) zu machen.

### Use cases: external service

An example could be that you have an external authentication provider that you need to call.

You send it a token and it returns an authenticated user.

This provider might be charging you per request, and calling it might take some extra time than if you had a fixed mock user for tests.

You probably want to test the external provider once, but not necessarily call it for every test that runs.

If one of your dependencies is declared multiple times for the same *path operation*, for example, multiple dependencies have a common sub-dependency, **FastAPI** will know to call that sub-dependency only once per request.

Als Nächstes werden die Daten konvertiert und validiert. Wenn Sie also dieses `settings`-Objekt verwenden, verfügen Sie über Daten mit den von Ihnen deklarierten Typen (z. B. ist `items_per_user` ein `int`).

### `settings` verwenden

Dann können Sie das neue `settings`-Objekt in Ihrer Anwendung verwenden:

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

### One Process per Container

In this type of scenario, you probably would want to have **a single (Uvicorn) process per container**, as you would already be handling replication at the cluster level.

```Python hl_lines="2  6"
{!../../../docs_src/advanced_middleware/tutorial003.py!}
```

Die folgenden Argumente werden unterstützt:

* `minimum_size` – Antworten, die kleiner als diese Mindestgröße in Bytes sind, nicht per GZip komprimieren. Der Defaultwert ist `500`.

## Andere Middlewares

Es gibt viele andere ASGI-Middlewares.

Zum Beispiel:

#### A "professional" attack

Of course, the attackers would not try all this by hand, they would write a program to do it, possibly with thousands or millions of tests per second. And would get just one extra correct letter at a time.

    {!> ../../../docs_src/extra_models/tutorial005.py!}
    ```

## Recap

Use multiple Pydantic models and inherit freely for each case.

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!}
```