Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.

You actually don't have users that log in to your application but robots, bots, or other systems, that have just an access token? Again, it all works the same.

Sie haben eigentlich keine Benutzer, die sich bei Ihrer Anwendung anmelden, sondern Roboter, Bots oder andere Systeme, die nur über einen Zugriffstoken verfügen? Auch hier funktioniert alles gleich.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

!!! tip
    When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

## Server Machine and Server Program

There's a small detail about names to keep in mind. 💡

The word "**server**" is commonly used to refer to both the remote/cloud computer (the physical or virtual machine) and also the program that is running on that machine (e.g. Uvicorn).

Just keep in mind that when you read "server" in general, it could refer to one of those two things.

@needs_pydanticv1
def test_union_scalar_list():
    # For coverage
    # TODO: there might not be a current valid code path that uses this, it would
    # potentially enable query parameters defined as both a scalar and a list
    # but that would require more refactors, also not sure it's really useful
    from fastapi._compat import is_pv1_scalar_field

    field_info = FieldInfo()
    field = ModelField(

## `GZipMiddleware`

Handles GZip responses for any request that includes `"gzip"` in the `Accept-Encoding` header.

The middleware will handle both standard and streaming responses.

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

The following arguments are supported:

```Python hl_lines="8-13"
{!../../../docs_src/sql_databases/sql_app/tests/test_sql_app.py!}
```

!!! tip
    You could reduce duplication in that code by putting it in a function and using it from both `database.py` and `tests/test_sql_app.py`.

    For simplicity and to focus on the specific testing code, we are just copying it.

## Create the database

* Hashage de **mots de passe sécurisé** par défaut.
* Authentification par **jetons JWT**.
* Modèles **SQLAlchemy** (indépendants des extensions Flask, afin qu'ils puissent être utilisés directement avec des *workers* Celery).

Let's say that now the file `main.py` with your **FastAPI** app has some other **path operations**.

It has a `GET` operation that could return an error.

It has a `POST` operation that could return several errors.

Both *path operations* require an `X-Token` header.

=== "Python 3.10+"

    ```Python
    {!> ../../../docs_src/app_testing/app_b_an_py310/main.py!}
    ```

=== "Python 3.9+"

    ```Python

## Pydantic

Toda a validação de dados é feita por baixo dos panos pelo <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>, então você tem todos os benefícios disso. E assim você sabe que está em boas mãos.

Você pode usar as mesmas declarações de tipo com `str`, `float`, `bool` e muitos outros tipos complexos de dados.

Vamos explorar muitos destes tipos nos próximos capítulos do tutorial.

## A ordem importa