## Create the database

Because now we are going to use a new database in a new file, we need to make sure we create the database with:

```Python
Base.metadata.create_all(bind=engine)
```

That is normally called in `main.py`, but the line in `main.py` uses the database file `sql_app.db`, and we need to make sure we create `test.db` for the tests.

So we add that line here, with the new file.

```Python hl_lines="16"

After you have tests, then you can upgrade the **FastAPI** version to a more recent one, and make sure that all your code is working correctly by running your tests.

If everything is working, or after you make the necessary changes, and all your tests are passing, then you can pin your `fastapi` to that new recent version.

## About Starlette

    !!! tip
        Prefer to use the `Annotated` version if possible.

    ```Python hl_lines="10"
    {!> ../../../docs_src/security/tutorial001.py!}
    ```

But that is still not that useful.

Let's make it give us the current user.

## Create a user model

First, let's create a Pydantic user model.

The same way we use Pydantic to declare bodies, we can use it anywhere else:

=== "Python 3.10+"

This way, its schema will show up in the API docs user interface:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses in Nested Data Structures

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

## Adding ASGI middlewares

As **FastAPI** is based on Starlette and implements the <abbr title="Asynchronous Server Gateway Interface">ASGI</abbr> specification, you can use any ASGI middleware.

A middleware doesn't have to be made for FastAPI or Starlette to work, as long as it follows the ASGI spec.

In general, ASGI middlewares are classes that expect to receive an ASGI app as the first argument.

!!! tip
    **GraphQL** solves some very specific use cases.

    It has **advantages** and **disadvantages** when compared to common **web APIs**.

    Make sure you evaluate if the **benefits** for your use case compensate the **drawbacks**. 🤓

## GraphQL Libraries

Here are some of the **GraphQL** libraries that have **ASGI** support. You could use them with **FastAPI**:

And then you can also have a path `/users/{user_id}` to get data about a specific user by some user ID.

Because *path operations* are evaluated in order, you need to make sure that the path for `/users/me` is declared before the one for `/users/{user_id}`:

```Python hl_lines="6  11"
{!../../../docs_src/path_params/tutorial003.py!}
```

async def router_ws_custom_error(websocket: WebSocket):
    raise CustomError()


def make_app(app=None, **kwargs):
    app = app or FastAPI(**kwargs)
    app.include_router(router)
    app.include_router(prefix_router, prefix="/prefix")
    app.include_router(native_prefix_route)
    return app


app = make_app(app)


def test_app():
    client = TestClient(app)

If you want to secure your API, there are several better things you can do, for example:

* Decompressing gzip-compressed request bodies.
* Automatically logging all request bodies.

## Handling custom request body encodings

Let's see how to make use of a custom `Request` subclass to decompress gzip requests.

And an `APIRoute` subclass to use that custom request class.

### Create a custom `GzipRequest` class

!!! tip