```Python
async with lifespan(app):
    await do_stuff()
```

When you create a context manager or an async context manager like above, what it does is that, before entering the `with` block, it will execute the code before the `yield`, and after exiting the `with` block, it will execute the code after the `yield`.

In our code example above, we don't use it directly, but we pass it to FastAPI for it to use it.

    {!> ../../../docs_src/sql_databases/sql_app/main.py!}
    ```

!!! info
    We put the creation of the `SessionLocal()` and handling of the requests in a `try` block.

    And then we close it in the `finally` block.

    This way we make sure the database session is always closed after the request. Even if there was an exception while processing the request.

```

!!! tip
    You can use `async` or regular functions.

    **FastAPI** will do the right thing with each, the same as with normal dependencies.

## A dependency with `yield` and `try`

If you use a `try` block in a dependency with `yield`, you'll receive any exception that was thrown when using the dependency.

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      </a>
    </div>
    <div class="item">

    Sie können `async`hrone oder reguläre Funktionen verwenden.

    **FastAPI** wird bei jeder das Richtige tun, so wie auch bei normalen Abhängigkeiten.

## Eine Abhängigkeit mit `yield` und `try`.

Wenn Sie einen `try`-Block in einer Abhängigkeit mit `yield` verwenden, empfangen Sie alle Exceptions, die bei Verwendung der Abhängigkeit geworfen wurden.

{!../../../docs_src/custom_response/tutorial008.py!}
```

1. This is the generator function. It's a "generator function" because it contains `yield` statements inside.
2. By using a `with` block, we make sure that the file-like object is closed after the generator function is done. So, after it finishes sending the response.

### Path operation functions

When you declare a *path operation function* with normal `def` instead of `async def`, it is run in an external threadpool that is then awaited, instead of being called directly (as it would block the server).

    Hier werden wir die Datei `requirements.txt` generieren.

3. Installiere Poetry in dieser Docker-Phase.

4. Kopiere die Dateien `pyproject.toml` und `poetry.lock` in das Verzeichnis `/tmp`.

    Da es `./poetry.lock*` verwendet (endet mit einem `*`), stürzt es nicht ab, wenn diese Datei noch nicht verfügbar ist.

5. Generiere die Datei `requirements.txt`.

    Here's where we will generate the file `requirements.txt`

3. Install Poetry in this Docker stage.

4. Copy the `pyproject.toml` and `poetry.lock` files to the `/tmp` directory.

    Because it uses `./poetry.lock*` (ending with a `*`), it won't crash if that file is not available yet.

5. Generate the `requirements.txt` file.

    Aqui é onde geraremos o arquivo `requirements.txt`

3. Instale o Poetry nesse estágio do Docker.

4. Copie os arquivos `pyproject.toml` e `poetry.lock` para o diretório `/tmp`.

    Porque está usando `./poetry.lock*` (terminando com um `*`), não irá falhar se esse arquivo ainda não estiver disponível.

5. Gere o arquivo `requirements.txt`.