So, we declare the event handler function with standard `def` instead of `async def`.

### `startup` and `shutdown` together

There's a high chance that the logic for your *startup* and *shutdown* is connected, you might want to start something and then finish it, acquire a resource and then release it, etc.

!!! info
    Note that the `TestClient` receives data that can be converted to JSON, not Pydantic models.

You can also use `dataclasses` in the `response_model` parameter:

```Python hl_lines="1  7-13  19"
{!../../../docs_src/dataclasses/tutorial002.py!}
```

The dataclass will be automatically converted to a Pydantic dataclass.

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

👆 💪 👈 ⏮️ `openapi_extra`:

```Python hl_lines="20-37  39-40"
{!../../../docs_src/path_operation_advanced_configuration/tutorial006.py!}
```

👉 🖼, 👥 🚫 📣 🙆 Pydantic 🏷. 👐, 📨 💪 🚫 <abbr title="converted from some plain format, like bytes, into Python objects">🎻</abbr> 🎻, ⚫️ ✍ 🔗 `bytes`, &amp; 🔢 `magic_data_reader()` 🔜 🈚 🎻 ⚫️ 🌌.

👐, 👥 💪 📣 📈 🔗 📨 💪.

### 🛃 🗄 🎚 🆎

#### Return *enumeration members*

You can return *enum members* from your *path operation*, even nested in a JSON body (e.g. a `dict`).

They will be converted to their corresponding values (strings in this case) before returning them to the client:

```Python hl_lines="18  21  23"
{!../../../docs_src/path_params/tutorial005.py!}
```

It would also mean that if you get data from the `Request` object directly (for example, read the body) it won't be validated, converted or documented (with OpenAPI, for the automatic API user interface) by FastAPI.

Although any other parameter declared normally (for example, the body with a Pydantic model) would still be validated, converted, annotated, etc.

But there are specific cases where it's useful to get the `Request` object.

# <abbr title="En anglais: Debugging">Débogage</abbr>

Vous pouvez connecter le <abbr title="En anglais: debugger">débogueur</abbr> dans votre éditeur, par exemple avec Visual Studio Code ou PyCharm.

## Faites appel à `uvicorn`

Dans votre application FastAPI, importez et exécutez directement `uvicorn` :

```Python hl_lines="1  15"
{!../../../docs_src/debugging/tutorial001.py!}
```

### À propos de `__name__ == "__main__"`

```

By creating these Pydantic models, the input data will be validated, serialized (converted), and annotated (documented).

So, you will be able to see it all in the interactive API docs.

## Connect and disconnect

* Create your `FastAPI` application.
* Create event handlers to connect and disconnect from the database.

```Python hl_lines="42  45-47  50-52"

Cela comprend, par exemple :

* Les notifications par email envoyées après l'exécution d'une action :
    * Étant donné que se connecter à un serveur et envoyer un email a tendance à être «lent» (plusieurs secondes), vous pouvez retourner la réponse directement et envoyer la notification en arrière-plan.
* Traiter des données :

    * Entendre quand je fais des annonces ou que je lance de nouveaux outils.
* <a href="https://www.linkedin.com/in/tiangolo/" class="external-link" target="_blank">Vous connectez à moi sur **LinkedIn**</a>.
    * Etre notifié quand je fais des annonces ou que je lance de nouveaux outils (bien que j'utilise plus souvent Twitter 🤷‍♂).