In the previous example, because the classes were different, we had to use the `response_model` parameter. But that also means that we don't get the support from the editor and tools checking the function return type.

But in most of the cases where we need to do something like this, we want the model just to **filter/remove** some of the data as in this example.

!!! info
    À moins que vous ne spécifiiez explicitement un type de média différent dans votre paramètre `responses`, FastAPI supposera que la réponse a le même type de média que la classe de réponse principale (par défaut `application/json`).

    Mais si vous avez spécifié une classe de réponse personnalisée avec `None` comme type de média, FastAPI utilisera `application/json` pour toute réponse supplémentaire associée à un modèle.

## Combinaison d'informations

### Création d'un `Enum`

Importez `Enum` et créez une sous-classe qui hérite de `str` et `Enum`.

En héritant de `str` la documentation sera capable de savoir que les valeurs doivent être de type `string` et pourra donc afficher cette `Enum` correctement.

Créez ensuite des attributs de classe avec des valeurs fixes, qui seront les valeurs autorisées pour cette énumération.

```Python hl_lines="1  6-9"

But it was created before there existed Python type hints. So, to define every <abbr title="the definition of how data should be formed">schema</abbr> you need to use specific utils and classes provided by Marshmallow.

!!! check "Inspired **FastAPI** to"
    Use code to define "schemas" that provide data types and validation, automatically.

You can import it directly form `fastapi`:

```python
from fastapi import WebSocketDisconnect
```

::: fastapi.WebSocketDisconnect

## WebSockets - additional classes

Additional classes for handling WebSockets.

Provided directly by Starlette, but you can import it from `fastapi`:

```python
from fastapi.websockets import WebSocketDisconnect, WebSocketState
```

    * `Optional`
    * ...and others.

=== "Python 3.8+"

    * `List`
    * `Tuple`
    * `Set`
    * `Dict`
    * `Union`
    * `Optional`
    * ...and others.

### Classes as types

You can also declare a class as the type of a variable.

Let's say you have a class `Person`, with a name:

```Python hl_lines="1-3"
{!../../../docs_src/python_types/tutorial010.py!}
```

* 🔧 Add CryptAPI sponsor. PR [#4264](https://github.com/tiangolo/fastapi/pull/4264) by [@tiangolo](https://github.com/tiangolo).
* 📝 Update `docs/tutorial/dependencies/classes-as-dependencies`: Add type of query parameters in a description of `Classes as dependencies`. PR [#4015](https://github.com/tiangolo/fastapi/pull/4015) by [@0417taehyun](https://github.com/0417taehyun).

    * Como as estruturas de dados do Pydantic são apenas instâncias de classes que você define, a auto completação, _linting_, _mypy_ e a sua intuição devem funcionar corretamente com seus dados validados.
* Valida **estruturas complexas**:

### Criando uma classe `Enum`

Importe `Enum` e crie uma sub-classe que herde de `str` e de `Enum`.

Por herdar de `str` a documentação da API vai ser capaz de saber que os valores devem ser do tipo `string` e assim ser capaz de mostrar eles corretamente.

Assim, crie atributos de classe com valores fixos, que serão os valores válidos disponíveis.

### Passo 1: importe `FastAPI`

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

`FastAPI` é uma classe Python que fornece todas as funcionalidades para sua API.

!!! note "Detalhes técnicos"
    `FastAPI` é uma classe que herda diretamente de `Starlette`.