By doing that, your editor can provide support even while processing items from the list:

<img src="/img/python-types/image05.png">

Without types, that's almost impossible to achieve.

Notice that the variable `item` is one of the elements in the list `items`.

And still, the editor knows it is a `str`, and provides support for that.

#### Tuple and Set

* <a href="https://code.visualstudio.com/" class="external-link" target="_blank">Visual Studio Code</a> ile:

![editor support](https://fastapi.tiangolo.com/img/vscode-completion.png)

* <a href="https://www.jetbrains.com/pycharm/" class="external-link" target="_blank">PyCharm</a> ile:

![editor support](https://fastapi.tiangolo.com/img/pycharm-completion.png)

!!! tip
    If you have strict type checks in your editor, mypy, etc, you can declare the function return type as `Any`.

    That way you tell the editor that you are intentionally returning anything. But FastAPI will still do the data documentation, validation, filtering, etc. with the `response_model`.

### `response_model` Priority

エディターがどのように役立つかを以下に示します:

* <a href="https://code.visualstudio.com/" class="external-link" target="_blank">Visual Studio Code</a>の場合:

![editor support](https://fastapi.tiangolo.com/img/vscode-completion.png)

* <a href="https://www.jetbrains.com/pycharm/" class="external-link" target="_blank">PyCharm</a>の場合:

![editor support](https://fastapi.tiangolo.com/img/pycharm-completion.png)

And it generates OpenAPI schemas.

That's how it works in Flask, Starlette, Responder, etc.

But then, we have again the problem of having a micro-syntax, inside of a Python string (a big YAML).

The editor can't help much with that. And if we modify parameters or Marshmallow schemas and forget to also modify that YAML docstring, the generated schema would be obsolete.

!!! info

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

E também serão utilizados em cada *função de operação de rota* que utilizá-los:

<img src="/img/tutorial/body/image02.png">

## Suporte do editor de texto:

No seu editor de texto, dentro da função você receberá dicas de tipos e completação em todo lugar (isso não aconteceria se você recebesse um `dict` em vez de um modelo Pydantic):

<img src="/img/tutorial/body/image03.png">

...de:

```Python
        ... "item_name": item.name ...
```

...a:

```Python
        ... "item_price": item.price ...
```

... y mira como el editor va a auto-completar los atributos y sabrá sus tipos:

![soporte de editor](https://fastapi.tiangolo.com/img/vscode-completion.png)

* trong <a href="https://code.visualstudio.com/" class="external-link" target="_blank">Visual Studio Code</a>:

![editor support](https://fastapi.tiangolo.com/img/vscode-completion.png)

* trong <a href="https://www.jetbrains.com/pycharm/" class="external-link" target="_blank">PyCharm</a>:

![editor support](https://fastapi.tiangolo.com/img/pycharm-completion.png)

```Python hl_lines="15"
{!../../../docs_src/body_nested_models/tutorial008.py!}
```

## Suporte de editor em todo canto

E você obtém suporte do editor em todos os lugares.

Mesmo para itens dentro de listas:

<img src="/img/tutorial/body-nested-models/image01.png">

Você não conseguiria este tipo de suporte de editor se estivesse trabalhando diretamente com `dict` em vez de modelos Pydantic.

...from:

```Python
        ... "item_name": item.name ...
```

...to:

```Python
        ... "item_price": item.price ...
```

...and see how your editor will auto-complete the attributes and know their types:

![editor support](https://fastapi.tiangolo.com/img/vscode-completion.png)