```

### Declare a `list` with a type parameter

To declare types that have type parameters (internal types), like `list`, `dict`, `tuple`:

* If you are in a Python version lower than 3.9, import their equivalent version from the `typing` module
* Pass the internal type(s) as "type parameters" using square brackets: `[` and `]`

In Python 3.9 it would be:

```Python
my_list: list[str]
```

    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

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

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

    Because of that, versions of FastAPI previous to 0.99.0 still used versions of OpenAPI lower than 3.1.0.

### Pydantic and FastAPI `examples`

When you add `examples` inside a Pydantic model, using `schema_extra` or `Field(examples=["something"])` that example is added to the **JSON Schema** for that Pydantic model.

## Top Translation Reviewers

These users are the **Top Translation Reviewers**. 🕵️

I only speak a few languages (and not very well 😅). So, the reviewers are the ones that have the [**power to approve translations**](contributing.md#translations){.internal-link target=_blank} of the documentation. Without them, there wouldn't be documentation in several other languages.

{% if people %}

        Item(name="Plumbus", price=32.0),
    ]
```

FastAPI will use the return type annotation to perform:

* Data validation
* Automatic documentation
    * It could power automatic client generators
* **Data filtering**

Before this version it was only supported via the `response_model` parameter.

If you are paying for 3 servers but you are using only a little bit of their RAM and CPU, you are probably **wasting money** 💸, and probably **wasting server electric power** 🌎, etc.

In that case, it could be better to have only 2 servers and use a higher percentage of their resources (CPU, memory, disk, network bandwidth, etc).

There you could buy me a coffee ☕️ to say thanks. 😄

And you can also become a Silver or Gold sponsor for FastAPI. 🏅🎉

## Sponsor the tools that power FastAPI

As you have seen in the documentation, FastAPI stands on the shoulders of giants, Starlette and Pydantic.

You can also sponsor:

To declare a **request** body, you use <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> models with all their power and benefits.

!!! info
    To send data, you should use one of: `POST` (the more common), `PUT`, `DELETE` or `PATCH`.

## Recap

You can use Pydantic Settings to handle the settings or configurations for your application, with all the power of Pydantic models.

* By using a dependency you can simplify testing.
* You can use `.env` files with it.