"pink":        "#e92063",
        "purple":      "#ab47bd",
        "deep-purple": "#7e56c2",
        "indigo":      "#4051b5",
        "blue":        "#2094f3",
        "light-blue":  "#02a6f2",
        "cyan":        "#00bdd6",
        "teal":        "#009485",
        "green":       "#4cae4f",
        "light-green": "#8bc34b",
        "lime":        "#cbdc38",
        "yellow":      "#ffec3d",

!!! info
    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:

That command also created a dummy file `docs/ht/index.md` for the main page, you can start by translating that one.

You can continue with the previous instructions for an "Existing Language" for that process.

You can make the first pull request with those two files, `docs/ht/mkdocs.yml` and `docs/ht/index.md`. 🎉

#### Preview the result

# Response Model - Return Type

You can declare the type used for the response by annotating the *path operation function* **return type**.

You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc.

=== "Python 3.10+"

    ```Python hl_lines="16  21"
    {!> ../../../docs_src/response_model/tutorial001_01_py310.py!}
    ```

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

!!! tip

# Middleware

You can add middleware to **FastAPI** applications.

A "middleware" is a function that works with every **request** before it is processed by any specific *path operation*. And also with every **response** before returning it.

* It takes each **request** that comes to your application.
* It can then do something to that **request** or run any needed code.

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

Several of these are explored in the next chapters of the tutorial.

## Order matters

When creating *path operations*, you can find situations where you have a fixed path.

#### Install `openapi-ts`

You can install `openapi-ts` in your frontend code with:

<div class="termy">

```console
$ npm install @hey-api/openapi-ts --save-dev

---> 100%
```

</div>

#### Generate Client Code

To generate the client code you can use the command line application `openapi-ts` that would now be installed.

    We are not restricted to having only one dependency that can return that type of data.

## Other models

You can now get the current user directly in the *path operation functions* and deal with the security mechanisms at the **Dependency Injection** level, using `Depends`.

And you can use any model or data for the security requirements (in this case, a Pydantic model `User`).

# Background Tasks - `BackgroundTasks`

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```