But in this case, the same **FastAPI** application will handle the API and the authentication.

So, let's review it from that simplified point of view:

* The user types the `username` and `password` in the frontend, and hits `Enter`.
* The frontend (running in the user's browser) sends that `username` and `password` to a specific URL in our API (declared with `tokenUrl="token"`).

It had automatic data validation, data serialization and OpenAPI schema generation based on the same type hints in several places.

Some of them also ✨ [**sponsor FastAPI**](../help-fastapi.md#sponsor-the-author){.internal-link target=_blank} ✨, this ensures the continued and healthy **development** of FastAPI and its **ecosystem**.

And it shows their true commitment to FastAPI and its **community** (you), as they not only want to provide you a **good service** but also want to make sure you have a **good and healthy framework**, FastAPI. 🙇

# About FastAPI versions

**FastAPI** is already being used in production in many applications and systems. And the test coverage is kept at 100%. But its development is still moving quickly.

New features are added frequently, bugs are fixed regularly, and the code is still continuously improving.

# About

      - name: Install Dependencies
        if: steps.cache.outputs.cache-hit != 'true'
        run: pip install -r requirements-tests.txt
      - name: Install Pydantic v2
        run: pip install "pydantic>=2.0.2,<3.0.0"
      - name: Lint
        run: bash scripts/lint.sh

  test:

# Вступ до типів Python

Python підтримує додаткові "підказки типу" ("type hints") (також звані "анотаціями типу" ("type annotations")).

Ці **"type hints"** є спеціальним синтаксисом, що дозволяє оголошувати <abbr title="наприклад: str, int, float, bool">тип</abbr> змінної.

За допомогою оголошення типів для ваших змінних, редактори та інструменти можуть надати вам кращу підтримку.

```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

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

    If you have a Pydantic model in your test and you want to send its data to the application during testing, you can use the `jsonable_encoder` described in [JSON Compatible Encoder](encoder.md){.internal-link target=_blank}.

## Run it

After that, you just need to install `pytest`:

FastAPI will use this `response_model` to do all the data documentation, validation, etc. and also to **convert and filter the output data** to its type declaration.

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