And these models are all sharing a lot of the data and duplicating attribute names and types.

We could do better.

We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).

### Tested

* 100% <abbr title="The amount of code that is automatically tested">test coverage</abbr>.
* 100% <abbr title="Python type annotations, with this your editor and external tools can give you better support">type annotated</abbr> code base.
* Used in production applications.

## Starlette features

But you don't have to worry about them either, incoming dicts are converted automatically and your output is converted automatically to JSON too.

## Bodies of arbitrary `dict`s

You can also declare a body as a `dict` with keys of some type and values of some other type.

### 💯

* 1️⃣0️⃣0️⃣ 💯 <abbr title="The amount of code that is automatically tested">💯 💰</abbr>.
* 1️⃣0️⃣0️⃣ 💯 <abbr title="Python type annotations, with this your editor and external tools can give you better support">🆎 ✍</abbr> 📟 🧢.
* ⚙️ 🏭 🈸.

## 💃 ⚒

**FastAPI** 🍕 🔗 ⏮️ (&amp; ⚓️ 🔛) <a href="https://www.starlette.io/" class="external-link" target="_blank"><strong>💃</strong></a>. , 🙆 🌖 💃 📟 👆 ✔️, 🔜 👷.

Or it might be the case that you just prefer to take other courses because they adapt better to your learning style.

### Is concurrency better than parallelism?

Nope! That's not the moral of the story.

Concurrency is different than parallelism. And it is better on **specific** scenarios that involve a lot of waiting. Because of that, it generally is a lot better than parallelism for web application development. But not for everything.

    Feel free to skip this.

    Peewee is not recommended with FastAPI as it doesn't play well with anything async Python. There are several better alternatives.

!!! info
    These docs assume Pydantic v1.

    Because Pewee doesn't play well with anything async and there are better alternatives, I won't update these docs for Pydantic v2, they are kept for now only for historical purposes.

```json
{"message": "Hello World"}
```

...this response will return:

```json
{
  "message": "Hello World"
}
```

Of course, you will probably find much better ways to take advantage of this than formatting JSON. 😉

## Default response class

When creating a **FastAPI** class instance or an `APIRouter` you can specify which response class to use by default.

!!! tip
    The important and "magic" thing here is that `get_current_user` will have a different list of `scopes` to check for each *path operation*.

...and adapt it with your database data and credentials (equivalently for MySQL, MariaDB or any other).

!!! tip

    This is the main line that you would have to modify if you wanted to use a different database.

### Create the SQLAlchemy `engine`

The first step is to create a SQLAlchemy "engine".

We will later use this `engine` in other places.

```Python hl_lines="8-10"