A jeśli istnieje jakaś konkretna potrzeba dotycząca stylu lub spójności, sam poproszę o zmiany lub dodam commity z takimi zmianami.

### Sprawdź kod

* Przeczytaj kod, zastanów się czy ma sens, **uruchom go lokalnie** i potwierdź czy faktycznie rozwiązuje problem.

* Następnie dodaj **komentarz** z informacją o tym, że sprawdziłeś kod, dzięki temu będę miał pewność, że faktycznie go sprawdziłeś.

!!! info

* Utilisez les mêmes exemples en Python et ne traduisez que le texte des documents. Vous n'avez pas besoin de changer quoi que ce soit pour que cela fonctionne.

* Utilisez les mêmes images, noms de fichiers et liens. Vous n'avez pas besoin de changer quoi que ce soit pour que cela fonctionne.

This idea of **asynchronous** code described above is also sometimes called **"concurrency"**. It is different from **"parallelism"**.

**Concurrency** and **parallelism** both relate to "different things happening more or less at the same time".

But the details between *concurrency* and *parallelism* are quite different.

To see the difference, imagine the following story about burgers:

### Concurrent Burgers

In this section you will see how to manage authentication and authorization with the same OAuth2 with scopes in your **FastAPI** application.

!!! warning
    This is a more or less advanced section. If you are just starting, you can skip it.

    You don't necessarily need OAuth2 scopes, and you can handle authentication and authorization however you want.

    ```

## Number validations: floats, greater than and less than

Number validations also work for `float` values.

Here's where it becomes important to be able to declare <abbr title="greater than"><code>gt</code></abbr> and not just <abbr title="greater than or equal"><code>ge</code></abbr>. As with it you can require, for example, that a value must be greater than `0`, even if it is less than `1`.

Now the client will get the same *HTTP 500 Internal Server Error* response, but the server will have our custom `InternalError` in the logs. 😎

## Execution of dependencies with `yield`

The sequence of execution is more or less like this diagram. Time flows from top to bottom. And each column is one of the parts interacting or executing code.

```mermaid
sequenceDiagram

participant client as Client
participant handler as Exception handler

# SQL (Relational) Databases

!!! info
    These docs are about to be updated. 🎉

    The current version assumes Pydantic v1, and SQLAlchemy versions less than 2.0.

    The new docs will include Pydantic v2 and will use <a href="https://sqlmodel.tiangolo.com/" class="external-link" target="_blank">SQLModel</a> (which is also based on SQLAlchemy) once it is updated to use Pydantic v2 as well.

**FastAPI** doesn't require you to use a SQL (relational) database.

* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
* **Easy**: Designed to be easy to use and learn. Less time reading docs.
* **Short**: Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.

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

    assert response.status_code == 422
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "less_than",
                    "loc": ["path", "item_id"],
                    "msg": "Input should be less than 3",
                    "input": "42",
                    "ctx": {"lt": 3.0},
                }
            ]
        }
    ) | IsDict(