# Concurrence et les mots-clés async et await

Cette page vise à fournir des détails sur la syntaxe `async def` pour les *fonctions de chemins* et quelques rappels sur le code asynchrone, la concurrence et le parallélisme.

## Vous êtes pressés ?

<abbr title="'too long; didn't read' en anglais, ou 'trop long ; j'ai pas lu'"><strong>TL;DR :</strong></abbr>

Si vous utilisez des bibliothèques tierces qui nécessitent d'être appelées avec `await`, telles que :

## Pydantic

Toda a validação de dados é feita por baixo dos panos pelo <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>, então você tem todos os benefícios disso. E assim você sabe que está em boas mãos.

Você pode usar as mesmas declarações de tipo com `str`, `float`, `bool` e muitos outros tipos complexos de dados.

Vamos explorar muitos destes tipos nos próximos capítulos do tutorial.

## A ordem importa

=== "Python 3.10+"

    ```Python
    q: Annotated[str | None] = None
    ```

=== "Python 3.8+"

    ```Python
    q: Annotated[Union[str, None]] = None
    ```

Both of those versions mean the same thing, `q` is a parameter that can be a `str` or `None`, and by default, it is `None`.

Now let's jump to the fun stuff. 🎉

## Add `Query` to `Annotated` in the `q` parameter

### Concurrency and Burgers

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:

```Python
if "stanleyjobsox" == "stanleyjobson" and "love123" == "swordfish":
    ...
```

Python will have to compare the whole `stanleyjobso` in both `stanleyjobsox` and `stanleyjobson` before realizing that both strings are not the same. So it will take some extra microseconds to reply back "Incorrect username or password".

#### The time to answer helps the attackers

We want to get the `current_user` *only* if this user is active.

So, we create an additional dependency `get_current_active_user` that in turn uses `get_current_user` as a dependency.

Both of these dependencies will just return an HTTP error if the user doesn't exist, or if is inactive.

So, in our endpoint, we will only get a user if the user exists, was correctly authenticated, and is active:

    These Pydantic models define more or less a "schema" (a valid data shape).

    So this will help us avoiding confusion while using both.

### Create the Pydantic *models* / schemas

Create all the same Pydantic models as in the SQLAlchemy tutorial:

```Python hl_lines="16-18  21-22  25-30  34-35  38-39  42-48"

You will see the JSON response as:

```JSON
{"item_id": 5, "q": "somequery"}
```

You already created an API that:

* Receives HTTP requests in the _paths_ `/` and `/items/{item_id}`.
* Both _paths_ take `GET` operations (also known as HTTP _methods_).
* The _path_ `/items/{item_id}` has a _path parameter_ `item_id` that should be an `int`.

    ```

Those parameters are what **FastAPI** will use to "solve" the dependency.

In both cases, it will have:

* An optional `q` query parameter that is a `str`.
* A `skip` query parameter that is an `int`, with a default of `0`.
* A `limit` query parameter that is an `int`, with a default of `100`.

In both cases the data will be converted, validated, documented on the OpenAPI schema, etc.

## Use it

    You can probably skip this part.

There's an alternative way to define this logic to be executed during *startup* and during *shutdown*.