// Since this is an artificially generated type variable, we don't bother checking
          // subtyping between declared type bound and actual type bound. So it's possible that we
          // may generate something like <capture#1-of ? extends Foo&SubFoo>.
          // Checking subtype between declared and actual type bounds
          // adds recursive isSubtypeOf() call and feels complicated.

Mais vous pouvez toujours les documenter comme décrit dans [Additional Responses in OpenAPI](additional-responses.md){.internal-link target=_blank}.

   *       AbstractPackageSanityTests} doesn't know how to construct, the test will fail.
   *   <li>If there is no visible constructor or visible static factory method declared by {@code
   *       C}, {@code C} is skipped for serialization test, even if it implements {@link
   *       Serializable}.
   *   <li>Serialization test is not performed on method return values unless the method is a

Because each SQLModel model is also a Pydantic model, you can use it in the same **type annotations** that you could use Pydantic models.

For example, if you declare a parameter of type `Hero`, it will be read from the **JSON body**.

The same way, you can declare it as the function's **return type**, and then the shape of the data will show up in the automatic API docs UI.

We can do better...

## What makes a dependency { #what-makes-a-dependency }

Up to now you have seen dependencies declared as functions.

But that's not the only way to declare dependencies (although it would probably be the more common).

The key factor is that a dependency should be a "callable".

///

/// note

This is supported since FastAPI version `0.113.0`. 🤓

///

## Pydantic Models for Forms { #pydantic-models-for-forms }

You just need to declare a **Pydantic model** with the fields you want to receive as **form fields**, and then declare the parameter as `Form`:

{* ../../docs_src/request_form_models/tutorial001_an_py39.py hl[9:11,15] *}

* Les arguments nommés à passer à la fonction de tâche (`message="some notification"`).

## Injection de dépendances

Utiliser `BackgroundTasks` fonctionne aussi avec le système d'injection de dépendances. Vous pouvez déclarer un paramètre de type `BackgroundTasks` à différents niveaux : dans une *fonction de chemin*, dans une dépendance, dans une sous-dépendance...

Estas funciones pueden ser declaradas con `async def` o `def` normal.

### Evento `startup`

Para añadir una función que debería ejecutarse antes de que la aplicación inicie, declárala con el evento `"startup"`:

{* ../../docs_src/events/tutorial001.py hl[8] *}

En este caso, la función manejadora del evento `startup` inicializará los ítems de la "base de datos" (solo un `dict`) con algunos valores.

Although any other parameter declared normally (for example, the body with a Pydantic model) would still be validated, converted, annotated, etc.

But there are specific cases where it's useful to get the `Request` object.

You can declare a parameter of type `Response` in your *path operation function*.

And then you can set cookies in that *temporal* response object.

{* ../../docs_src/response_cookies/tutorial002.py hl[1, 8:9] *}

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).