# Response Headers { #response-headers }

## Use a `Response` parameter { #use-a-response-parameter }

You can declare a parameter of type `Response` in your *path operation function* (as you can do for cookies).

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

{* ../../docs_src/response_headers/tutorial002_py310.py hl[1, 7:8] *}

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

///

/// tip | Dica

Essa mesma técnica se aplica para `Query`, `Cookie`, e `Header`. 😎

///

## Cookies com Modelos Pydantic { #cookies-with-a-pydantic-model }

Declare os parâmetros de **cookie** de que você precisa em um **modelo Pydantic**, e depois declare o parâmetro como `Cookie`:

{* ../../docs_src/cookie_param_models/tutorial001_an_py310.py hl[9:12,16] *}

                            * `security_scopes.scopes` contiendra `[]` (rien) pour le *chemin d’accès* `read_system_status`, car il n’a déclaré aucun `Security` avec des `scopes`, et sa dépendance, `get_current_user`, ne déclare pas non plus de `scopes`.

/// tip | Astuce

  @J2ktIncompatible // Incompatible return type change. Use inherited implementation
  public Object[] toArray() {
    /*
     * If we could, we'd declare the no-arg `Collection.toArray()` to return "Object[] but elements
     * have the same nullness as E." Since we can't, we declare it to return nullable elements, and
     * we can override it in our non-null-guaranteeing subtypes to present a better signature to
     * their users.
     *

But that is still not that useful.

Let's make it give us the current user.

## Create a user model { #create-a-user-model }

First, let's create a Pydantic user model.

The same way we use Pydantic to declare bodies, we can use it anywhere else:

{* ../../docs_src/security/tutorial002_an_py310.py hl[5,12:6] *}

## Create a `get_current_user` dependency { #create-a-get-current-user-dependency }

# Background Tasks - `BackgroundTasks`

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```

These functions can be declared with `async def` or normal `def`.

### `startup` event { #startup-event }

To add a function that should be run before the application starts, declare it with the event `"startup"`:

{* ../../docs_src/events/tutorial001_py310.py hl[8] *}

In this case, the `startup` event handler function will initialize the items "database" (just a `dict`) with some values.

        "price": 42.0,
        "tax": 3.2
    },
    "user": {
        "username": "dave",
        "full_name": "Dave Grohl"
    }
}
```

/// note | Remarque

Notez que, bien que `item` ait été déclaré de la même manière qu'auparavant, il est désormais attendu à l'intérieur du corps de la requête sous la clé `item`.

///

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

Read more about it in the [FastAPI docs about using Request directly](https://fastapi.tiangolo.com/advanced/using-request-directly/)

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

/// tip

## Parameterized dependencies { #parameterized-dependencies }

All the dependencies we have seen are a fixed function or class.

But there could be cases where you want to be able to set parameters on the dependency, without having to declare many different functions or classes.

Let's imagine that we want to have a dependency that checks if the query parameter `q` contains some fixed content.

But we want to be able to parameterize that fixed content.