But if you return a `Response` directly (or any subclass, like `JSONResponse`), the data won't be automatically converted (even if you declare a `response_model`), and the documentation won't be automatically generated (for example, including the specific "media type", in the HTTP header `Content-Type` as part of the generated OpenAPI).

# 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
```

The dependency injection system requires pre-registration of the dependencies and the dependencies are solved based on the declared types. So, it's not possible to declare more than one "component" that provides a certain type.

# `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.

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.

  @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.
     *

## Dependencies errors and return values { #dependencies-errors-and-return-values }

You can use the same dependency *functions* you use normally.

### Dependency requirements { #dependency-requirements }

They can declare request requirements (like headers) or other sub-dependencies:

{* ../../docs_src/dependencies/tutorial006_an_py39.py hl[8,13] *}

### Raise exceptions { #raise-exceptions }

Note that in this case, we are declaring a path parameter beside the request parameter.

So, the path parameter will be extracted, validated, converted to the specified type and annotated with OpenAPI.

The same way, you can declare any other parameter as normally, and additionally, get the `Request` too.

///

## `Request` documentation { #request-documentation }

Esto hará que `tags` sea una lista, aunque no declare el tipo de los elementos de la lista.

## Campos de lista con parámetro de tipo { #list-fields-with-type-parameter }

Pero Python tiene una forma específica de declarar listas con tipos internos, o "parámetros de tipo":

### Declarar una `list` con un parámetro de tipo { #declare-a-list-with-a-type-parameter }

## Importar `Header` { #import-header }

Primero importa `Header`:

{* ../../docs_src/header_params/tutorial001_an_py310.py hl[3] *}

## Declarar parámetros de `Header` { #declare-header-parameters }

Luego declara los parámetros de header usando la misma estructura que con `Path`, `Query` y `Cookie`.

Puedes definir el valor por defecto así como toda la validación extra o los parámetros de anotaciones: