## Using `BackgroundTasks`

First, import `BackgroundTasks` and define a parameter in your *path operation function* with a type declaration of `BackgroundTasks`:

{* ../../docs_src/background_tasks/tutorial001.py hl[1,13] *}

**FastAPI** will create the object of type `BackgroundTasks` for you and pass it as that parameter.

## Create a task function

Create a function to be run as the background task.

```

### Eine `list`e mit einem Typ-Parameter deklarieren

Um Typen wie `list`, `dict`, `tuple` mit inneren Typ-Parametern (inneren Typen) zu deklarieren:

* Wenn Sie eine Python-Version kleiner als 3.9 verwenden, importieren Sie das Äquivalent zum entsprechenden Typ vom `typing`-Modul
* Überreichen Sie den/die inneren Typ(en) von eckigen Klammern umschlossen, `[` und `]`, als „Typ-Parameter“

In Python 3.9 wäre das:

```Python

   *
   * @param iterator the iterator whose minimum element is to be determined
   * @throws NoSuchElementException if {@code iterator} is empty
   * @throws ClassCastException if the parameters are not <i>mutually comparable</i> under this
   *     ordering.
   * @since 11.0
   */
  @ParametricNullness
  public <E extends T> E min(Iterator<E> iterator) {

# Body - Fields

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field`

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

# Response-Header

## Verwenden Sie einen `Response`-Parameter

Sie können einen Parameter vom Typ `Response` in Ihrer *Pfadoperation-Funktion* deklarieren (wie Sie es auch für Cookies tun können).

Und dann können Sie Header in diesem *vorübergehenden* Response-Objekt festlegen.

```Python hl_lines="1  7-8"
{!../../docs_src/response_headers/tutorial002.py!}
```

    /**
     * Moves the cursor up. If the parameter y is negative it moves the cursor down.
     *
     * @param y the number of lines to move up
     * @return this Ansi instance
     */
    public Ansi cursorUp(final int y) {
        return y > 0 ? appendEscapeSequence('A', y) : y < 0 ? cursorDown(-y) : this;
    }

    /**
     * Moves the cursor down. If the parameter y is negative it moves the cursor up.
     *

func (l *List[T]) Len() int  { … }
</pre>

<h3 id="Type_parameter_declarations">Type parameter declarations</h3>

<p>
A type parameter list declares the <i>type parameters</i> of a generic function or type declaration.
The type parameter list looks like an ordinary <a href="#Function_types">function parameter list</a>
except that the type parameter names must all be present and the list is enclosed
in square brackets rather than parentheses

{!> ../../docs_src/dependencies/tutorial005.py!}
```

////

Let's focus on the parameters declared:

* Even though this function is a dependency ("dependable") itself, it also declares another dependency (it "depends" on something else).
    * It depends on the `query_extractor`, and assigns the value returned by it to the parameter `q`.
* It also declares an optional `last_query` cookie, as a `str`.

{!> ../../docs_src/body_nested_models/tutorial002.py!}
```

### Declare a `list` with a type parameter

To declare types that have type parameters (internal types), like `list`, `dict`, `tuple`:

* If you are in a Python version lower than 3.9, import their equivalent version from the `typing` module
* Pass the internal type(s) as "type parameters" using square brackets: `[` and `]`

In Python 3.9 it would be:

```Python

# Paramètres de chemin

Vous pouvez déclarer des "paramètres" ou "variables" de chemin avec la même syntaxe que celle utilisée par le
<a href="https://docs.python.org/fr/3/library/string.html#format-string-syntax" class="external-link" target="_blank">formatage de chaîne Python</a> :


```Python hl_lines="6-7"
{!../../docs_src/path_params/tutorial001.py!}
```

La valeur du paramètre `item_id` sera transmise à la fonction dans l'argument `item_id`.