## 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.

## API Request

To make an STS API request with this method, send a POST request to the MinIO endpoint with following query parameters:

| Parameter       | Type    | Required |                                                                      |
|-----------------|---------|----------|----------------------------------------------------------------------|

    //                                     Parameter Logging
    //                                     -----------------
    // logging filter cannot show the parameters when multi-part so logging here
    protected void showFieldLoggingTitle() {
        if (logger.isDebugEnabled()) {
            logger.debug("[Multipart Request Parameter]");
        }
    }

```

////

Obwohl Sie `Depends` in den Parametern Ihrer Funktion genauso verwenden wie `Body`, `Query`, usw., funktioniert `Depends` etwas anders.

Sie übergeben `Depends` nur einen einzigen Parameter.

Dieser Parameter muss so etwas wie eine Funktion sein.

Sie **rufen diese nicht direkt auf** (fügen Sie am Ende keine Klammern hinzu), sondern übergeben sie einfach als Parameter an `Depends()`.

* `@app.get()`
* `@app.post()`
* `@app.put()`
* `@app.delete()`
* etc.

{* ../../docs_src/response_status_code/tutorial001.py hl[6] *}

/// note

Notice that `status_code` is a parameter of the "decorator" method (`get`, `post`, etc). Not of your *path operation function*, like all the parameters and body.

///

        </field>
      </fields>
    </class>

    <class xdoc.anchorName="parameter">
      <name>Parameter</name>
      <version>1.0.0+</version>
      <description>A parameter description.</description>
      <!-- see o.a.m.plugin.descriptor.Parameter -->
      <fields>
        <field>
          <name>name</name>
          <version>1.0.0+</version>

# 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!}
```

import java.lang.annotation.Target;

/**
 * Marks a method as an event subscriber.
 *
 * <p>The type of event will be indicated by the method's first (and only) parameter, which cannot
 * be primitive. If this annotation is applied to methods with zero parameters, or more than one
 * parameter, the object containing the method will not be able to register for event delivery from
 * the {@link EventBus}.
 *

{!> ../../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`.

# 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