* executor keeps it alive). Ideally, nulling out `callable` would be the responsibility of
       * InterruptibleTask itself so that its other subclasses also benefit. (Handling `callable` in
       * InterruptibleTask itself might also eliminate some of the existing boilerplate for, e.g.,
       * pendingToString().)
       */
      CombinedFuture.this.task = null;

/// tip | Astuce

**GraphQL** résout des cas d'utilisation très spécifiques.

Il présente des **avantages** et des **inconvénients** par rapport aux **API web** classiques.

Assurez-vous d'évaluer si les **bénéfices** pour votre cas d'utilisation compensent les **inconvénients**. 🤓

///

## Bibliothèques GraphQL { #graphql-libraries }

 * instance for non-daemon threads.
 *
 * The task runner is also responsible for releasing held threads when the library is unloaded.
 * This is for the benefit of container environments that implement code unloading.
 *
 * Most applications should share a process-wide [TaskRunner] and use queues for per-client work.
 */
class TaskRunner(
  val backend: Backend,

   *     associated FinalizableReferenceQueue is no longer referenced.
   */
  private boolean finalizeReference(Reference<?> reference, Method finalizeReferentMethod) {
    /*
     * This is for the benefit of phantom references. Weak and soft references will have already
     * been cleared by this point.
     */
    reference.clear();

    if (reference == frqReference) {
      /*

Keep in mind that this means that the whole contents will be stored in memory. This will work well for small files.

But there are several cases in which you might benefit from using `UploadFile`.

## File Parameters with `UploadFile` { #file-parameters-with-uploadfile }

Define a file parameter with a type of `UploadFile`:

{* ../../docs_src/request_files/tutorial001_an_py310.py hl[14] *}

Sie können diese Vorlage verwenden, um loszulegen, da sie bereits vieles der anfänglichen Einrichtung, Sicherheit, Datenbank und einige API-Endpunkte für Sie eingerichtet hat.

GitHub-Repository: [Full Stack FastAPI Template](https://github.com/tiangolo/full-stack-fastapi-template)

### Rückgabewerte { #return-values }

Und sie können Werte zurückgeben oder nicht, die Werte werden nicht verwendet.

Sie können also eine normale Abhängigkeit (die einen Wert zurückgibt), die Sie bereits an anderer Stelle verwenden, wiederverwenden, und auch wenn der Wert nicht verwendet wird, wird die Abhängigkeit ausgeführt:

{* ../../docs_src/dependencies/tutorial006_an_py310.py hl[11,16] *}

		// passing in valid object name.
		{"object", []int{14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}},
		{"The Shining Script <v1>.pdf", []int{16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}},
		{"Cost Benefit Analysis (2009-2010).pptx", []int{15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14}},
		{"117Gn8rfHL2ACARPAhaFd0AGzic9pUbIA/5OCn5A", []int{3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2}},

## Caveat { #caveat }

If you need to perform heavy background computation and you don't necessarily need it to be run by the same process (for example, you don't need to share memory, variables, etc), you might benefit from using other bigger tools like [Celery](https://docs.celeryq.dev).

Additional integration tests for a certain elasticsearch modules that are specific to certain cluster configuration can be declared in a separate so called `qa` subproject of your module.

The benefit of a dedicated project for these tests are:
- `qa` projects are dedicated two specific usecases and easier to maintain
- It keeps the specific test logic separated from the common test logic.