@SuppressWarnings("nullness")
    ListenableFuture<List<V>> nonNull = nullable;
    return nonNull;
  }

  /**
   * Creates a {@link FutureCombiner} that processes the completed futures whether or not they're
   * successful.
   *
   * <p>Any failures from the input futures will not be propagated to the returned future.
   *
   * @since 20.0
   */
  @SafeVarargs

 * (or {@link FluentFuture#transform(com.google.common.base.Function, Executor)
 * FluentFuture.transform}), but you will often find it easier to use a framework. Frameworks
 * automate the process, often adding features like monitoring, debugging, and cancellation.
 * Examples of frameworks include:
 *
 * <ul>
 *   <li><a href="https://dagger.dev/producers.html">Dagger Producers</a>
 * </ul>
 *

 * (or {@link FluentFuture#transform(com.google.common.base.Function, Executor)
 * FluentFuture.transform}), but you will often find it easier to use a framework. Frameworks
 * automate the process, often adding features like monitoring, debugging, and cancellation.
 * Examples of frameworks include:
 *
 * <ul>
 *   <li><a href="https://dagger.dev/producers.html">Dagger Producers</a>
 * </ul>
 *

            return new OpenIdConnectCredential(attributes);
        } catch (final IOException e) {
            if (logger.isDebugEnabled()) {
                logger.debug("Failed to process callbacked request.", e);
            }
        }
        return null;
    }

    protected void parseJwtClaim(final String jwtClaim, final Map<String, Object> attributes) throws IOException {

 *
 * 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,
  internal val logger: Logger = TaskRunner.logger,
) {
  val lock: ReentrantLock = ReentrantLock()

   * method returns.
   *
   * <p>This method does not create any memory pressure as would be required to cause soft
   * references to be processed.
   *
   * @throws RuntimeException if timed out or interrupted while waiting
   * @since 12.0
   */
  @SuppressWarnings({"removal", "Finalize"}) // b/260137033
  public static void awaitFullGc() {

<div class="termy">

```console
$ uvicorn main:app --reload

INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO:     Started reloader process [28720]
INFO:     Started server process [28722]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
```

</div>

<details markdown="1">

        // simple checks first to short circuit processing below.
        if (WILDCARD.equals(pattern) || pattern.equals(originalId)) {
            result = true;
        } else {
            // process the list
            String[] repos = pattern.split(",");
            for (String repo : repos) {
                // see if this is a negative match
                if (repo.length() > 1 && repo.startsWith("!")) {

<div class="termy">

```console
$ uvicorn main:app --reload

INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO:     Started reloader process [28720]
INFO:     Started server process [28722]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
```

</div>

<details markdown="1">

Con **FastAPI** puedes aprovechar la concurrencia que es muy común para el desarrollo web (atractivo principal de NodeJS).

Pero también puedes aprovechar los beneficios del paralelismo y el multiprocesamiento (tener múltiples procesos ejecutándose en paralelo) para cargas de trabajo **CPU bound** como las de los sistemas de Machine Learning.