But it's possible to customize it, you can set a specific CDN, or serve the files yourself.

## Custom CDN for JavaScript and CSS { #custom-cdn-for-javascript-and-css }

        assertEquals("In progress", statusMap.get(CrawlerStatus.RUNNING));
        assertEquals("Completed", statusMap.get(CrawlerStatus.DONE));

        // Test with EnumMap for better performance
        java.util.EnumMap<CrawlerStatus, String> enumMap = new java.util.EnumMap<>(CrawlerStatus.class);
        enumMap.put(CrawlerStatus.INITIALIZING, "Init");
        enumMap.put(CrawlerStatus.RUNNING, "Run");

 * as the traditional heap data structure used in {@link PriorityQueue}.
 *
 * <p>This class is not thread-safe, and does not accept null elements.
 *
 * <p><i>Performance notes:</i>
 *
 * <ul>
 *   <li>If you only access one end of the queue, and do use a maximum size, this class will perform
 *       significantly worse than a {@code PriorityQueue} with manual eviction above the maximum

Example:

    Source (English):

        «««
        [One of the fastest Python frameworks available](#performance)
        »»»

    Result (German):

        «««
        [Eines der schnellsten verfügbaren Python-Frameworks](#performance)
        »»»

Con **FastAPI** obtienes todas las funcionalidades de **Starlette** (ya que FastAPI es simplemente Starlette potenciado):

* Rendimiento seriamente impresionante. Es <a href="https://github.com/encode/starlette#performance" class="external-link" target="_blank">uno de los frameworks de Python más rápidos disponibles, a la par de **NodeJS** y **Go**</a>.
* Soporte para **WebSocket**.
* Tareas en segundo plano en el mismo proceso.

 * the columns. The reverse is also available, associating a column with a row key / value map. Note
 * that, in some implementations, data access by column key may have fewer supported operations or
 * worse performance than data access by row key.
 *
 * <p>The methods returning collections or maps always return views of the underlying table.
 * Updating the table can change the contents of those collections, and updating the collections

                }
            });
        }

        long endTime = System.currentTimeMillis();
        long duration = endTime - startTime;

        // Then - should complete quickly (this is more of a performance indicator)
        assertTrue(duration < 1000, "Creating and using 10000 EmptyIterators should be fast (took " + duration + "ms)");
    }

    @Test

   * all super-classes, that are annotated with {@code @Subscribe}. The cache is shared across all
   * instances of this class; this greatly improves performance if multiple EventBus instances are
   * created and objects of the same class are registered on all of them.
   */
  private static final LoadingCache<Class<?>, ImmutableList<Method>> subscriberMethodsCache =

 *       in any other way than how {@code Stopwatch} uses them.
 *   <li>An alternative source of nanosecond ticks can be substituted, for example for testing or
 *       performance reasons, without affecting most of your code.
 * </ul>
 *
 * <p>The one downside of {@code Stopwatch} relative to {@link System#nanoTime()} is that {@code

   * This implementation requires O(|N|) time. Classes extending this one may manually keep track of
   * the number of edges as the graph is updated, and override this method for better performance.
   */
  protected long edgeCount() {
    long degreeSum = 0L;
    for (N node : nodes()) {
      degreeSum += degree(node);
    }