*         <li>20 levels: average of 393ns per lock()/unlock()
 *       </ul>
 * </ul>
 *
 * <p>As such, the CycleDetectingLockFactory may not be suitable for performance-critical
 * applications which involve tightly-looped or deeply-nested locking algorithms.
 *
 * @author Darick Tong
 * @since 13.0
 */
@J2ktIncompatible
@GwtIncompatible
public class CycleDetectingLockFactory {

  /**

      }
      int oldSize = size(); // calls refreshIfEmpty

      // Guava issue 1013: AbstractSet and most JDK set implementations are
      // susceptible to quadratic removeAll performance on lists;
      // use a slightly smarter implementation here
      boolean changed = Sets.removeAllImpl((Set<V>) delegate, c);
      if (changed) {
        int newSize = delegate.size();
        totalSize += newSize - oldSize;
        removeIfEmpty();

  //     Iterable<? extends T> iterable,
  //     Predicate<? super T> predicate,
  //     @JointlyNullable T defaultValue);
  //
  // ...where "@JointlyNullable" is similar to @PolyNull but slightly different:
  //
  // - @PolyNull means "@Nullable or @Nonnull"
  //   (That would be unsound for an input Iterable<@Nullable Foo>. So, if we wanted to use

  //     Iterable<? extends T> iterable,
  //     Predicate<? super T> predicate,
  //     @JointlyNullable T defaultValue);
  //
  // ...where "@JointlyNullable" is similar to @PolyNull but slightly different:
  //
  // - @PolyNull means "@Nullable or @Nonnull"
  //   (That would be unsound for an input Iterable<@Nullable Foo>. So, if we wanted to use

	if err != nil {
		writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
		return
	}

	// We have to adjust the size of encrypted parts since encrypted parts
	// are slightly larger due to encryption overhead.
	// Further, we have to adjust the ETags of parts when using SSE-S3.
	// Due to AWS S3, SSE-S3 encrypted parts return the plaintext ETag

   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,

And even if you were not using FastAPI, you could also write your own async applications with [AnyIO](https://anyio.readthedocs.io/en/stable/) to be highly compatible and get its benefits (e.g. *structured concurrency*).

      }
      int oldSize = size(); // calls refreshIfEmpty

      // Guava issue 1013: AbstractSet and most JDK set implementations are
      // susceptible to quadratic removeAll performance on lists;
      // use a slightly smarter implementation here
      boolean changed = Sets.removeAllImpl((Set<V>) delegate, c);
      if (changed) {
        int newSize = delegate.size();
        totalSize += newSize - oldSize;
        removeIfEmpty();

      map1.put(i, null);
    }
    assertWithMessage("table size after adding %s elements", size)
        .that(bucketsOf(map1))
        .isEqualTo(initialBuckets);

    /*
     * Something slightly different happens when the entries are added all at
     * once; make sure that passes too.
     */
    map2.putAll(map1);
    assertWithMessage("table size after adding %s elements", size)

	if objAPI == nil {
		return np, grid.NewRemoteErr(errServerNotInitialized)
	}

	pools, ok := objAPI.(*erasureServerPools)
	if !ok {
		return np, nerr
	}

	// No need to return errors, this is not a highly strict operation.
	uploadID := mss.Get(peerRESTUploadID)
	if uploadID != "" {
		pools.ClearUploadID(uploadID)
	}

	return np, nerr
}