return &dsync.LockArgs{}
	}, func() *dsync.LockResp {
		return &dsync.LockResp{}
	})
}

// registerLockRESTHandlers - register lock rest router.
func registerLockRESTHandlers(gm *grid.Manager) {
	lockServer := &lockRESTServer{
		ll: newLocker(),
	}

labels.notification_search_top=Search Top Page
labels.storage_endpoint=Endpoint
labels.storage_access_key=Access Key
labels.storage_secret_key=Secret Key
labels.storage_bucket=Bucket
labels.send_testmail=Send Test Mail
labels.backup_configuration=Backup
labels.backup_name=Name
labels.backup_bulk_file=Bulk File
labels.backup_button_upload=Upload

		_, err := io.ReadFull(respBody, tmp[:])
		if err != nil {
			return err
		}
		// Check if we have a response ready or a filler byte.
		switch tmp[0] {
		case 0:
			// 0 is unbuffered, copy the rest.
			_, err := io.CopyBuffer(w, respBody, buf)
			if err == io.EOF {
				return nil
			}
			return err
		case 1:
			errorText, err := io.ReadAll(respBody)
			if err != nil {
				return err

這與 **FastAPI** 所能提供的性能水平相同。

你可以同時利用並行性和平行性，進一步提升效能，這比大多數已測試的 NodeJS 框架都更快，並且與 Go 語言相當，而 Go 是一種更接近 C 的編譯語言（<a href="https://www.techempower.com/benchmarks/#section=data-r17&hw=ph&test=query&l=zijmkf-1" class="external-link" target="_blank">感謝 Starlette</a>）。

### 並行比平行更好嗎？

不是的！這不是故事的本意。

並行與平行不同。並行在某些 **特定** 的需要大量等待的情境下表現更好。正因如此，並行在 Web 應用程式開發中通常比平行更有優勢。但並不是所有情境都如此。

因此，為了平衡報導，想像下面這個短故事

### Other notable changes

Harshavardhana <******@****.***> 1723451895 -0700

Klaus Post <******@****.***> 1700528975 -0800

    assertFinallyFailsWithException(closingFuture);
    waitUntilClosed(closingFuture);
    assertStillOpen(closeable1);
    assertClosed(closeable2, closeable3);
  }

  // We don't need to test the happy case for SuccessfulCombiner.call(Async) because it's the same
  // as Combiner.

  public void testWhenAllSucceed_call_failedInput() throws Exception {
    assertFinallyFailsWithException(

      }

      @Override
      public void forEach(Consumer<? super T> action) {
        checkNotNull(action);
        unfiltered.forEach(
            (@ParametricNullness T a) -> {
              if (retainIfTrue.test(a)) {
                action.accept(a);
              }
            });
      }

      @Override
      public Spliterator<T> spliterator() {

	// setup becoming a reality we must try to shard the work properly such as
	// pick 10 nodes that precisely can send those 100 requests the first node
	// in the 10 node shard would coordinate between other 9 shards to get the
	// rest of the `99*9` requests.
	//
	// This essentially splits the workload properly and also allows for network
	// utilization to be optimal, instead of blindly throttling the way we are