* Bởi vì các cấu trúc dữ liệu của Pydantic chỉ là các instances của class bạn định nghĩa; auto-completion, linting, mypy và trực giác của bạn nên làm việc riêng biệt với những dữ liệu mà bạn đã validate.
* Validate **các cấu trúc phức tạp**:
    * Sử dụng các models Pydantic phân tầng, `List` và `Dict` của Python `typing`,...

    * 没有新的模式定义 micro-language 需要学习。
    * 如果你知道 Python types，你就知道如何使用 Pydantic。
* 和你 **<abbr title="集成开发环境，和代码编辑器类似">IDE</abbr>/<abbr title="一个检查代码错误的程序">linter</abbr>/brain** 适配:
    * 因为 pydantic 数据结构仅仅是你定义的类的实例；自动补全，linting，mypy 以及你的直觉应该可以和你验证的数据一起正常工作。
* 验证**复杂结构**:
    * 使用分层的 Pydantic 模型, Python `typing`的 `List` 和 `Dict` 等等。
    * 验证器使我们能够简单清楚的将复杂的数据模式定义、检查并记录为 JSON Schema。
    * 你可以拥有深度**嵌套的 JSON** 对象并对它们进行验证和注释。
* **可扩展**:

      int nextPermitsToAcquire = max(1, random.nextInt(permits));
      permits -= nextPermitsToAcquire;
      rateLimiter.acquire(nextPermitsToAcquire);
    }
    rateLimiter.acquire(1); // to repay for any pending debt
    return NANOSECONDS.toMillis(stopwatch.instant - startTime);
  }

  private void assertEvents(String... events) {
    assertEquals(Arrays.toString(events), stopwatch.readEventsAndClear());
  }

      int nextPermitsToAcquire = max(1, random.nextInt(permits));
      permits -= nextPermitsToAcquire;
      rateLimiter.acquire(nextPermitsToAcquire);
    }
    rateLimiter.acquire(1); // to repay for any pending debt
    return NANOSECONDS.toMillis(stopwatch.instant - startTime);
  }

  private void assertEvents(String... events) {
    assertEquals(Arrays.toString(events), stopwatch.readEventsAndClear());
  }

 *       (However, cancellation can prevent an <i>unstarted</i> task from running.) Therefore, the
 *       next task will wait for any running callable (or pending {@code Future} returned by an
 *       {@code AsyncCallable}) to complete, without interrupting it (and without calling {@code
 *       cancel} on the {@code Future}). So beware: <i>Even if you cancel every preceding {@code

    TF_Status status;
    // Let this custom device choose the device to pin this op on if it
    // implements the pinning function.
    if (device_.shall_pin_to_this_device != nullptr) {
      return device_.shall_pin_to_this_device(tensorflow::wrap(op), &status);
    }
    return errors::Unimplemented("No custom device pinning implementation.");
  }

 private:
  TFE_Context* context_;
  TFE_CustomDevice device_;
  void* info_;

     * `CollectionFuture.values`). This might be a no-op: If this future completed during
     * handleAllCompleted(), they will already have been nulled out. But in the case of
     * whenAll*().call*(), this future may be pending until the callback runs -- or even longer in
     * the case of callAsync(), which waits for the callback's returned future to complete.
     */
    releaseResources(ALL_INPUT_FUTURES_PROCESSED);
  }

  /**

  //
  // The size of this field is limited to 128. This is large enough for
  // many clusters. Larger clusters may need more attempts to find a node
  // that suits all pending resources. This may get increased in the
  // future, but not reduced.
  //
  // +listType=set
  // +optional
  repeated string potentialNodes = 2;
}

	// in Finish()

	quitFlag := false
	for !quitFlag {
		select {
		case data := <-writer.errCh:
			quitFlag = true
			// Flush collected records before sending error message
			if !writer.flushRecords() {
				break
			}
			writer.write(data)

		case payload, ok := <-writer.payloadCh:
			if !ok {
				// payloadCh is closed by caller to

	for _, dobj := range deletedObjects {
		if dobj.ObjectName == "" {
			continue
		}

		if replicateDeletes && (dobj.DeleteMarkerReplicationStatus() == replication.Pending || dobj.VersionPurgeStatus() == Pending) {
			// copy so we can re-add null ID.
			dobj := dobj
			if isDirObject(dobj.ObjectName) && dobj.VersionID == "" {
				dobj.VersionID = nullVersionID
			}
			dv := DeletedObjectReplicationInfo{