// The above implementation would incorrectly consider
	// such an ETag (with a nonce value containing a '-')
	// as non-encrypted.

	return len(e) >= 32 // We consider all ETags longer than 32 bytes as encrypted
}

// IsMultipart reports whether the ETag belongs to an
// object that has been uploaded using the S3 multipart
// API.
// An S3 multipart ETag has a -<part-number> suffix.

[@rosti](https://github.com/rosti)) Courtesy of SIG Cluster Lifecycle, SIG Release, and SIG Testing

        // We might need new connections to keep policies satisfied
        connectionPool.scheduleOpener(route.address)
      } else if (allocationLimit > oldLimit) {
        // We might no longer need some connections
        connectionPool.scheduleCloser()
      }
    }
  }

  override fun handshake(): Handshake? = handshake

    assert200Http2Response(execute(url), server.hostName)
    assertThat(client.connectionPool.connectionCount()).isEqualTo(1)
  }

  /** Test a previously coalesced connection that's no longer healthy.  */
  @Test
  fun staleCoalescedConnection() {
    server.enqueue(MockResponse())
    server.enqueue(MockResponse())
    val connection = AtomicReference<Connection?>()
    client =

    * Nếu bạn biết kiểu dữ liệu Python, bạn biết cách sử dụng Pydantic.
* Sử dụng tốt với **<abbr title="Môi trường phát triển tích hợp, tương tự như một trình soạn thảo code">IDE</abbr>/<abbr title="Một chương trình kiểm tra code lỗi">linter</abbr>/não của bạn**:

    * 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.

* **更简单**：
    * 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。

* Gutes Zusammenspiel mit Ihrer/Ihrem **<abbr title="Integrierten Entwicklungsumgebung, ähnlich zu (Quellcode-)Editor">IDE</abbr>/<abbr title="Ein Programm, was Fehler im Quellcode sucht">Linter</abbr>/Gehirn**:
    * Weil Pydantics Datenstrukturen einfach nur Instanzen ihrer definierten Klassen sind; Autovervollständigung, Linting, mypy und ihre Intuition sollten alle einwandfrei mit ihren validierten Daten funktionieren.

    * If you know Python types you know how to use Pydantic.
* Plays nicely with your **<abbr title="Integrated Development Environment, similar to a code editor">IDE</abbr>/<abbr title="A program that checks for code errors">linter</abbr>/brain**:
    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
* Validate **complex structures**:

* Kullandığın geliştirme araçları ile iyi çalışır **<abbr title="Integrated Development Environment, kod editörüne benzer">IDE</abbr>/<abbr title="Code errorlarınızı inceleyen program">linter</abbr>/brain**:
    * Pydantic'in veri yapıları aslında sadece senin tanımladığın classlar; Bu yüzden doğrulanmış dataların ile otomatik tamamlama, linting ve mypy'ı kullanarak sorunsuz bir şekilde çalışabilirsin

  }

  /**
   * Registers the given {@code closeable} to be closed when this {@code Closer} is {@linkplain
   * #close closed}.
   *
   * @return the given {@code closeable}
   */
  // close. this word no longer has any meaning to me.
  @CanIgnoreReturnValue
  @ParametricNullness
  public <C extends @Nullable Closeable> C register(@ParametricNullness C closeable) {
    if (closeable != null) {
      stack.addFirst(closeable);