Map<String, String> childUrlRuleMap = newHashMap();
        childUrlRuleMap.put("//A", "href");
        childUrlRuleMap.put("//AREA", "href");
        childUrlRuleMap.put("//FRAME", "src");
        childUrlRuleMap.put("//IFRAME", "src");
        childUrlRuleMap.put("//IMG", "src");
        childUrlRuleMap.put("//LINK", "href");
        childUrlRuleMap.put("//SCRIPT", "src");

      assertThat(event.responseBody).isEqualTo(body)
    }
    assertThat(event.t.javaClass).isEqualTo(cls)
    assertThat(event.t.message).isEqualTo(message)
  }

  /** Expose this recorder as a frame callback and shim in "ping" events.  */
  fun asFrameCallback() =
    object : WebSocketReader.FrameCallback {
      override fun onReadMessage(text: String) {
        events.add(Message(string = text))
      }

    assertThat(firstFrame(logs, "HEADERS")!!, "header logged")
      .contains("HEADERS       END_HEADERS")
    // While MockWebServer waits to read the client's HEADERS frame before sending the response, it
    // doesn't wait to read the client's DATA frame and may send a DATA frame before the client
    // does. So we can't assume the client's empty DATA will be logged first.

Houveram mudanças no próprio Pydantic para que isso fosse possível.

As capturas de tela anteriores foram capturas no <a href="https://code.visualstudio.com" class="external-link" target="_blank">Visual Studio Code</a>.

    } finally {
      service.shutdown();
    }
    assertThat(holder.count).isEqualTo(ITERATION_COUNT);
    for (int length : completeLengthChecks) {
      // Verify that at max depth, less than one stack frame per submitted task was consumed
      assertThat(length - baseStackDepth).isLessThan(DIRECT_EXECUTIONS_PER_THREAD / 2);
    }
  }

  @SuppressWarnings("ObjectToString") // Intended behavior

    peer.acceptFrame() // ACK
    peer.sendFrame().ping(false, 2, 0)
    peer.acceptFrame()
    peer.play()

    // Play it back.
    val connection = connect(peer)

    // fake a settings frame with clear flag set.
    val settings2 = Settings()
    settings2[Settings.MAX_CONCURRENT_STREAMS] = 60000
    connection.readerRunnable.applyAndAckSettings(true, settings2)
    connection.withLock {

	op := operands[next]
	if len(op) < 2 || op[0].ScanToken != '$' {
		p.errorf("TEXT %s: frame size must be an immediate constant", name)
		return
	}
	op = op[1:]
	negative := false
	if op[0].ScanToken == '-' {
		negative = true
		op = op[1:]
	}
	if len(op) == 0 || op[0].ScanToken != scanner.Int {
		p.errorf("TEXT %s: frame size must be an immediate constant", name)
		return
	}

    * Utilise les modèles hiérarchique de Pydantic, le `typage` Python pour les `Lists`, `Dict`, etc.
    * Et les validateurs permettent aux schémas de données complexes d'être clairement et facilement définis, validés et documentés sous forme d'un schéma JSON.
    * Vous pouvez avoir des objets **JSON fortement imbriqués** tout en ayant, pour chacun, de la validation et des annotations.
* **Renouvelable**:

  }

  /** The maximum size of bytes that may be sent in a single call to [data]. */
  fun maxDataLength(): Int = maxFrameSize

  /**
   * `source.length` may be longer than the max length of the variant's data frame. Implementations
   * must send multiple frames as necessary.
   *
   * @param source the buffer to draw bytes from. May be null if byteCount is 0.

labels.backup_button_upload=Hochladen
labels.process_time_is_exceeded=Das Zeitlimit für die Suche wurde überschritten. Das angezeigte Suchergebnis kann daher unvollständig sein.
labels.user_given_name=Vorname
labels.givenName=Vorname
labels.user_surname=Nachname
labels.surame=Nachname
labels.user_mail=E-Mail
labels.mail=E-Mail
labels.user_employeeNumber=Personalnummer
labels.employeeNumber=Personalnummer