# Using Dataclasses { #using-dataclasses }

FastAPI is built on top of **Pydantic**, and I have been showing you how to use Pydantic models to declare requests and responses.

But FastAPI also supports using <a href="https://docs.python.org/3/library/dataclasses.html" class="external-link" target="_blank">`dataclasses`</a> the same way:

{* ../../docs_src/dataclasses/tutorial001.py hl[1,7:12,19:20] *}

**FastAPI** bietet dieselben `starlette.status`-Codes auch via `fastapi.status` an, als Annehmlichkeit für Sie, den Entwickler. Sie kommen aber direkt von Starlette.

///

## Den Defaultwert ändern

   * of {@code map}.
   *
   * @throws IllegalArgumentException if an attempt to {@code put} any entry fails. Note that some
   *     map entries may have been added to the bimap before the exception was thrown.
   */
  @Override
  void putAll(Map<? extends K, ? extends V> map);

  // Views

  /**
   * {@inheritDoc}
   *

import jcifs.internal.smb1.ServerMessageBlock;
import jcifs.internal.util.SMBUtil;

/**
 * SMB1 Read AndX request message.
 *
 * This command is used to read data from a file that has been
 * previously opened with an Open command.
 */
public class SmbComReadAndX extends AndXServerMessageBlock {

    private long offset;
    private int fid;
    int openTimeout;
    int maxCount, minCount, remaining;

### Expiry or removal events

Prozess ausgeführt werden müssen (z. B. müssen Sie Speicher, Variablen, usw. nicht gemeinsam nutzen), könnte die Verwendung anderer größerer Tools wie z. B. <a href="https://docs.celeryq.dev" class="external-link" target="_blank">Celery</a> von Vorteil sein.

Sie erfordern in der Regel komplexere Konfigurationen und einen Nachrichten-/Job-Queue-Manager wie RabbitMQ oder Redis, ermöglichen Ihnen jedoch die Ausführung von Hintergrundtasks in mehreren Prozessen und insbesondere auf mehreren Servern....

      "FINE: Q10000 scheduled after 100 µs: task",
      "FINE: Q10000 starting              : task",
      "FINE: Q10000 finished run in   0 µs: task",
    )
  }

  /** Inspect how many runnables have been enqueued. If none then we're truly sequential. */
  @Test fun singleQueueIsSerial() {
    redQueue.execute("task one", 100.µs) {
      log += "one:run@${taskFaker.nanoTime} parallel=${taskFaker.isParallel}"
    }

// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package cmd

import (
	"io"
	"maps"
	"math"
	"net/http"
	"time"

 * <li>Child URL extraction and queueing</li>
 * <li>Integration with Fess configuration and permission systems</li>
 * <li>Client selection based on URL patterns</li>
 * </ul>
 *
 * @see CrawlerThread
 * @see org.codelibs.fess.crawler.client.CrawlerClient
 */
public class FessCrawlerThread extends CrawlerThread {

    /**
     * Default constructor.
     */
    public FessCrawlerThread() {
        super();

    client.processNextFrame() // Pong.

    // After 1000ms the client will attempt a ping 2, but we don't process it. That'll cause the
    // client to fail at 1500ms when it's time to send ping 3 because pong 2 hasn't been received.
    taskFaker.advanceUntil(ns(1000L))
    taskFaker.advanceUntil(ns(1500L))
    client.listener.assertFailure(
      SocketTimeoutException::class.java,