# Modelos de Parâmetros do Cabeçalho

Se você possui um grupo de **parâmetros de cabeçalho** relacionados, você pode criar um **modelo do Pydantic** para declará-los.

Isso vai lhe permitir **reusar o modelo** em **múltiplos lugares** e também declarar validações e metadadados para todos os parâmetros de uma vez. 😎

/// note | Nota

Isso é possível desde a versão `0.115.0` do FastAPI. 🤓

///

## Parâmetros do Cabeçalho com um Modelo Pydantic

   * Creates a table with the specified data.
   *
   * @param data the table data, repeating the sequence row key, column key, value once per mapping
   * @throws IllegalArgumentException if the size of {@code data} isn't a multiple of 3
   * @throws ClassCastException if a data element has the wrong type
   */
  protected abstract Table<String, Integer, C> create(@Nullable Object... data);

  protected void assertSize(int expectedSize) {

 * string {@code "Foo<Bar>"}.
 *
 * <p>A {@code CharEscaper} instance is required to be stateless, and safe when used concurrently by
 * multiple threads.
 *
 * <p>Popular escapers are defined as constants in classes like {@link
 * com.google.common.html.HtmlEscapers} and {@link com.google.common.xml.XmlEscapers}. To create

  private val tasksExecutor = Executors.newCachedThreadPool(threadFactory("TaskFaker"))

  /**
   * True if this task faker has ever had multiple tasks scheduled to run concurrently. Guarded by
   * [TaskRunner.lock].
   */
  var isParallel = false

  /** Number of calls to [TaskRunner.Backend.execute]. Guarded by [TaskRunner.lock]. */
  var executeCallCount = 0

```bash
go install github.com/minio/minio/docs/debugging/xl-meta@latest
```

### Using xl-meta

				"arn:minio:replication::id:bucket": newReplicateTargetDecision("arn:minio:replication::id:bucket", true, false),
			},
		},
	},
	{ // 3.
		name:   "replicate decision for multiple targets",
		dsc:    "arn:minio:replication::id:bucket=true;false;arn:minio:replication::id:bucket;id,arn:minio:replication::id2:bucket=false;true;arn:minio:replication::id2:bucket;id2",
		expErr: nil,
		expDsc: ReplicateDecision{

///

With that you can connect the WebSocket and then send and receive messages:

<img src="/img/tutorial/websockets/image05.png">

## Handling disconnections and multiple clients

When a WebSocket connection is closed, the `await websocket.receive_text()` will raise a `WebSocketDisconnect` exception, which you can then catch and handle like in this example.

//// tab | Python 3.9+

    }

  /**
   * The maximum number of requests for each host to execute concurrently. This limits requests by
   * the URL's host name. Note that concurrent requests to a single IP address may still exceed this
   * limit: multiple hostnames may share an IP address or be routed through the same HTTP proxy.
   *
   * If more than [maxRequestsPerHost] requests are in flight when this is invoked, those requests
   * will remain in flight.
   *

    }
  }

  private fun ensureAllTaskQueuesIdle() {
    val entryTime = System.nanoTime()

    for (queue in TaskRunner.INSTANCE.activeQueues()) {
      // We wait at most 1 second, so we don't ever turn multiple lost threads into
      // a test timeout failure.
      val waitTime = (entryTime + 1_000_000_000L - System.nanoTime())
      if (!queue.idleLatch().await(waitTime, TimeUnit.NANOSECONDS)) {

     */
    long deadline = System.nanoTime() + unit.toNanos(timeout);
    int added = 0;
    while (added < numElements) {
      // we could rely solely on #poll, but #drainTo might be more efficient when there are multiple
      // elements already available (e.g. LinkedBlockingQueue#drainTo locks only once)
      added += q.drainTo(buffer, numElements - added);