Questo con le annotazioni per i tipi standard di Python.

Non c'è bisogno di imparare una nuova sintassi, metodi o classi specifici a una libreria, ecc.

È normalissimo **Python 3.6+**.

Per esempio, per un `int`:

```Python
item_id: int
```

o per un modello `Item` più complesso:

```Python
item: Item
```

 * }</pre>
 *
 * <p>As another example, imagine that we produce a stream of data, and we want to cap it at 5kb per
 * second. This could be accomplished by requiring a permit per byte, and specifying a rate of 5000
 * permits per second:
 *
 * <pre>{@code
 * final RateLimiter rateLimiter = RateLimiter.create(5000.0); // rate = 5000 permits per second
 * void submitPacket(byte[] packet) {
 *   rateLimiter.acquire(packet.length);

    + row.withPanels([
      panels.timeSeries.connections('Connections', queries.connections, 'Connections opened and closed per instance'),
      panels.timeSeries.bytesRate('Bytes Transmitted', queries.bytes, 'Bytes sent and received per instance'),
      panels.timeSeries.dns('DNS Request', queries.dns, 'DNS queries received per instance'),
    ]),
    row.new('Operations')
    + row.withPanels([
      panels.timeSeries.base(

 * }</pre>
 *
 * <p>As another example, imagine that we produce a stream of data, and we want to cap it at 5kb per
 * second. This could be accomplished by requiring a permit per byte, and specifying a rate of 5000
 * permits per second:
 *
 * <pre>{@code
 * final RateLimiter rateLimiter = RateLimiter.create(5000.0); // rate = 5000 permits per second
 * void submitPacket(byte[] packet) {
 *   rateLimiter.acquire(packet.length);

  }

  // Takes a description of a single operation being executed on the
  // ParallelDevice, and in turn runs one operation per component device with
  // its corresponding inputs from the input ParallelTensors. Wraps the
  // resulting per-device and per-output TFE_TensorHandles into one
  // ParallelTensor per output of the original operation.
  //
  // Attributes are forwarded to executed operations unmodified.
  //

| `minio_node_drive_reads_per_sec`     | Reads per second on a drive.                             |
| `minio_node_drive_reads_kb_per_sec`  | Kilobytes read per second on a drive.                    |
| `minio_node_drive_reads_await`       | Average time for read requests to be served on a drive.  |
| `minio_node_drive_writes_per_sec`    | Writes per second on a drive.                            |

    row.new('Push Information')
    + row.withPanels([
      panels.timeSeries.xdsPushes(
        'XDS Pushes', queries.xdsPushes, |||
          Rate of XDS push operations, by type. This is incremented on a per-proxy basis.
        |||
      ),
      panels.timeSeries.base(
        'Events', queries.pilotEvents, |||
          Size of each xDS push.
        |||
      ),
      panels.timeSeries.base(

	statLock    sync.RWMutex
	targetStats map[TargetID]targetStat
}

type targetStat struct {
	// The number of concurrent async Send calls per targets
	currentSendCalls int64
	// The number of total events per target
	totalEvents int64
	// The number of failed events per target
	failedEvents int64
}

func (list *TargetList) getStatsByTargetID(id TargetID) (stat targetStat) {
	list.statLock.RLock()

      <phase>package</phase>
      <implementation>org.apache.maven.plugin.jar.JarMojo</implementation>
      <language>java</language>
      <instantiationStrategy>per-lookup</instantiationStrategy>
      <executionStrategy>once-per-session</executionStrategy>
      <deprecated>deprecated-mojo</deprecated>
      <since>2.2</since>
      <executePhase>generate-sources</executePhase>
      <executeGoal>some-goal</executeGoal>

	configLk.Lock()
	defer configLk.Unlock()
	c.MaxTimeout = getMaxTimeout(new.MaxTimeout)
	return nil
}

// GetMaxTimeout - returns the per call drive operation timeout
func (c *Config) GetMaxTimeout() time.Duration {
	return c.GetOPTimeout()
}

// GetOPTimeout - returns the per call drive operation timeout
func (c *Config) GetOPTimeout() time.Duration {
	configLk.RLock()
	defer configLk.RUnlock()