int listenerCount = 20;
    CountDownLatch listenerLatch = new CountDownLatch(listenerCount);

    // Test that listeners added both before and after the value is available
    // get called correctly.
    for (int i = 0; i < 20; i++) {

      // Right in the middle start up a thread to close the latch.
      if (i == 10) {
        new Thread(() -> latch.countDown()).start();
      }

    }

    @Override
    protected List<V> delegate() {
      return emptyList();
    }
  }

  @Override
  Iterator<Entry<K, V>> entryIterator() {
    throw new AssertionError("should never be called");
  }

  @Override
  Collection<Entry<K, V>> createEntries() {
    return new Entries();
  }

  @WeakOuter
  class Entries extends ForwardingCollection<Entry<K, V>> {
    @Override

 *   <dt>{@link BiMap}
 *   <dd>An extension of {@link java.util.Map} that guarantees the uniqueness of its values as well
 *       as that of its keys. This is sometimes called an "invertible map," since the restriction on
 *       values enables it to support an {@linkplain BiMap#inverse inverse view} -- which is another
 *       instance of {@code BiMap}.
 *   <dt>{@link Table}

In an advanced scenario where you know you need the dependency to be called at every step (possibly multiple times) in the same request instead of using the "cached" value, you can set the parameter `use_cache=False` when using `Depends`:

//// tab | Python 3.8+

```Python hl_lines="1"

 *   <dt>{@link BiMap}
 *   <dd>An extension of {@link java.util.Map} that guarantees the uniqueness of its values as well
 *       as that of its keys. This is sometimes called an "invertible map," since the restriction on
 *       values enables it to support an {@linkplain BiMap#inverse inverse view} -- which is another
 *       instance of {@code BiMap}.
 *   <dt>{@link Table}

        }
        tasks.named("publishLocalPublicationToLocalRepository") {
            dependsOn("signGradleDistributionPublication")
        }
    }
}

/**
 * Tasks that are called by the (currently separate) promotion build running on CI.
 */
tasks.register("promotionBuild") {
    description = "Build production distros, smoke test them and publish"
    group = "publishing"

```Python
if not (credentials.username == "stanleyjobson") or not (credentials.password == "swordfish"):
    # Return some error
    ...
```

But by using the `secrets.compare_digest()` it will be secure against a type of attacks called "timing attacks".

### Timing Attacks

But what's a "timing attack"?

Let's imagine some attackers are trying to guess the username and password.

	m.mu.Lock()
	defer m.mu.Unlock()
	for bucket, b := range m.buckets {
		b.deleteAll()
		delete(m.buckets, bucket)
	}
}

// checkMetacacheState should be used if data is not updating.
// Should only be called if a failure occurred.
func (o listPathOptions) checkMetacacheState(ctx context.Context, rpc *peerRESTClient) error {
	// We operate on a copy...
	o.Create = false
	c, err := rpc.GetMetacacheListing(ctx, o)

		// in the beginning of erasure set healing
		if err := bgSeq.healBucket(objAPI, bucket, true); err != nil {
			// Set this such that when we return this function
			// we let the caller retry this disk again for the
			// buckets that failed healing.
			retErr = err
			healingLogIf(ctx, err)
			continue
		}

		var (
			vc   *versioning.Versioning
			lc   *lifecycle.Lifecycle

  - New objects inherit the retention settings of the bucket object lock configuration automatically
  - Retention headers can be optionally set while uploading objects
  - Once objects are uploaded PutObjectRetention API can be called to change retention settings
- *MINIO_NTP_SERVER* environment variable can be set to remote NTP server endpoint if system time is not desired for setting retention dates.

## Explore Further