}

    @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}

	return &Cache[T]{
		ttl:      ttl,
		updateFn: update,
		opts:     opts,
	}
}

// InitOnce initializes the cache with a TTL and an update function. It is
// guaranteed to be called only once.
func (t *Cache[T]) InitOnce(ttl time.Duration, opts Opts, update func(ctx context.Context) (T, error)) {
	t.Once.Do(func() {
		t.ttl = ttl
		t.updateFn = update
		t.opts = opts
	})
}

```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)

  - 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

              // we reached EOF
              return new String(buffer, 0, bufIndex);
            }
            // otherwise we got the size wrong.  This can happen if the size changes between when
            // we called sizeIfKnown and when we started reading the file (or I guess if
            // maxCharsPerByte is wrong)
            // Fallback to an incremental approach
            StringBuilder builder = new StringBuilder(bufIndex + 32);

Calls are executed in one of two ways:

 * **Synchronous:** your thread blocks until the response is readable.
 * **Asynchronous:** you enqueue the request on any thread, and get [called back](https://square.github.io/okhttp/4.x/okhttp/okhttp3/-callback/) on another thread when the response is readable.