return info, toStorageErr(errors.New(info.Error))
			}
			return info, nil
		},
	)

	return client.diskInfoCache.GetWithCtx(ctx)
}

// MakeVolBulk - create multiple volumes in a bulk operation.
func (client *storageRESTClient) MakeVolBulk(ctx context.Context, volumes ...string) (err error) {
	return errInvalidArgument
}

// MakeVol - create a volume on a remote disk.

    BloomFilter<Object> bf = BloomFilter.create(HashTestUtils.BAD_FUNNEL, 10, 0.03);
    double fpp = bf.expectedFpp();
    assertThat(fpp).isEqualTo(0.0);
    // usually completed in less than 200 iterations
    while (fpp != 1.0) {
      boolean changed = bf.put(new Object());
      double newFpp = bf.expectedFpp();
      // if changed, the new fpp is strictly higher, otherwise it is the same

    HashTestUtils.assertInvariants(Hashing.fingerprint2011());
    assertEquals("Hashing.fingerprint2011()", Hashing.fingerprint2011().toString());
  }

  @AndroidIncompatible // slow TODO(cpovirk): Maybe just reduce iterations under Android.
  public void testGoodFastHash() {
    for (int i = 1; i < 200; i += 17) {
      HashFunction hasher = Hashing.goodFastHash(i);
      assertTrue(hasher.bits() >= i);

  }

  /**
   * An object that joins map entries in the same manner as {@code Joiner} joins iterables and
   * arrays. Like {@code Joiner}, it is thread-safe and immutable.
   *
   * <p>In addition to operating on {@code Map} instances, {@code MapJoiner} can operate on {@code
   * Multimap} entries in two distinct modes:
   *
   * <ul>

          "editorMode": "code",
          "exemplar": true,
          "expr": "sum by (bucket,range,operation) (minio_bucket_replication_latency_ms{job=~\"$scrape_jobs\"})",
          "format": "time_series",
          "instant": false,
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "{{bucket,range,operation}}",
          "refId": "A",
          "step": 300
        }
      ],

        CacheBuilder.newBuilder().weakValues().build(countingLoader);
    ConcurrentMap<Object, Object> map = cache.asMap();

    int iterations = 10;
    WeakReference<Object> ref = new WeakReference<>(null);
    int expectedComputations = 0;
    for (int i = 0; i < iterations; i++) {
      // The entry should get garbage collected and recomputed.
      Object oldValue = ref.get();
      if (oldValue == null) {

Podemos **leer** un único héroe:

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[75:80] hl[77] *}

### Actualizar un Hero con `HeroUpdate`

Podemos **actualizar un héroe**. Para esto usamos una operación HTTP `PATCH`.

   * exhausted: its {@code hasNext()} method will return {@code false}.
   *
   * @return {@code true} if {@code collection} was modified as a result of this operation
   */
  @CanIgnoreReturnValue
  public static <T extends @Nullable Object> boolean addAll(
      Collection<T> addTo, Iterator<? extends T> iterator) {
    checkNotNull(addTo);
    checkNotNull(iterator);

			return err
		}
	}
}

// merge will merge other into m.
// If the same entries exists in both and metadata matches only one is added,
// otherwise the entry from m will be placed first.
// Operation time is expected to be O(n+m).
func (m *metaCacheEntriesSorted) merge(other metaCacheEntriesSorted, limit int) {
	merged := make(metaCacheEntries, 0, m.len()+other.len())
	a := m.entries()
	b := other.entries()

```JSON
{"item_id": 5, "q": "somequery"}
```

Damit haben Sie bereits eine API erstellt, welche:

* HTTP-Anfragen auf den _Pfaden_ `/` und `/items/{item_id}` entgegennimmt.
* Beide _Pfade_ erhalten `GET` Operationen (auch bekannt als HTTP _Methoden_).
* Der _Pfad_ `/items/{item_id}` hat einen _Pfadparameter_ `item_id`, der ein `int` sein sollte.
* Der _Pfad_ `/items/{item_id}` hat einen optionalen `str` _Query Parameter_ `q`.