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## Opiniões

"*[...] Estou usando **FastAPI** muito esses dias. [...] Estou na verdade planejando utilizar ele em todos os times de **serviços _Machine Learning_ na Microsoft**. Alguns deles estão sendo integrados no _core_ do produto **Windows** e alguns produtos **Office**.*"

  // shuffle sharding of requests into queues.  When enqueuing a request
  // at this priority level the request's flow identifier (a string
  // pair) is hashed and the hash value is used to shuffle the list
  // of queues and deal a hand of the size specified here.  The
  // request is put into one of the shortest queues in that hand.
  // `handSize` must be no larger than `queues`, and should be
  // significantly smaller (so that a few heavy flows do not

  // shuffle sharding of requests into queues.  When enqueuing a request
  // at this priority level the request's flow identifier (a string
  // pair) is hashed and the hash value is used to shuffle the list
  // of queues and deal a hand of the size specified here.  The
  // request is put into one of the shortest queues in that hand.
  // `handSize` must be no larger than `queues`, and should be
  // significantly smaller (so that a few heavy flows do not

  // shuffle sharding of requests into queues.  When enqueuing a request
  // at this priority level the request's flow identifier (a string
  // pair) is hashed and the hash value is used to shuffle the list
  // of queues and deal a hand of the size specified here.  The
  // request is put into one of the shortest queues in that hand.
  // `handSize` must be no larger than `queues`, and should be
  // significantly smaller (so that a few heavy flows do not

      // It's a weird formula, but tests prove it works.
      int adjust = size() - 1;
      for (int i = 0; i < axes.size(); i++) {
        adjust *= 31;
        adjust = ~~adjust;
        // in GWT, we have to deal with integer overflow carefully
      }
      int hash = 1;
      for (Set<E> axis : axes) {
        hash = 31 * hash + (size() / axis.size() * axis.hashCode());

        hash = ~~hash;
      }

- [Topology Manager](https://github.com/kubernetes/enhancements/issues/693), a new Kubelet component, aims to co-ordinate resource assignment decisions to provide optimized resource allocations.
- [IPv4/IPv6 dual-stack](https://kubernetes.io/docs/concepts/services-networking/dual-stack) enables the allocation of both IPv4 and IPv6 addresses to Pods and Services.

- Fix a bug with dual stack clusters using the beta feature MultiCIDRServiceAllocator can not create dual stack Services or Services with IPs on the secondary range. User that want to use this feature in 1.30 with dual stack clusters can workaround the issue by setting the feature gate DisableAllocatorDualWrite to true ([#127598](https://github.com/kubernetes/kubernetes/pull/127598),...

     * handling not just {@code Iterable<S>} instances, but also any {@code
     * Iterable<? extends S>}. However, the need for this comes up so rarely
     * that it doesn't justify making everyone else deal with the very ugly
     * wildcard.
     */
    return new LexicographicalOrdering<S>(this);
  }

  // Regular instance methods

  @Override

    int hashCode = 1;
    for (Object o : list) {
      hashCode = 31 * hashCode + (o == null ? 0 : o.hashCode());

      hashCode = ~~hashCode;
      // needed to deal with GWT integer overflow
    }
    return hashCode;
  }

  /** An implementation of {@link List#equals(Object)}. */
  static boolean equalsImpl(List<?> thisList, @CheckForNull Object other) {

    Object key = new Object();
    assertNotNull(cache.getUnchecked(key));

    CacheTesting.simulateValueReclamation(cache, key);

    // this blocks if computation can't deal with partially-collected values
    assertNotNull(cache.getUnchecked(key));
    assertEquals(1, cache.size());
    assertEquals(2, countingLoader.getCount());

    CacheTesting.simulateValueReclamation(cache, key);