n++
					}
					atomic.AddInt64(&ops, int64(n))
					atomic.AddInt64(&lat, latency)
				})
				spent := time.Since(t)
				if spent > 0 && n > 0 {
					// Since we are benchmarking n parallel servers we need to multiply by n.
					// This will give an estimate of the total ops/s.
					latency := float64(atomic.LoadInt64(&lat)) / float64(time.Millisecond)

Nevertheless, although we are not using the default integrated functionality, we are still using a Pydantic model to manually generate the JSON Schema for the data that we want to receive in YAML.

Then we use the request directly, and extract the body as `bytes`. This means that FastAPI won't even try to parse the request payload as JSON.

	}

	cache := store.lock()
	defer store.unlock()

	// We should only update the in-memory cache if there were no changes
	// to the in-memory cache since the disk loading began. If there
	// were changes to the in-memory cache we should wait for the next
	// cycle until we can safely update the in-memory cache.
	//
	// An in-memory cache must be replaced only if we know for sure that the

  protected AbstractIterator() {}

  private enum State {
    /** We have computed the next element and haven't returned it yet. */
    READY,

    /** We haven't yet computed or have already returned the element. */
    NOT_READY,

    /** We have reached the end of the data and are finished. */
    DONE,

    /** We've suffered an exception and are kaput. */
    FAILED,
  }

  }

  /*
   * TODO(b/242884182): Figure out why this helps produce the same class file when we compile most
   * of common.collect a second time with the results of the first compilation on the classpath. Or
   * just back this out once we stop doing that (which we'll do after our internal GWT setup
   * changes).
   */
  @Override
  public ImmutableMap<Object, Collection<Object>> asMap() {

    return requireNonNull(DEST_TL.get());
  }

  /**
   * A thread-local destination buffer to keep us from creating new buffers. The starting size is
   * 1024 characters. If we grow past this we don't put it back in the threadlocal, we just keep
   * going and grow as needed.
   */
  private static final ThreadLocal<char[]> DEST_TL =
      new ThreadLocal<char[]>() {
        @Override
        protected char[] initialValue() {

    if (mapEntryAboveToTruncate != null) {
      // we know ( ]
      RangeMapEntry<K, V> rangeMapEntry = mapEntryAboveToTruncate.getValue();
      if (rangeMapEntry.getUpperBound().compareTo(rangeToRemove.upperBound) > 0) {
        // we know ( ] ), and since we dealt with truncating below already,
        // we know [ ( ] )
        putRangeMapEntry(
            rangeToRemove.upperBound,

		return selected, true
	}

	// If we would never be able to reach read quorum.
	if objsValid < r.objQuorum {
		return nil, false
	}

	// If all objects agree.
	if selected != nil && objsAgree == objsValid {
		return selected, true
	}

	// If cached is nil we shall skip the entry.
	if selected.cached == nil {
		return nil, false
	}

	// Merge if we have disagreement.

//   "format": "XXXXX",
//   "XXXXX": {
//
//   }
// }
// Here "XXXXX" depends on the backend, currently we have "fs" and "xl" implementations.
// formatMetaV1 should be inherited by backend format structs. Please look at format-fs.go
// and format-xl.go for details.

// Ideally we will never have a situation where we will have to change the
// fields of this struct and deal with related migration.
type formatMetaV1 struct {

    for (LoadingCache<Object, Object> cache : caches()) {
      cache.getUnchecked(1);
      cache.getUnchecked(2);

      Set<Object> keys = cache.asMap().keySet();
      // We don't know whether these are still in the cache, so we can't assert on the return
      // values of these removes, but the cache should be empty after the removes, regardless.
      keys.remove(1);
      keys.remove(2);