}
  }

  @AndroidIncompatible // slow
  @GwtIncompatible // java.math.BigInteger
  public void testMean() {
    // Odd-sized ranges have an obvious mean
    assertMean(2, 1, 3);

    assertMean(-2, -3, -1);
    assertMean(0, -1, 1);
    assertMean(1, -1, 3);
    assertMean((1 << 30) - 1, -1, Integer.MAX_VALUE);

    // Even-sized ranges should prefer the lower mean
    assertMean(2, 1, 4);

     * with each iteration, so this algorithm takes O(log(digits)) iterations.
     *
     * We start out with a double-precision approximation, which may be higher or lower than the
     * true value. Therefore, we perform at least one Newton iteration to get a guess that's
     * definitely >= floor(sqrt(x)), and then continue the iteration until we reach a fixed point.
     */

Mit **FastAPI** bekommen Sie alles von **Starlette** (da FastAPI nur Starlette auf Steroiden ist):

* Schwer beeindruckende Performanz. Es ist <a href="https://github.com/encode/starlette#performance" class="external-link" target="_blank">eines der schnellsten Python-Frameworks, auf Augenhöhe mit **NodeJS** und **Go**</a>.

		nsUnlocker = func() { lock.RUnlock(lkctx) }
		unlockOnDefer = true
	}

	checkPrecondFn := opts.CheckPrecondFn
	opts.CheckPrecondFn = nil // do not need to apply pre-conditions at lower layer.
	opts.NoLock = true        // no locks needed at lower levels for getObjectInfo()
	objInfo, zIdx, err := z.getLatestObjectInfoWithIdx(ctx, bucket, object, opts)
	if err != nil {
		if objInfo.DeleteMarker {
			if opts.VersionID == "" {

In discussions and PRs, in many cases, people bring their frustration and show it without filter, in many cases exaggerating, complaining, being entitled, etc. That's really not nice, and when it happens, it lowers our priority to solve their problems. But still, try to breath, and be gentle with your answers.

// Checksum returns the content checksum if set.
func (r *Reader) Checksum() *Checksum {
	if !r.contentHash.Type.IsSet() || !r.contentHash.Valid() {
		return nil
	}
	return &r.contentHash
}

var _ io.Closer = (*Reader)(nil) // compiler check

// Close and release resources.

    }
  }

  @AndroidIncompatible // slow
  @GwtIncompatible // java.math.BigInteger
  public void testMean() {
    // Odd-sized ranges have an obvious mean
    assertMean(2, 1, 3);

    assertMean(-2, -3, -1);
    assertMean(0, -1, 1);
    assertMean(1, -1, 3);
    assertMean((1 << 30) - 1, -1, Integer.MAX_VALUE);

    // Even-sized ranges should prefer the lower mean
    assertMean(2, 1, 4);

#### General guidelines and philosophy for contribution

*   Include unit tests when you contribute new features, as they help to a)
    prove that your code works correctly, and b) guard against future breaking
    changes to lower the maintenance cost.
*   Bug fixes also generally require unit tests, because the presence of bugs
    usually indicates insufficient test coverage.
*   Keep API compatibility in mind when you change code in core TensorFlow,

 * <strong>not</strong> equal to {@code key2}, it is <strong>not</strong> guaranteed that {@code
 * striped.get(key1) != striped.get(key2)}; the elements might nevertheless be mapped to the same
 * lock. The lower the number of stripes, the higher the probability of this happening.
 *
 * <p>There are three flavors of this class: {@code Striped<Lock>}, {@code Striped<Semaphore>}, and

    rangeMap.put(Range.closedOpen(18, 19), 3);

    rangeMap.putCoalescing(Range.closedOpen(-5, -4), 0); // disconnected
    rangeMap.putCoalescing(Range.closedOpen(-6, -5), 0); // lower than minimum

    rangeMap.putCoalescing(Range.closedOpen(2, 4), 1); // between
    rangeMap.putCoalescing(Range.closedOpen(9, 14), 0); // different value
    rangeMap.putCoalescing(Range.closedOpen(17, 20), 3); // enclosing