*
 * <p>Test cases that should be handled similarly in any graph implementation are included in this
 * class. For example, testing that {@code nodes()} method returns the set of the nodes in the
 * graph. The following test cases are left for the subclasses to handle:
 *
 * <ul>
 *   <li>Test cases related to whether the graph is directed or undirected.

    return delegate().tailMap(fromKey);
  }

  /**
   * A sensible implementation of {@link SortedMap#keySet} in terms of the methods of {@code
   * ForwardingSortedMap}. In many cases, you may wish to override {@link
   * ForwardingSortedMap#keySet} to forward to this implementation or a subclass thereof.
   *
   * @since 15.0
   */
  protected class StandardKeySet extends Maps.SortedKeySet<K, V> {

        new AbstractFuture<Object>() {
          @Override
          public String pendingToString() {
            return "cause=[Because this test isn't done]";
          }
        };
    assertThat(testFuture.toString())
        .matches(
            "[^\\[]+\\[status=PENDING, info=\\[cause=\\[Because this test isn't done\\]\\]\\]");
    TimeoutException e = assertThrows(TimeoutException.class, () -> testFuture.get(1, NANOSECONDS));

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

the vast majority of deployments in any negative way.

> Will an upgrade of an existing MinIO cluster impact the SLA of the cluster or will it even cause downtime?

No, an upgrade should not cause any downtime. However, on the first startup -
since MinIO will attempt to migrate any existing IAM data - the boot process may
take slightly longer, but may not be visibly noticeable. Once the migration has

    switch (mode) {
      case UNNECESSARY:
        checkRoundingUnnecessary(x == floorPow);
      // fall through
      case FLOOR:
      case DOWN:
        return logFloor;
      case CEILING:
      case UP:
        return logFloor + lessThanBranchFree(floorPow, x);
      case HALF_DOWN:
      case HALF_UP:
      case HALF_EVEN:

// ETag.
//
// In general, a caller has to distinguish the following cases:
//   - The object is a multipart object. In this case,
//     Format returns the ETag unmodified.
//   - The object is a SSE-KMS or SSE-C encrypted single-
//     part object. In this case, Format returns the last
//     16 bytes of the encrypted ETag which will be a random
//     value.

}

func (d *DummyDataGen) Seek(offset int64, whence int) (int64, error) {
	switch whence {
	case io.SeekStart:
		if offset < 0 {
			return 0, errors.New("Invalid offset")
		}
		d.idx = offset
	case io.SeekCurrent:
		if d.idx+offset < 0 {
			return 0, errors.New("Invalid offset")
		}
		d.idx += offset
	case io.SeekEnd:
		if d.length+offset < 0 {
			return 0, errors.New("Invalid offset")
		}

     * @since 31.0
     */
    public ImmutableTable<R, C, V> buildOrThrow() {
      int size = cells.size();
      switch (size) {
        case 0:
          return of();
        case 1:
          return new SingletonImmutableTable<>(getOnlyElement(cells));
        default:
          return RegularImmutableTable.forCells(cells, rowComparator, columnComparator);
      }
    }

///

## Duplicate headers { #duplicate-headers }

It is possible to receive duplicate headers. That means, the same header with multiple values.

You can define those cases using a list in the type declaration.

You will receive all the values from the duplicate header as a Python `list`.

For example, to declare a header of `X-Token` that can appear more than once, you can write: