* remove()}. Otherwise, all optional operations are supported. Null row keys, columns keys, and
   * values are not supported.
   *
   * <p>Lookups by row key are often faster than lookups by column key, because the data is stored
   * in a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still
   * runs quickly, since the row key is provided. However, {@code column(columnKey).size()} takes

    return createInstance(factory, tentativeArgs).hashCode()
        == createInstance(factory, args).hashCode();
  }

  // distinctValues is a type-safe class-values mapping, but we don't have a type-safe data
  // structure to hold the mappings.
  @SuppressWarnings({"unchecked", "rawtypes"})
  private FreshValueGenerator newFreshValueGenerator() {
    FreshValueGenerator generator =
        new FreshValueGenerator() {

 *       Stats.of} factory method below. Primitive arrays, iterables and iterators of any kind of
 *       {@code Number}, and primitive varargs are supported.
 *   <li>Or, to avoid storing up all the data first, create a {@link StatsAccumulator} instance,
 *       feed values to it as you get them, then call {@link StatsAccumulator#snapshot}.
 * </ul>
 *

 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,

   * is used as a parameter to any of its methods.
   *
   * <p>The returned list is serializable.
   *
   * <p><b>Note:</b> when possible, you should represent your data as an {@link
   * ImmutableDoubleArray} instead, which has an {@link ImmutableDoubleArray#asList asList} view.
   *
   * @param backingArray the array to back the list
   * @return a list view of the array
   */

- Fixes a 1.29.0 regression that introduced a possible data race that could cause panics in kube-controller-manager and kube-scheduler ([#124518](https://github.com/kubernetes/kubernetes/pull/124518), [@wojtek-t](https://github.com/wojtek-t)) [SIG API Machinery and Scheduling]

    ) {
      setBody(response, Buffer().writeUtf8(content), chunkSize)
    }
  }

  /** Returns a gzipped copy of `bytes`.  */
  fun gzip(data: String): Buffer {
    val result = Buffer()
    val sink = GzipSink(result).buffer()
    sink.writeUtf8(data)
    sink.close()
    return result
  }

  companion object {

  version "4.1.1"
  resolved "https://registry.yarnpkg.com/ansi-colors/-/ansi-colors-4.1.1.tgz#cbb9ae256bf750af1eab344f229aa27fe94ba348"
  integrity sha512-JoX0apGbHaUJBNl6yF+p6JAFYZ666/hhCGKN5t9QFjbJQKUU/g8MNbFDbvfrgKXvI1QpZplPOnwIo99lX/AAmA==

ansi-regex@^5.0.1:
  version "5.0.1"
  resolved "https://registry.yarnpkg.com/ansi-regex/-/ansi-regex-5.0.1.tgz#082cb2c89c9fe8659a311a53bd6a4dc5301db304"

  // For a (long) discussion about this specific issue and the general futility of life.
  //
  // For the time being we are OK with the problem discussed above since it requires a caller to
  // introduce a very specific kind of data-race. And given the other operations performed by these
  // methods that involve volatile read/write operations, in practice there is no issue. Also, the

  private final TestLogHandler aggregateFutureLogHandler = new TestLogHandler();

  private static final String DATA1 = "data";
  private static final String DATA2 = "more data";
  private static final String DATA3 = "most data";

  @Override
  public void setUp() throws Exception {
    super.setUp();
    aggregateFutureLogger.addHandler(aggregateFutureLogHandler);
  }