*
   * <p><b>Warning:</b> This method, which reencodes the input before hashing it, is useful only for
   * cross-language compatibility. For other use cases, prefer {@link #hashUnencodedChars}, which is
   * faster, produces the same output across Java releases, and hashes every {@code char} in the
   * input, even if some are invalid.
   */
  HashCode hashString(CharSequence input, Charset charset);

  /**

   *
   * <p><b>Warning:</b> This method, which reencodes the input before hashing it, is useful only for
   * cross-language compatibility. For other use cases, prefer {@link #hashUnencodedChars}, which is
   * faster, produces the same output across Java releases, and hashes every {@code char} in the
   * input, even if some are invalid.
   */
  HashCode hashString(CharSequence input, Charset charset);

  /**

		controllers.WithGenericReconciler(s.reconcile),
		controllers.WithMaxAttempts(5),
	)
	// We only need to handle pods on our node
	s.pods = kclient.NewFiltered[*corev1.Pod](kubeClient, kclient.Filter{FieldSelector: "spec.nodeName=" + NodeName})
	s.pods.AddEventHandler(controllers.FromEventHandler(func(o controllers.Event) {
		s.queue.Add(o)
	}))

	// Namespaces could be anything though, so we watch all of those
	//

        bool((must, should, mustNot, filter) -> {
            filteredLambda.callback(must, filter);
        }, opLambda);
    }

    public void not(OperatorCall<LabelTypeCQ> notLambda) {
        not(notLambda, null);
    }

    public void not(final OperatorCall<LabelTypeCQ> notLambda, final ConditionOptionCall<BoolQueryBuilder> opLambda) {
        bool((must, should, mustNot, filter) -> notLambda.callback(mustNot), opLambda);
    }

    protected String searchPreference;

    protected String[] targetIndices;

    public FesenClient() {
        address = System.getProperty(HTTP_ADDRESS, "localhost:9200").trim();
        final String targets = System.getProperty(TARGET_INDICES);
        if (StringUtil.isNotBlank(targets)) {
            targetIndices = Arrays.stream(targets.split(",")).map(String::trim).toArray(n -> new String[n]);

    [`tf.debugging`](https://www.tensorflow.org/versions/master/api_docs/python/tf/debugging),
    [`tf.dtypes`](https://www.tensorflow.org/versions/master/api_docs/python/tf/dtypes),
    [`tf.image`](https://www.tensorflow.org/versions/master/api_docs/python/tf/image),
    [`tf.io`](https://www.tensorflow.org/versions/master/api_docs/python/tf/io),
    [`tf.linalg`](https://www.tensorflow.org/versions/master/api_docs/python/tf/linalg),

      <name>Nexus Release Repository</name>
      <url>https://oss.sonatype.org/service/local/staging/deploy/maven2/</url>
    </repository>
    <site>
      <id>guava-site</id>
      <name>Guava Documentation Site</name>
      <url>scp://dummy.server/dontinstall/usestaging</url>
    </site>
  </distributionManagement>
  <dependencyManagement>
    <dependencies>
      <dependency>

      <name>Nexus Release Repository</name>
      <url>https://oss.sonatype.org/service/local/staging/deploy/maven2/</url>
    </repository>
    <site>
      <id>guava-site</id>
      <name>Guava Documentation Site</name>
      <url>scp://dummy.server/dontinstall/usestaging</url>
    </site>
  </distributionManagement>
  <dependencyManagement>
    <dependencies>
      <dependency>

Then APIStar stopped to exist as a server and Starlette was created, and was a new better foundation for such a system. That was the final inspiration to build **FastAPI**.

I consider **FastAPI** a "spiritual successor" to APIStar, while improving and increasing the features, typing system, and other parts, based on the learnings from all these previous tools.

///

## Used by **FastAPI**

    long length = 0;
    for (long[] array : arrays) {
      length += array.length;
    }
    long[] result = new long[checkNoOverflow(length)];
    int pos = 0;
    for (long[] array : arrays) {
      System.arraycopy(array, 0, result, pos, array.length);
      pos += array.length;
    }
    return result;
  }

  private static int checkNoOverflow(long result) {
    checkArgument(