/** The key of the message: Started a data update process. */
    public static final String SUCCESS_started_data_update = "{success.started_data_update}";

    /** The key of the message: Started re-indexing. */
    public static final String SUCCESS_reindex_started = "{success.reindex_started}";

    /** The key of the message: Started a bulk process. */

    val a3 = client.newCall(newRequest("http://a/3"))
    val a4 = client.newCall(newRequest("http://a/4"))
    val t1 = makeSynchronousCall(a1)
    val t2 = makeSynchronousCall(a2)

    // We created 4 calls and started 2 of them. That's 2 running calls and 0 queued.
    ready.await()
    assertThat(dispatcher.runningCallsCount()).isEqualTo(2)
    assertThat(dispatcher.queuedCallsCount()).isEqualTo(0)

     * `input` does not have a scheme that starts at `pos`.
     */
    private fun schemeDelimiterOffset(
      input: String,
      pos: Int,
      limit: Int,
    ): Int {
      if (limit - pos < 2) return -1

      val c0 = input[pos]
      if ((c0 < 'a' || c0 > 'z') && (c0 < 'A' || c0 > 'Z')) return -1 // Not a scheme start char.

      characters@ for (i in pos + 1 until limit) {

    assertTrue(executor.isTerminated());
    assertInterrupted();
  }

  /**
   * Wrapper around {@link Stopwatch} which also contains an "expected completion time." Creating a
   * {@code Completion} starts the underlying stopwatch.
   */
  private static final class Completion {
    final Stopwatch stopwatch;
    final long expectedCompletionWaitMillis;

    Completion(long expectedCompletionWaitMillis) {

                    proactiveCheckInterval, TimeUnit.MILLISECONDS);
            log.info("Started proactive health checking with interval {} ms", proactiveCheckInterval);
        }
    }

    /**
     * Stop proactive health checking
     */
    public void stopProactiveHealthChecking() {
        if (healthCheckTask != null) {
            healthCheckTask.cancel(false);

    * `tf.data` now has an `autotune_options.initial_parallelism` option to
      control the initial parallelism setting used by autotune before the data
      pipeline has started running. The default is 16. A lower value reduces
      initial memory usage, while a higher value improves startup time.

## Keras

*  `keras.layers.experimental.DynamicEmbedding`
    * Added `DynamicEmbedding` Keras layer
    * Added 'UpdateEmbeddingCallback`

    void testReadAndXWireFormatWithPlainSMB() {
        DummyPlainSMB next = new DummyPlainSMB();
        // The implementation uses andx.wordCount, which starts at 0 by default
        // We need to test the actual behavior where wordCount is 0
        // This means readParameterWordsWireFormat won't be called (line 282-284)

        DummyAndXBlock block = new DummyAndXBlock(next);

compression will not only reduce disk usage but also help increase system throughput.
Typically, enabling compression on spinning disk systems
will increase speed when the content can be compressed.

## Get Started

### 1. Prerequisites

Install MinIO - [MinIO Quickstart Guide](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-on-redhat-linux.html).

### 2. Run MinIO with compression

$ python main.py

I solemnly swear 🐺
```

</div>

## Alternatives { #alternatives }

This is a simple guide to get you started and teach you how everything works **underneath**.

There are many **alternatives** to managing virtual environments, package dependencies (requirements), projects.

	if h == nil {
		return "", nil
	}
	start := strconv.Itoa(int(h.Start))
	end := strconv.Itoa(int(h.End))
	switch {
	case h.Start >= 0 && h.End >= 0:
		if h.Start > h.End {
			return "", errInvalidRange
		}
	case h.IsSuffixLength:
		end = strconv.Itoa(int(h.Start * -1))
		start = ""
	case h.Start > -1:
		end = ""
	default: