.Builder()
        .add("Connection", "close")
        .add("Transfer-Encoding", "chunked")
        .build()
    val headers2 =
      Headers
        .Builder()
        .add("Connection", "keep-alive")
        .add("Transfer-Encoding", "chunked")
        .build()
    assertThat(headers2).isNotEqualTo(headers1)
    assertThat(headers2.hashCode()).isNotEqualTo(headers1.hashCode().toLong())
  }

	wrappedHandler := http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
		// If server is in shutdown.
		if atomic.LoadUint32(&srv.inShutdown) != 0 {
			// To indicate disable keep-alive, server is shutting down.
			w.Header().Set("Connection", "close")

			// Add 1 minute retry header, incase-client wants to honor it
			w.Header().Set(RetryAfter, "60")

 * number of streams, dynamically configured with `SETTINGS_MAX_CONCURRENT_STREAMS`. A connection
 * currently carrying zero streams is an idle stream. We keep it alive because reusing an existing
 * connection is typically faster than establishing a new one.
 *
 * When a single logical call requires multiple streams due to redirects or authorization

set FESS_JAVA_OPTS=%FESS_JAVA_OPTS% -XX:MaxDirectMemorySize=%FESS_DIRECT_SIZE%
)

REM set to headless, just in case
set FESS_JAVA_OPTS=%FESS_JAVA_OPTS% -Djava.awt.headless=true

REM maximum # keep-alive connections to maintain at once
set FESS_JAVA_OPTS=%FESS_JAVA_OPTS% -Dhttp.maxConnections=20

REM Force the JVM to use IPv4 stack
if NOT "%FESS_USE_IPV4%" == "" (

* back and forth: de un lado a otro
* I/O (as in "input and output"): I/O (do not translate to "E/S")
* Machine Learning: Machine Learning (do not translate to "Aprendizaje Automático")
* Deep Learning: Deep Learning (do not translate to "Aprendizaje Profundo")
* callback hell: callback hell (do not translate to "infierno de callbacks")
* tip: Consejo (do not translate to "tip")

  @Test
  public void testThatFinalizerStops() {
    weaklyReferenceQueue();
    GcFinalization.awaitClear(queueReference);
  }

  /** If we don't keep a strong reference to the reference object, it won't be enqueued. */
  @Nullable FinalizableWeakReference<Object> reference;

  /** Create the FRQ in a method that goes out of scope so that we're sure it will be reclaimed. */
  private void weaklyReferenceQueue() {

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

There is some assistance in the IDE for this plus a lot of validation that is applied at build time and on CI, but it is useful to keep these constraints in mind as well.

See [Gradle runtimes](runtimes.md) for a list of these runtimes and more details.

### Build execution model

                return host + "/"; // mimic the JVM behaviour for root or server
            }
            if (path.endsWith("/")) {
                return path.substring(0, path.length()); // keep trailing slash
            }
            String[] parts = path.split("/");
            return parts[parts.length - 1];
        }

        @Override
        public String getParent() {

   * example, we could compute the appropriate throttle time for an incoming request, and make the
   * calling thread wait for that time.
   *
   * The simplest way to maintain a rate of QPS is to keep the timestamp of the last granted
   * request, and ensure that (1/QPS) seconds have elapsed since then. For example, for a rate of
   * QPS=5 (5 tokens per second), if we ensure that a request isn't granted earlier than 200ms after