labels.includedDocPaths=Chemins inclus pour la recherche
labels.includedDocUrls=URL incluses pour la recherche
labels.maxAccessCount=Nombre d'accès maximum
labels.name=Nom
labels.numOfThread=Nombre de threads
labels.duplicateHostName=Nom d'hôte en double
labels.pageNumber=Numéro de page
labels.password=Mot de passe
labels.paths=Chemins
labels.port=Port
labels.regex=Expression régulière
labels.regularName=Nom régulier

        method.setAccessible(true);

        // Test with null thread
        try {
            method.invoke(crawler, (Thread) null);
        } catch (Exception e) {
            fail("Should not throw exception with null thread");
        }

        // Test with normal thread
        Thread testThread = new Thread(() -> {
            try {

 * currently supporting Kryo and JavaBin serialization formats. The serializer
 * type is determined by the crawler data serializer configuration.
 * </p>
 * <p>
 * The class is thread-safe and uses ThreadLocal to maintain Kryo instances
 * per thread to avoid synchronization overhead.
 * </p>
 *
 */
public class DataSerializer {

    /** Logger for this class. */

            assertTrue(processHelper.isProcessRunning());

            // Wait a bit for the processes to start
            Thread.sleep(50);

            // Destroy all processes
            processHelper.destroy();

            // Wait a bit for destruction to complete
            Thread.sleep(100);

            assertFalse(processHelper.isProcessRunning());
        } catch (Exception e) {

 *
 * OkHttp performs best when you create a single `OkHttpClient` instance and reuse it for all of
 * your HTTP calls. This is because each client holds its own connection pool and thread pools.
 * Reusing connections and threads reduces latency and saves memory. Conversely, creating a client
 * for each request wastes resources on idle pools.
 *
 * Use `new OkHttpClient()` to create a shared instance with the default settings:
 *

labels.includedUrls=Included URLs for Crawling
labels.includedDocPaths=Included Paths for Searching
labels.includedDocUrls=Included URLs for Searching
labels.maxAccessCount=Max Access Count
labels.name=Name
labels.numOfThread=Number of Threads
labels.duplicateHostName=Duplicate Host Name
labels.pageNumber=Page Number
labels.password=Password
labels.paths=Paths
labels.port=Port
labels.regex=Regex
labels.regularName=Regular Name

        final ClassLoader context = Thread.currentThread().getContextClassLoader();
        try {
            final ClassLoader cl = new URLClassLoader(new URL[0], getClass().getClassLoader());
            Thread.currentThread().setContextClassLoader(cl);
            assertThat(ClassLoaderUtil.getClassLoader(TestCase.class), is(sameInstance(cl)));
        } finally {
            Thread.currentThread().setContextClassLoader(context);

Mas antes disso, controlar código assíncrono era bem mais complexo e difícil.

Nas versões anteriores do Python, você poderia utilizar threads ou <a href="http://www.gevent.org/" class="external-link" target="_blank">Gevent</a>. Mas o código é bem mais complexo de entender, debugar, e pensar sobre.

        @Test
        @DisplayName("Should handle received notification")
        void testReceived() throws InterruptedException {
            CountDownLatch latch = new CountDownLatch(1);

            Thread waiter = new Thread(() -> {
                synchronized (response) {
                    try {
                        if (!response.isReceived()) {
                            response.wait(1000);
                        }

// that pass integers back and forth.  No actual
// concurrency, just threads and synchronization
// and foreign code on multiple pthreads.

package main

import (
	big "."
	"runtime"
)

func fibber(c chan *big.Int, out chan string, n int64) {
	// Keep the fibbers in dedicated operating system
	// threads, so that this program tests coordination
	// between pthreads and not just goroutines.