runCalled.getAndIncrement();
          }
        },
        directExecutor());
    Runnable execute =
        new Runnable() {
          @Override
          public void run() {
            list.execute();
          }
        };
    Thread thread1 = new Thread(execute);
    Thread thread2 = new Thread(execute);
    thread1.start();
    thread2.start();
    assertEquals(0, runCalled.get());

### Configuración de Plugins para OpenSearch

Ejecuta antrun:run para descargar los plugins en el directorio de plugins:

    $ mvn antrun:run

### Ejecutar Fess

Ejecuta o depura `org.codelibs.fess.FessBoot` en tu IDE, y luego accede a http://localhost:8080/

### Construir el Paquete

Ejecuta el objetivo `package` y luego se creará el archivo de lanzamiento en target/releases.

   * @param executor the executor with which removal notifications are asynchronously executed
   */
  public static <K, V> RemovalListener<K, V> asynchronous(
      RemovalListener<K, V> listener, Executor executor) {
    checkNotNull(listener);
    checkNotNull(executor);
    return (RemovalNotification<K, V> notification) ->
        executor.execute(() -> listener.onRemoval(notification));
  }

# Depuração

Você pode conectar o depurador no seu editor, por exemplo, com o Visual Studio Code ou PyCharm.

## Chamar `uvicorn`

Em seu aplicativo FastAPI, importe e execute `uvicorn` diretamente:

{* ../../docs_src/debugging/tutorial001.py hl[1,15] *}

### Sobre `__name__ == "__main__"`

O objetivo principal de `__name__ == "__main__"` é ter algum código que seja executado quando seu arquivo for chamado com:

<div class="termy">

   * one of the listener's callbacks will execute at once. However, multiple listeners' callbacks
   * may execute concurrently, and listeners may execute in an order different from the one in which
   * they were registered.
   *
   * <p>RuntimeExceptions thrown by a listener will be caught and logged. Any exception thrown
   * during {@code Executor.execute} (e.g., a {@code RejectedExecutionException}) will be caught and

        // Test execute method with null query
        QueryContext context = new QueryContext("*:*", false);
        float boost = 1.0f;

        QueryBuilder result = matchAllQueryCommand.execute(context, null, boost);

        assertNotNull(result);
        assertTrue(result instanceof MatchAllQueryBuilder);
    }

    public void test_execute_withZeroBoost() {
        // Test execute method with zero boost

    return new NoOpScheduledExecutorService();
  }

  /**
   * Creates a scheduled executor service that runs each task in the thread that invokes {@code
   * execute/submit/schedule}, as in {@link CallerRunsPolicy}. This applies both to individually
   * submitted tasks and to collections of tasks submitted via {@code invokeAll}, {@code invokeAny},

programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a

        echo "### NOT starting on installation, please execute the following statements to configure fess service to start automatically using chkconfig"
        echo " sudo chkconfig --add fess"
        echo "### You can start fess service by executing"
        echo " sudo service fess start"

    elif command -v update-rc.d >/dev/null; then

        return (context, query, boost) -> filter.execute(context, query, boost, chain);
    }

    /**
     * Creates the default filter chain that executes query commands.
     * This chain looks up the appropriate query command based on the query class name
     * and executes it. If no command is found, throws an InvalidQueryException.
     *