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Timefold solves planning problems. This lightweight, embeddable planning engine implements powerful and scalable algorithms to optimize business resource scheduling and planning. This module contains the core implementation of the Python solver.

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package ai.timefold.solver.python;

import java.util.concurrent.Executors;
import java.util.concurrent.ThreadFactory;

/**
 * There a Catch-22 that occurs on shutdown:
 * 
 * - In order for Python to free its variables, it must be terminated.
 * - In order for Python to be terminated, the JVM must be terminated.
 * - In order for the JVM to be terminated, all its non-daemon threads must be terminated.
 * - Executors keep all its threads alive until it is freed/have no more references.
 * - In order for the Executor to be freed/have no more references, it cannot have a reference in Python.
 * - To not have a reference in Python means Python must free its variables, creating the Catch-22
 * 

 * Thus, if non-daemon threads are used, and a {@link ai.timefold.solver.core.api.solver.SolverManager}
 * solves at least one problem (creating a keep-alive thread in its {@link java.util.concurrent.ThreadPoolExecutor}),
 * Python cannot shut down gracefully and will become unresponsive when interrupted.
 * 
 * This class uses {@link Executors#defaultThreadFactory()} to create a new thread, but sets the created
 * thread to daemon mode so Python can shut down gracefully.
 */
public class DaemonThreadFactory implements ThreadFactory {
    private static final ThreadFactory THREAD_FACTORY = Executors.defaultThreadFactory();

    @Override
    public Thread newThread(Runnable runnable) {
        Thread out = THREAD_FACTORY.newThread(runnable);
        out.setDaemon(true);
        return out;
    }
}