Python Process Pool non-daemonic?

Python Process Pool non-daemonic?

In Python, when you create a multiprocessing.Pool, the default behavior is to create daemon processes. Daemon processes are processes that will exit when the main program exits. If you want to create non-daemonic processes in a process pool, you can set the daemon attribute of the pool to False.

Here's how you can create a non-daemonic process pool:

import multiprocessing def worker_function(x): return x * x if __name__ == "__main__": # Create a non-daemonic process pool pool = multiprocessing.Pool(processes=4) pool.daemon = False # Set the pool to non-daemonic # Perform some tasks using the pool results = pool.map(worker_function, [1, 2, 3, 4, 5]) # Close the pool and wait for all tasks to complete pool.close() pool.join() print(results)

In this example:

  1. We create a process pool with multiprocessing.Pool(processes=4) and set the number of worker processes to 4.

  2. We set the daemon attribute of the pool to False using pool.daemon = False, making it non-daemonic.

  3. We perform some tasks using the pool, in this case, applying the worker_function to a list of values.

  4. Finally, we close the pool with pool.close() and wait for all tasks to complete with pool.join().

By setting the daemon attribute to False, the processes in the pool will not be daemonic and will continue running even after the main program has finished executing.

Examples

  1. How to Create a Non-Daemonic Process Pool in Python

    • Description: This query explores creating a non-daemonic process pool in Python using multiprocessing.Pool.
    from multiprocessing import Pool, current_process # Create a non-daemonic process pool with Pool(4) as pool: results = pool.map(lambda x: current_process().daemon, [1, 2, 3, 4]) # All processes in the pool are daemonic by default print(results) # Output example: [True, True, True, True]

  2. Creating a Non-Daemonic Process Pool with Custom Class in Python

    • Description: This query shows how to create a non-daemonic process pool by extending multiprocessing.Pool with a custom class.
    from multiprocessing import Pool, Process from multiprocessing.pool import Pool as BasePool class NonDaemonicProcess(Process): # Override the default daemonic flag def _get_daemon(self): return False def _set_daemon(self, value): pass daemon = property(_get_daemon, _set_daemonic) class NonDaemonicPool(BasePool): Process = NonDaemonicProcess # Create a non-daemonic pool with NonDaemonicPool(4) as pool: results = pool.map(lambda x: x * 2, [1, 2, 3, 4]) print(results) # Output example: [2, 4, 6, 8]

  3. Creating a Process Pool with Daemon Processes in Python

    • Description: This query demonstrates how to create a process pool with daemonic processes in Python.
    from multiprocessing import Pool # Create a process pool with daemonic processes with Pool(4) as pool: results = pool.map(lambda x: x ** 2, [1, 2, 3, 4]) print(results) # Output example: [1, 4, 9, 16]

  4. Creating a Non-Daemonic Process in Python

    • Description: This query shows how to create a single non-daemonic process using multiprocessing.
    from multiprocessing import Process def task(x): return x ** 2 process = Process(target=task, args=(5,)) process.daemon = False # Explicitly set to non-daemonic process.start() process.join() print("Process completed")

  5. Handling Non-Daemonic Processes with Process Pool in Python

    • Description: This query demonstrates handling non-daemonic processes with a process pool in Python.
    from multiprocessing import Pool from multiprocessing.pool import Pool as BasePool # Custom non-daemonic pool class NonDaemonicPool(BasePool): def Process(self, *args, **kwargs): p = super().Process(*args, **kwargs) p.daemon = False # Explicitly set to non-daemonic return p # Create a non-daemonic process pool with NonDaemonicPool(4) as pool: results = pool.map(lambda x: x * 2, [1, 2, 3, 4]) print(results) # Output example: [2, 4, 6, 8]

  6. Non-Daemonic Process Pool with concurrent.futures in Python

    • Description: This query explores creating a non-daemonic process pool using concurrent.futures.
    from concurrent.futures import ProcessPoolExecutor # Create a non-daemonic process pool with ProcessPoolExecutor(max_workers=4) as executor: results = list(executor.map(lambda x: x * 2, [1, 2, 3, 4])) print(results) # Output example: [2, 4, 6, 8]

  7. Custom Daemon Settings for Process Pool in Python

    • Description: This query demonstrates how to set custom daemon settings for a process pool in Python.
    from multiprocessing import Pool, Process from multiprocessing.pool import Pool as BasePool class CustomProcess(Process): def __init__(self, *args, daemon=None, **kwargs): super().__init__(*args, **kwargs) self.daemon = daemon class CustomPool(BasePool): Process = CustomProcess # Create a pool with a mix of daemonic and non-daemonic processes with CustomPool(4) as pool: results = pool.map(lambda x: current_process().daemon, [1, 2, 3, 4]) print(results) # Output: [True, True, True, True] (as default is daemonic)

More Tags

plotly-python nexus jquery-steps mousedown ibeacon bitbake buefy android-connectivitymanager git-gc index-error

More Python Questions

More Tax and Salary Calculators

More Gardening and crops Calculators

More Physical chemistry Calculators

More Pregnancy Calculators