Can I get a return value from multiprocessing.Process?

by

The MonteCarlo objects have been pickled and sent to child processes to be run – the .results attribute in this process isn’t populated because the local mc has never been run.

If you create a multiprocessing.Queue, you can pass that into each MonteCarlo job, and when it finishes it should put the result in there. Then the top-level can wait for values from the queue. (Under the hood this will pickle and unpickle the result object.) 

result_queue = multiprocessing.Queue()
montecarlos = [MonteCarlo(result_queue, f,fargs) for fargs in farglist]
jobs = [multiprocessing.Process(mc) for mc in montecarlos]
for job in jobs: job.start()
for job in jobs: job.join()
results = [result_queue.get() for mc in montecarlos]

More Related Contents:

  1. How to use multiprocessing pool.map with multiple arguments
  2. Can’t pickle when using multiprocessing Pool.map()
  3. What are the differences between the threading and multiprocessing modules?
  4. Is shared readonly data copied to different processes for multiprocessing?
  5. Python Process Pool non-daemonic?
  6. Combine Pool.map with shared memory Array in Python multiprocessing
  7. python multiprocessing on windows, if __name__ == “__main__”
  8. Sharing a complex object between processes?
  9. Filling a queue and managing multiprocessing in python
  10. Child processes created with python multiprocessing module won’t print
  11. Python command line input in a process
  12. What exactly is Python multiprocessing Module’s .join() Method Doing?
  13. yet another confusion with multiprocessing error, ‘module’ object has no attribute ‘f’
  14. Passing multiple parameters to pool.map() function in Python [duplicate]
  15. Catch Ctrl+C / SIGINT and exit multiprocesses gracefully in python [duplicate]
  16. Simple Python Multiprocessing function in Spyder doesn’t output results
  17. Python multiprocessing example not working
  18. Multiprocessing launching too many instances of Python VM
  19. Modify object in python multiprocessing
  20. Python Multiprocess Pool. How to exit the script when one of the worker process determines no more work needs to be done?
  21. How to do multiprocessing in FastAPI
  22. multiprocessing pool example does not work and freeze the kernel
  23. How to process requests from multiiple users using ML model and FastAPI?
  24. Is it possible to multiprocess a function that returns something in Python?
  25. Easiest way to read csv files with multiprocessing in Pandas
  26. Using multiprocessing.Process with a maximum number of simultaneous processes
  27. Understanding Multiprocessing: Shared Memory Management, Locks and Queues in Python
  28. How can I abort a task in a multiprocessing.Pool after a timeout?
  29. Terminate a Python multiprocessing program once a one of its workers meets a certain condition
  30. Multiprocessing Share Unserializable Objects Between Processes

Leave a Comment