multiprocessing – Page 16

How to get the return value of a function passed to multiprocessing.Process?

November 25, 2022 by Tarik

Use shared variable to communicate. For example like this: import multiprocessing def worker(procnum, return_dict): “””worker function””” print(str(procnum) + ” represent!”) return_dict[procnum] = procnum if __name__ == “__main__”: manager = multiprocessing.Manager() return_dict = manager.dict() jobs = [] for i in range(5): p = multiprocessing.Process(target=worker, args=(i, return_dict)) jobs.append(p) p.start() for proc in jobs: proc.join() print(return_dict.values())

Show the progress of a Python multiprocessing pool imap_unordered call?

November 22, 2022 by Tarik

My personal favorite — gives you a nice little progress bar and completion ETA while things run and commit in parallel. from multiprocessing import Pool import tqdm pool = Pool(processes=8) for _ in tqdm.tqdm(pool.imap_unordered(do_work, tasks), total=len(tasks)): pass

How to use multiprocessing queue in Python?

November 22, 2022 by Tarik

My main problem is that I really don’t know how to implement multiprocessing.queue correctly, you cannot really instantiate the object for each process since they will be separate queues, how do you make sure that all processes relate to a shared queue (or in this case, queues) This is a simple example of a reader … Read more

What exactly is Python multiprocessing Module’s .join() Method Doing?

November 21, 2022 by Tarik

The join() method, when used with threading or multiprocessing, is not related to str.join() – it’s not actually concatenating anything together. Rather, it just means “wait for this [thread/process] to complete”. The name join is used because the multiprocessing module’s API is meant to look as similar to the threading module’s API, and the threading … Read more

Shared-memory objects in multiprocessing

November 20, 2022 by Tarik

If you use an operating system that uses copy-on-write fork() semantics (like any common unix), then as long as you never alter your data structure it will be available to all child processes without taking up additional memory. You will not have to do anything special (except make absolutely sure you don’t alter the object). … Read more

Keyboard Interrupts with python’s multiprocessing Pool

November 17, 2022 by Tarik

This is a Python bug. When waiting for a condition in threading.Condition.wait(), KeyboardInterrupt is never sent. Repro: import threading cond = threading.Condition(threading.Lock()) cond.acquire() cond.wait(None) print “done” The KeyboardInterrupt exception won’t be delivered until wait() returns, and it never returns, so the interrupt never happens. KeyboardInterrupt should almost certainly interrupt a condition wait. Note that this … Read more

multiprocessing: How do I share a dict among multiple processes?

November 12, 2022 by Tarik

A general answer involves using a Manager object. Adapted from the docs: from multiprocessing import Process, Manager def f(d): d[1] += ‘1’ d[‘2’] += 2 if __name__ == ‘__main__’: manager = Manager() d = manager.dict() d[1] = ‘1’ d[‘2’] = 2 p1 = Process(target=f, args=(d,)) p2 = Process(target=f, args=(d,)) p1.start() p2.start() p1.join() p2.join() print d … Read more

How to run functions in parallel?

October 26, 2022 by Tarik

You could use threading or multiprocessing. Due to peculiarities of CPython, threading is unlikely to achieve true parallelism. For this reason, multiprocessing is generally a better bet. Here is a complete example: from multiprocessing import Process def func1(): print ‘func1: starting’ for i in xrange(10000000): pass print ‘func1: finishing’ def func2(): print ‘func2: starting’ for … Read more

Multiprocessing : use tqdm to display a progress bar

October 21, 2022 by Tarik

Use imap instead of map, which returns an iterator of the processed values. from multiprocessing import Pool import tqdm import time def _foo(my_number): square = my_number * my_number time.sleep(1) return square if __name__ == ‘__main__’: with Pool(2) as p: r = list(tqdm.tqdm(p.imap(_foo, range(30)), total=30))

Multiprocessing – Pipe vs Queue

October 20, 2022 by Tarik

A Pipe() can only have two endpoints. A Queue() can have multiple producers and consumers. When to use them If you need more than two points to communicate, use a Queue(). If you need absolute performance, a Pipe() is much faster because Queue() is built on top of Pipe(). Performance Benchmarking Let’s assume you want … Read more