I want to execute some tasks in parallel in multiple subprocesses and time out if the tasks were not completed within some delay.
A first approach consists in forking and joining the subprocesses individually with remaining timeouts computed with respect to the global timeout, like suggested in this answer. It works fine for me.
A second approach, which I want to use here, consists in creating a pool of subprocesses and waiting with the global timeout, like suggested in this answer.
However I have a problem with the second approach: after feeding the pool of subprocesses with tasks that have multiprocessing.Event()
objects, waiting for their completion raises this exception:
RuntimeError: Condition objects should only be shared between processes through inheritance
Here is the Python code snippet:
import multiprocessing.pool
import time
class Worker:
def __init__(self):
self.event = multiprocessing.Event() # commenting this removes the RuntimeError
def work(self, x):
time.sleep(1)
return x * 10
if __name__ == "__main__":
pool_size = 2
timeout = 5
with multiprocessing.pool.Pool(pool_size) as pool:
result = pool.map_async(Worker().work, [4, 5, 2, 7])
print(result.get(timeout)) # raises the RuntimeError