Python多重处理-并行处理

Question

I'm new to Python multiprocessing, and I'm trying to implement some parallel calculations. I've got the info that this:

#M is an integer, contains the number of processes I'd like to launch.
results = []
for i in range(0, M):
        p = Process(target=processchild, args=(data[i],q))
        p.start()
        result.append(q.get())
        p.join()

is still sequential, because .join() causes the loop to wait until p is finished before starting the next one. I've read here in an answer, that

You'll either want to join your processes individually outside of your for loop (eg, by storing them in a list and then iterating over it)...

So if I'd modify my code to

results = []
for i in range(0, M):
        processes[i] = Process(target=processchild, args=(data[i],q))
        processes[i].start()
        result.append(q.get())

for i in range(0, M):
        processes[i].join()

Would it actually run in parallel now? If not, how can I modify my code to work that way? I've read the solution using numpy.Pool and apply_async posted as an answer to the question I previously linked, so I'm mostly interested in a solution that doesn't use these.

Answer 1

Yes, this will run in parallel.

All processes are started before you try joining one, so this will not block after the first process.