What you are looking for is the process pool class in multiprocessing.
import multiprocessing
import subprocess
def work(cmd):
return subprocess.call(cmd, shell=False)
if __name__ == '__main__':
count = multiprocessing.cpu_count()
pool = multiprocessing.Pool(processes=count)
print pool.map(work, ['ls'] * count)
And here is a calculation example to make it easier to understand. The following will divide 10000 tasks on N processes where N is the cpu count. Note that I’m passing None as the number of processes. This will cause the Pool class to use cpu_count for the number of processes (reference)
import multiprocessing
import subprocess
def calculate(value):
return value * 10
if __name__ == '__main__':
pool = multiprocessing.Pool(None)
tasks = range(10000)
results = []
r = pool.map_async(calculate, tasks, callback=results.append)
r.wait() # Wait on the results
print results