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#!/usr/bin/env python
"""
A simple example of parallel computation using a map and managed callables.
"""
import pprocess
import time
#import random
# Array size and a limit on the number of processes.
N = 10
limit = 10
delay = 1
# Work function and monitoring class.
def calculate(i, j):
"""
A supposedly time-consuming calculation on 'i' and 'j'.
"""
#time.sleep(delay * random.random())
time.sleep(delay)
return i * N + j
# Main program.
if __name__ == "__main__":
t = time.time()
# Initialise the results using a map with a limit on the number of
# channels/processes.
results = pprocess.Map(limit=limit, reuse=1)
# Wrap the calculate function and manage it.
calc = results.manage(pprocess.MakeReusable(calculate))
# Perform the work.
print "Calculating..."
for i in range(0, N):
for j in range(0, N):
calc(i, j)
# Show the results.
for i in range(0, N):
for result in results[i*N:i*N+N]:
print result,
print
print "Time taken:", time.time() - t
# vim: tabstop=4 expandtab shiftwidth=4
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