Benchmark Comparison Pool

Where coproc was designed for situations where you want to maintain persistent, stateful processes, the conproc.Pool interface essentially emulates the behavior of multiprocessing.Pool in order to benchmark the performance of the underlying WorkerResource and PriorityMessenger systems.

RESULTS: similar performance except when thread tasks are small and numerous, in which case coproc is much slower.

import sys
sys.path.append('..')
import coproc
import multiprocessing

import time
def square(v):
    time.sleep(0.05)
    return v**2

def map_square(vs, pool):
    return pool.map(square, vs)

n = 3
values = list(range(100))
cp = coproc.LazyPool(n)

#map_square(values, cp)
#map_square(values, cp)
#map_square(values, cp)
#map_square(values, cp)
#%timeit map_square(values, cp)
with coproc.Pool(n) as p:
    %time map_square(values, cp)
    %time map_square(values, p)

CPU times: user 1.59 s, sys: 108 ms, total: 1.69 s
Wall time: 1.74 s
CPU times: user 1.55 s, sys: 116 ms, total: 1.66 s
Wall time: 1.71 s