New submission from Joachim:
The »basic example of data parallelism using Pool« is too basic. It
demonstrates the syntax, but otherwise makes no sense, and therefore is
potentially confusing. It is blatant nonsense to run 5 processes when there are
only 3 data to be treated. Let me suggest the following:
from multiprocessing import Pool
import time
def f(x):
time.sleep(1)
return x*x
if __name__ == '__main__':
start_time = time.time()
with Pool(4) as p:
print(p.map(f, range(20)))
print("elapsed wall time: ", time.time()-start_time)
The sleep command makes f representative for a function that takes significant
time to execute. Printing the elapsed time shows the user that the 20 calls of
f have indeed taken place in parallel.
----------
assignee: docs@python
components: Documentation
messages: 287895
nosy: docs@python, j5w6
priority: normal
severity: normal
status: open
title: doc 17.2.1: basic Pool example is too basic
versions: Python 3.7
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Python tracker <rep...@bugs.python.org>
<http://bugs.python.org/issue29575>
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