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July 21, 2013 07:04
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Python multiprocessing hello world. Split a list and process sublists in different jobs
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import multiprocessing | |
# split a list into evenly sized chunks | |
def chunks(l, n): | |
return [l[i:i+n] for i in range(0, len(l), n)] | |
def do_job(job_id, data_slice): | |
for item in data_slice: | |
print "job", job_id, item | |
def dispatch_jobs(data, job_number): | |
total = len(data) | |
chunk_size = total / job_number | |
slice = chunks(data, chunk_size) | |
jobs = [] | |
for i, s in enumerate(slice): | |
j = multiprocessing.Process(target=do_job, args=(i, s)) | |
jobs.append(j) | |
for j in jobs: | |
j.start() | |
if __name__ == "__main__": | |
data = ['a', 'b', 'c', 'd'] | |
dispatch_jobs(data, 2) | |
As someone just learning to program, this finally made multiprocessing make sense. Thanks for posting.
That is a nice example, thank you!
Exactly what I needed to see. Thank you.
Good example for the beginner programming.
For python 3.7, the section
slice = chunks(data, chunk_size)
needs to be changed to:
slice = chunks(data, int(chunk_size))
To avoid:
TypeError: 'float' object cannot be interpreted as an integer
Good example for the beginner programming.
For python 3.7, the section
slice = chunks(data, chunk_size)
needs to be changed to:
slice = chunks(data, int(chunk_size))
To avoid:
TypeError: 'float' object cannot be interpreted as an integer
or
chunk_size = total // job_number
it works to me! thanks
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very elegant. thanks for sharing!