python for-loop parallelization using multiprocessing.pool -

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i have piece of code looks this:

def calc_stuff(x,a,b,c):     ...     return y x = range(n) y = zeros(x.shape) if __name__ == '__main__':     p = pool(nprocs)     y = p.map(calc_stuff,x,a,b,c)

this not work, , searched online, because map function deals iterables rather argument lists. wonder what's simplest method modify code parallelize it, i.e., x array/iterable want parallelize.

thank you.

one option use itertools.repeat zip (or itertools.izip) build multiple arguments iterable of tuples , use multiprocessing.pool.starmap call function tuple unpacked arguments:

from itertools import repeat  if __name__ == '__main__':     p = pool(nprocs)     y = p.starmap(calc_stuff, zip(x, repeat(a), repeat(b), repeat(c)))

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