List comprehension, map, and numpy.vectorize performance
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Published on 2010-04-24T05:16:33Z
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2010/04/24
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I have a function foo(i) that takes an integer and takes a significant amount of time to execute. Will there be a significant performance difference between any of the following ways of initializing a:
a = [foo(i) for i in xrange(100)]
a = map(foo, range(100))
vfoo = numpy.vectorize(foo)
a = vfoo(range(100))
(I don't care whether the output is a list or a numpy array.)
Is there a better way?
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