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?

python performance numpy list-comprehension
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