numpy vs list comprehension, which is faster?
I ran a simple speed test comparing numpy and python list comprehension, and apparently list comprehension was faster. Is that correct?

    import sys, numpy
	from datetime import datetime

	def numpysum(n):
		a = numpy.arange(n) ** 2
		b = numpy.arange(n) ** 3
		return a + b

	def pythonsum(n):
		a = [i ** 2 for i in range(n)]
		b = [i ** 3 for i in range(n)]
		return [a[i] + b[i] for i in range(n)]

	size = 10
	start = datetime.now()
	c1 = pythonsum(size)
	delta1 = datetime.now() - start

	start = datetime.now()
	c2 = numpysum(size)
	delta2 = datetime.now() - start

	print c1
	print c2

	print delta1
	print delta2
numpy vs list comprehension, which is faster?
===

I ran a simple speed test comparing numpy and python list comprehension, and apparently list comprehension was faster. Is that correct?

    import sys, numpy
	from datetime import datetime

	def numpysum(n):
		a = numpy.arange(n) ** 2
		b = numpy.arange(n) ** 3
		return a + b

	def pythonsum(n):
		a = [i ** 2 for i in range(n)]
		b = [i ** 3 for i in range(n)]
		return [a[i] + b[i] for i in range(n)]

	size = 10
	start = datetime.now()
	c1 = pythonsum(size)
	delta1 = datetime.now() - start

	start = datetime.now()
	c2 = numpysum(size)
	delta2 = datetime.now() - start

	print c1
	print c2

	print delta1
	print delta2