日記ネタ: list, array, numpy.arrayの処理時間

speed.py

import timeit

common_for = """
for d in data:
    s += d
"""
common_sum = """
sum(data)
"""
common_numpy_sum = """
numpy.sum(data)
"""

def timeit_list(n, iter):
    list_setup = """
import numpy
data = [1] * {}
s = 0
""".format(n)
    print 'list:',
    print timeit.timeit(common_for, list_setup, number = iter),
    print timeit.timeit(common_sum, list_setup, number = iter),
    print timeit.timeit(common_numpy_sum, list_setup, number = iter)

def timeit_array(n, iter):
    array_setup = """
import numpy
import array
data = array.array('L', [1] * {})
s = 0
""".format(n)
    print 'array:',
    print timeit.timeit(common_for, array_setup, number = iter),
    print timeit.timeit(common_sum, array_setup, number = iter),
    print timeit.timeit(common_numpy_sum, array_setup, number = iter)

def timeit_numpy(n, iter):
    numpy_setup = """
import numpy
data = numpy.array([1] * {})
s = 0
""".format(n)
    print 'numpy.array:',
    print timeit.timeit(common_for, numpy_setup, number = iter),
    print timeit.timeit(common_sum, numpy_setup, number = iter),
    print timeit.timeit(common_numpy_sum, numpy_setup, number = iter)

if __name__ == '__main__':
    timeit_list(100000, 1000)
    timeit_array(100000, 1000)
    timeit_numpy(100000, 1000)