1、本文主要对传统for循环，sum函数，以及numpy包中的sum函数的执行快慢进行比较
for循环：
sum_by_for="""
for d in data:
s+=d
"""sum函数：
sum_by_sum="""
sum(data)
"""numpy中的sum函数：
sum_by_numpy="""
import numpy
numpy.sum(data)
"""2、本文针对上述三种方法，分别对list，array和numpy数据形式用上述三种方法进行比较：
list：
def timeit_using_list(n,loops):
list_setup="""
data=[1]*{}
s=0
""".format(n)
print('list result:')
print(timeit.timeit(sum_by_for,list_setup,number=loops))
print(timeit.timeit(sum_by_sum,list_setup,number=loops))
print(timeit.timeit(sum_by_numpy,list_setup,number=loops))array：
def timeit_using_array(n,loops):
array_setup="""
import array
data=array.array('L',[1]*{})
s=0
""".format(n)
print('array result:')
print(timeit.timeit(sum_by_for,array_setup,number=loops))
print(timeit.timeit(sum_by_sum,array_setup,number=loops))
print(timeit.timeit(sum_by_numpy,array_setup,number=loops))def numpy:
def timeit_using_numpy(n,loops):
numpy_setup="""
import numpy
data=numpy.array([1]*{})
s=0
""".format(n)
print('numpy result:')
print(timeit.timeit(sum_by_for,numpy_setup,number=loops))
print(timeit.timeit(sum_by_sum,numpy_setup,number=loops))
print(timeit.timeit(sum_by_numpy,numpy_setup,number=loops))3、实验结果对比
全部代码：
import timeit
sum_by_for="""
for d in data:
s+=d
"""
sum_by_sum="""
sum(data)
"""
sum_by_numpy="""
import numpy
numpy.sum(data)
"""
def timeit_using_list(n,loops):
list_setup="""
data=[1]*{}
s=0
""".format(n)
print('list result:')
print(timeit.timeit(sum_by_for,list_setup,number=loops))
print(timeit.timeit(sum_by_sum,list_setup,number=loops))
print(timeit.timeit(sum_by_numpy,list_setup,number=loops))
def timeit_using_array(n,loops):
array_setup="""
import array
data=array.array('L',[1]*{})
s=0
""".format(n)
print('array result:')
print(timeit.timeit(sum_by_for,array_setup,number=loops))
print(timeit.timeit(sum_by_sum,array_setup,number=loops))
print(timeit.timeit(sum_by_numpy,array_setup,number=loops))
def timeit_using_numpy(n,loops):
numpy_setup="""
import numpy
data=numpy.array([1]*{})
s=0
""".format(n)
print('numpy result:')
print(timeit.timeit(sum_by_for,numpy_setup,number=loops))
print(timeit.timeit(sum_by_sum,numpy_setup,number=loops))
print(timeit.timeit(sum_by_numpy,numpy_setup,number=loops))
if __name__=='__main__':
timeit_using_list(30000,500)
timeit_using_array(30000,500)
timeit_using_numpy(30000,500)