IPython 中用 magic 命令 %timeit 来计时。
比较生成速度
%timeit [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25]1000000 loops, best of 3: 456 ns per loop%timeit (1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25)10000000 loops, best of 3: 23 ns per loop
可以看到，元组的生成速度要比列表的生成速度快得多，相差大概一个数量级。
比较遍历速度
产生内容相同的随机列表和元组：
'''遇到问题没人解答？小编创建了一个Python学习交流QQ群：778463939寻找有志同道合的小伙伴，互帮互助,群里还有不错的视频学习教程和PDF电子书！'''from numpy.random import randvalues = rand(10000,4)lst = [list(row) for row in values]tup = tuple(tuple(row) for row in values)%timeit for row in lst: list(row)100 loops, best of 3: 4.12 ms per loop%timeit for row in tup: tuple(row)100 loops, best of 3: 2.07 ms per loop
在遍历上，元组和列表的速度表现差不多。
比较遍历和索引速度：
%timeit for row in lst: a = row[0] + 1The slowest run took 12.20 times longer than the fastest. This could mean that an intermediate result is being cached 100 loops, best of 3: 3.73 ms per loop%timeit for row in tup: a = row[0] + 1100 loops, best of 3: 3.82 ms per loop
元组的生成速度会比列表快很多，迭代速度快一点，索引速度差不多。
