数据结构性能分析

- 实例化一个空列表，将0-n范围的数据添加到列表中

def test01():
    alist = []
    for i in range(10000):
        alist.append(i)
    return alist

def test02():
    alist = []
    for i in range(10000):
        alist += [i]
    return alist

def test03():
    alist = [i for i in range(10000)]
    return alist

def test04():
    alist = list(range(10000))
    return alist

• timeit模块：该模块可以用来测试一段python代码的执行速度/时长。

• Timer类：该类是timeit模块中专门用于测量python代码的执行速度/时长的。原型为：class timeit.Timer(stmt='pass',setup='pass')。

  • stmt参数：表示即将进行测试的代码块语句。

  • setup：运行代码块语句时所需要的设置。

  • timeit函数：timeit.Timer.timeit(number=100000),该函数返回代码块语句执行number次的平均耗时　　

from timeit import Timer


def test01():
    alist = []
    for i in range(10000):
        alist.append(i)
    return alist


def test02():
    alist = []
    for i in range(10000):
        alist += [i]
    return alist


def test03():
    alist = [i for i in range(10000)]
    return alist


def test04():
    alist = list(range(10000))
    return alist


if __name__ == '__main__':
    t1 = Timer('test01()', setup='from __main__ import test01')
    second_1 = t1.timeit(1000)
    print(second_1)

    t2 = Timer('test02()', setup='from __main__ import test02')
    second_2 = t2.timeit(1000)
    print(second_2)

    t3 = Timer('test03()', setup='from __main__ import test03')
    second_3 = t3.timeit(1000)
    print(second_3)

    t4 = Timer('test04()', setup='from __main__ import test04')
    second_4 = t4.timeit(1000)
    print(second_4)

#0.82598802
#0.9852309690000001
#0.40580514600000006
#0.2559222590000001

• 计算运行平均耗时