Python八大常见排序算法定义、实现及时间消耗效率分析
这篇文章主要介绍了python八大常见排序算法定义、实现及时间消耗效率分析,结合具体实例形式对比分析了冒泡排序、直接插入排序、选择排序、归并排序、希尔排序、桶排序、堆排序等排序算法的使用与执行效率,需要的朋友可以参考下
本文实例讲述了Python八大常见排序算法定义、实现及时间消耗效率分析。分享给大家供大家参考,具体如下:
昨晚上开始总结了一下常见的几种排序算法,由于之前我已经写了好几篇排序的算法的相关博文了现在总结一下的话可以说是很方便的,这里的目的是为了更加完整详尽的总结一下这些排序算法,为了复习基础的东西,从冒泡排序、直接插入排序、选择排序、归并排序、希尔排序、桶排序、堆排序。快速排序入手来分析和实现,在最后也给出来了简单的时间统计,重在原理、算法基础,其他的次之,这些东西的熟练掌握不算是对之后的工作或者接下来的准备面试都是很有帮助的,算法重在理解内在含义和理论基础,在实现的时候才能避开陷阱少出错误,这不是说练习的时候有错误不好而是说,有些不该出现的错误尽量还是少出现的好,毕竟好的编程习惯是离不开严格的约束的,好了,这里就不多说了,复习一下基础知识,共同学习吧,下面是具体实现,注释应该都很详细,就不解释了:
#!usr/bin/env python#encoding:utf-8'''''__Author__:沂水寒城功能:八大排序算法'''import timeimport randomtime_dict={}def time_deco(sort_func): ''''' 时间计算的装饰器函数,可用于计算函数执行时间 ''' def wrapper(num_list): start_time=time.time() res=sort_func(num_list) end_time=time.time() time_dict[str(sort_func)]=(end_time-start_time)*1000 print '耗时为:',(end_time-start_time)*1000 print '结果为:', res return wrapperdef random_nums_generator(max_value=1000, total_nums=20): ''''' 随机数列表生成器 一些常用函数: random随机数生成 random.random()用于生成一个0到1之间的随机数:0 num_list[j]: #这里是升序排序 num_list[i], num_list[j]=num_list[j], num_list[i] return num_list#@time_decodef Insert_sort(num_list): ''''' 直接插入排序,时间复杂度O(n^2),空间复杂度O(1),是稳定排序 ''' for i in range(len(num_list)): for j in range(0,i): if num_list[i]<num_list def>0: i=0 while i<count:>=0: if t>=new_list[k]: new_list.insert(k+1, t) break k=k-step if knum_list[max_temp]: max_temp = left_child if right_child<size>num_list[max_temp]: max_temp = right_child if max_temp != i: num_list[i], num_list[max_temp] = num_list[max_temp], num_list[i] Heap_adjust(num_list, max_temp, size) #避免调整之后以max为父节点的子树不是堆def Create_heap(num_list, size): a = size/2-1 for i in range(a, -1, -1): #print '**********', i Heap_adjust(num_list, i, size)#@time_decodef Heap_sort(num_list): ''''' 堆排序,时间复杂度:O(nlog₂n),空间复杂度:O(1),不是稳定排序 ''' size=len(num_list) Create_heap(num_list, size) i = size-1 while i > 0: num_list[0], num_list[i] = num_list[i], num_list[0] size -= 1 i -= 1 Heap_adjust(num_list, 0, size) return num_listif __name__ == '__main__': num_list=random_nums_generator(max_value=100, total_nums=50) print 'Bubble_sort', Bubble_sort(num_list) print 'Insert_sort', Insert_sort(num_list) print 'Select_sort', Select_sort(num_list) print 'Merge_sort', Merge_sort(num_list) print 'Shell_sort', Shell_sort(num_list) print 'Tong_sort', Tong_sort(num_list) print 'Heap_sort', Heap_sort(num_list) print 'Quick_sort', Quick_sort(num_list) # print '-----------------------------------------------------------------------------' # for k,v in time_dict.items(): # print k, v</size></count:></num_list>
结果如下:
立即学习“Python免费学习笔记(深入)”;
Bubble_sort [34, 49, 63, 67, 71, 72, 75, 120, 128, 181, 185, 191, 202, 217, 241, 257, 259, 260, 289, 293, 295, 304, 311, 326, 362, 396, 401, 419, 423, 456, 525, 570, 618, 651, 701, 711, 717, 718, 752, 774, 813, 816, 845, 885, 894, 900, 918, 954, 976, 998]Insert_sort [34, 49, 63, 67, 71, 72, 75, 120, 128, 181, 185, 191, 202, 217, 241, 257, 259, 260, 289, 293, 295, 304, 311, 326, 362, 396, 401, 419, 423, 456, 525, 570, 618, 651, 701, 711, 717, 718, 752, 774, 813, 816, 845, 885, 894, 900, 918, 954, 976, 998]Select_sort [34, 49, 63, 67, 71, 72, 75, 120, 128, 181, 185, 191, 202, 217, 241, 257, 259, 260, 289, 293, 295, 304, 311, 326, 362, 396, 401, 419, 423, 456, 525, 570, 618, 651, 701, 711, 717, 718, 752, 774, 813, 816, 845, 885, 894, 900, 918, 954, 976, 998]Merge_sort [34, 49, 63, 67, 71, 72, 75, 120, 128, 181, 185, 191, 202, 217, 241, 257, 259, 260, 289, 293, 295, 304, 311, 326, 362, 396, 401, 419, 423, 456, 525, 570, 618, 651, 701, 711, 717, 718, 752, 774, 813, 816, 845, 885, 894, 900, 918, 954, 976, 998]Shell_sort [34, 49, 63, 67, 71, 72, 75, 120, 128, 181, 185, 191, 202, 217, 241, 257, 259, 260, 289, 293, 295, 304, 311, 326, 362, 396, 401, 419, 423, 456, 525, 570, 618, 651, 701, 711, 717, 718, 752, 774, 813, 816, 845, 885, 894, 900, 918, 954, 976, 998]Tong_sort [34, 49, 63, 67, 71, 72, 75, 120, 128, 181, 185, 191, 202, 217, 241, 257, 259, 260, 289, 293, 295, 304, 311, 326, 362, 396, 401, 419, 423, 456, 525, 570, 618, 651, 701, 711, 717, 718, 752, 774, 813, 816, 845, 885, 894, 900, 918, 954, 976, 998]Heap_sort [34, 49, 63, 67, 71, 72, 75, 120, 128, 181, 185, 191, 202, 217, 241, 257, 259, 260, 289, 293, 295, 304, 311, 326, 362, 396, 401, 419, 423, 456, 525, 570, 618, 651, 701, 711, 717, 718, 752, 774, 813, 816, 845, 885, 894, 900, 918, 954, 976, 998]Quick_sort [34, 49, 63, 67, 71, 72, 75, 120, 128, 181, 185, 191, 202, 217, 241, 257, 259, 260, 289, 293, 295, 304, 311, 326, 362, 396, 401, 419, 423, 456, 525, 570, 618, 651, 701, 711, 717, 718, 752, 774, 813, 816, 845, 885, 894, 900, 918, 954, 976, 998]这里没有使用到装饰器,主要自己对这个装饰器不太了解,在快速排序的时候报错了,也没有去解决,这里简单贴一下一个测试样例使用装饰器的结果吧:
Bubble_sort 耗时为: 0.0290870666504
结果为: [5, 45, 46, 63, 81, 83, 89, 89, 89, 90]
None
Insert_sort 耗时为: 0.0209808349609
结果为: [5, 45, 46, 63, 81, 83, 89, 89, 89, 90]
None
Select_sort 耗时为: 0.0259876251221
结果为: [5, 45, 46, 63, 81, 83, 89, 89, 89, 90]
None
Merge_sort 耗时为: 0.0138282775879
结果为: [5, 45, 46, 63, 81, 83, 89, 89, 89, 90]
None
Shell_sort 耗时为: 0.113964080811
结果为: [5, 45, 46, 63, 81, 83, 89, 89, 89, 90]
None
Tong_sort 耗时为: 0.0460147857666
结果为: [5, 45, 46, 63, 81, 83, 89, 89, 89, 90]
None
Heap_sort 耗时为: 0.046968460083
结果为: [5, 45, 46, 63, 81, 83, 89, 89, 89, 90]
None
Quick_sort [5, 45, 46, 63, 81, 83, 89, 89, 89, 90]
-----------------------------------------------------------------------------
0.113964080811
0.0259876251221
0.0209808349609
0.046968460083
0.0138282775879
0.0460147857666
0.0290870666504
接下来有时间的话我想学一下装饰器的东西,感觉对于模式化的东西装饰器简直就是一个神器,但是得明白会用会写才行哈!