标签：style blog color 使用 strong 数据
1- "原地"排序-转换后替换
>>> list = [2,1,3]
>>> list.sort()
>>> list
[1, 2, 3]
降序 reverse = True
>>> list.sort(reverse = True) >>> list [3, 2, 1, 1]
2- "复制"排序-转换然后返回
>>> data = []
>>> list = [3,2,4,1]
>>> data = sorted(list)
>>> data
[1, 2, 3, 4]
>>> list
[3, 2, 4, 1]
>>>
降序参数 reverse = True
>>> data = sorted(list, reverse = True) >>> data [5, 3, 2, 1]
3- "方法串链"-从左向右读,对数据应用一组方法
1 try: 2 with open(filename) as f: 3 data = f.readline() 4 return ( data.strip().split(‘,‘))
4- "函数串链"-从右向左读,对数据应用一组函数
print( sorted( set ([sanitize(s) for s in julie]) )[0:3] )
5- "列表推导" - 在一行上指定一个转换(不是使用迭代)
>>> new_l = [] >>> for each_item in old_l: ... new_l.append(len(each_item))
可用下面方法替换
>>> new_l = [] >>> new_l = [ len(s) for s in old_l ]
6- "分片" 从一个列表访问多个列表项 [1:2] 不包含2,只显示第1个项目, 从0开始
>>> list = [1,2,3,4] >>> list[1:2] [2] >>> list[1:3] [2, 3] >>>
7- "集合"- 一组无序的数据项,其中不包含重复项,使用set工厂
>>> list = [1,1,2,3] >>> set( list ) {1, 2, 3}
print( sorted( set ([sanitize(s) for s in james]) )[0:3] )
[Head First Python] 5. summary,布布扣,bubuko.com
[Head First Python] 5. summary
标签：style blog color 使用 strong 数据
原文地址：http://www.cnblogs.com/galoishelley/p/3794781.html
