sharpsmile 发表于 2017-1-6 10:49:24

python 遍历中each的用法

今天在练习Python零基础的时候,课后练习的动动手部分,有这么个题目:

data:image/png;base64,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

当我采用位置参数,一个个去读取列表中的元素,然后打印出来:
member = ['小甲鱼', '88', '黑夜', '90', '迷途', '85', '怡景', '90', '秋舞斜阳','88']
i = 0
index = len(member)
for i in range(index):
    item = member
    print(item)
    i+=1

然后看到小甲鱼的参考答案用了for each去遍历,
代码立马简洁了许多。{:5_95:}
那么,求解下 each在python中的用法。(当然我也会百度)

yretsym 发表于 2017-1-6 16:40:28

member = ['小甲鱼', 88, '黑夜', 90, '迷途', 85, '怡静', 90, '秋舞斜阳', 88]
for each in member:
    print(each)
楼主说的是这个each?
这个each只是个变量名,你改成别的同样成立
例如:
member = ['小甲鱼', 88, '黑夜', 90, '迷途', 85, '怡静', 90, '秋舞斜阳', 88]
for i in member:
    print(i)

sharpsmile 发表于 2017-1-6 17:32:11

本帖最后由 sharpsmile 于 2017-1-6 17:35 编辑

一语惊醒梦中人,被自己蠢哭了{:5_104:}

sharpsmile 发表于 2017-1-6 17:33:09

yretsym 发表于 2017-1-6 16:40
楼主说的是这个each?
这个each只是个变量名,你改成别的同样成立
例如:

一语惊醒梦中人,被自己蠢哭了,为什么大家都用each,,for reach.....

yxyzlgy 发表于 2023-2-26 21:35:37

yretsym 发表于 2017-1-6 16:40
楼主说的是这个each?
这个each只是个变量名,你改成别的同样成立
例如:

{:5_100:}原来如此
页: [1]
查看完整版本: python 遍历中each的用法