生成列表

要生成list [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],我们可以用range(1, 11):

>>> range(1, 11)
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

但如果要生成[1x1, 2x2, 3x3, ..., 10x10]怎么做?方法一是循环:

>>> L = []
>>> for x in range(1, 11):
... L.append(x * x)
...
>>> L
[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

但是循环太繁琐,而列表生成式则可以用一行语句代替循环生成上面的list:

>>> [x * x for x in range(1, 11)]
[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

这种写法就是Python特有的列表生成式。利用列表生成式,可以以非常简洁的代码生成 list。

写列表生成式时,把要生成的元素 x * x 放到前面,后面跟 for 循环,就可以把list创建出来,十分有用,多写几次,很快就可以熟悉这种语法。

任务

请利用列表生成式生成列表 [1x2, 3x4, 5x6, 7x8, ..., 99x100]

提示:range(1, 100, 2) 可以生成list [1, 3, 5, 7, 9,...]

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" 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复杂表达式

使用for循环的迭代不仅可以迭代普通的list,还可以迭代dict。

假设有如下的dict:

d = { 'Adam': 95, 'Lisa': 85, 'Bart': 59 }

完全可以通过一个复杂的列表生成式把它变成一个 HTML 表格:

tds = ['<tr><td>%s</td><td>%s</td></tr>' % (name, score) for name, score in d.iteritems()]
print '<table>'
print '<tr><th>Name</th><th>Score</th><tr>'
print '\n'.join(tds)
print '</table>'

注:字符串可以通过 % 进行格式化,用指定的参数替代%s。字符串的join()方法可以把一个 list 拼接成一个字符串。

把打印出来的结果保存为一个html文件,就可以在浏览器中看到效果了:

<table border="1">
<tr><th>Name</th><th>Score</th><tr>
<tr><td>Lisa</td><td>85</td></tr>
<tr><td>Adam</td><td>95</td></tr>
<tr><td>Bart</td><td>59</td></tr>
</table>

任务

在生成的表格中,对于没有及格的同学,请把分数标记为红色。

提示:红色可以用 <td style="color:red"> 实现。

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alt="" />

条件过滤

列表生成式的 for 循环后面还可以加上 if 判断。例如:

>>> [x * x for x in range(1, 11)]
[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

如果我们只想要偶数的平方,不改动 range()的情况下,可以加上 if 来筛选:

>>> [x * x for x in range(1, 11) if x % 2 == 0]
[4, 16, 36, 64, 100]

有了 if 条件,只有 if 判断为 True 的时候,才把循环的当前元素添加到列表中。

任务

请编写一个函数,它接受一个 list,然后把list中的所有字符串变成大写后返回,非字符串元素将被忽略。

提示:

1. isinstance(x, str) 可以判断变量 x 是否是字符串;

2. 字符串的 upper() 方法可以返回大写的字母。

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" 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多层表达式

for循环可以嵌套,因此,在列表生成式中,也可以用多层 for 循环来生成列表。

对于字符串 'ABC' 和 '123',可以使用两层循环,生成全排列:

>>> [m + n for m in 'ABC' for n in '123']
['A1', 'A2', 'A3', 'B1', 'B2', 'B3', 'C1', 'C2', 'C3']

翻译成循环代码就像下面这样:

L = []
for m in 'ABC':
for n in '123':
L.append(m + n)

任务

利用 3 层for循环的列表生成式,找出对称的 3 位数。例如,121 就是对称数,因为从右到左倒过来还是 121。

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" alt="" />

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