嵌套列表推导式

列表解析中的第一个表达式可以是任何表达式，包括列表解析。

考虑下面由三个长度为 4 的列表组成的 3x4 矩阵：

>>> matrix = [
...     [1, 2, 3, 4],
...     [5, 6, 7, 8],
...     [9, 10, 11, 12],
... ]

现在，如果你想交换行和列，可以用嵌套的列表推导式：

>>> [[row[i] for row in matrix] for i in range(4)]
[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

像前面看到的，嵌套的列表推导式是对 for 后面的内容进行求值，所以上例就等价于：

>>> transposed = []
>>> for i in range(4):
...     transposed.append([row[i] for row in matrix])
...
>>> transposed
[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

反过来说，如下也是一样的：

>>> transposed = []
>>> for i in range(4):
...     # the following 3 lines implement the nested listcomp
...     transposed_row = []
...     for row in matrix:
...         transposed_row.append(row[i])
...     transposed.append(transposed_row)
...
>>> transposed
[[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

在实际中，使用内置函数组成复杂流程语句。对此种情况zip()函数将会做的更好：

>>> list(zip(*matrix))
[(1, 5, 9), (2, 6, 10), (3, 7, 11), (4, 8, 12)]