如果您使用内置功能的map，那么它可能比LC稍快：>>> strs = " ".join(str(x) for x in xrange(10**5))
>>> %timeit [int(x) for x in strs.split()]
1 loops, best of 3: 111 ms per loop
>>> %timeit map(int, strs.split())
1 loops, best of 3: 105 ms per loop
使用用户定义的函数：>>> def func(x):
... return int(x)
>>> %timeit map(func, strs.split())
1 loops, best of 3: 129 ms per loop
>>> %timeit [func(x) for x in strs.split()]
1 loops, best of 3: 128 ms per loop
Python 3.3.1比较：>>> strs = " ".join([str(x) for x in range(10**5)])
>>> %timeit list(map(int, strs.split()))
10 loops, best of 3: 59 ms per loop
>>> %timeit [int(x) for x in strs.split()]
10 loops, best of 3: 79.2 ms per loop
>>> def func(x):
return int(x)
...
>>> %timeit list(map(func, strs.split()))
10 loops, best of 3: 94.6 ms per loop
>>> %timeit [func(x) for x in strs.split()]
1 loops, best of 3: 92 ms per loopThe only restriction is that the "loop body" of map must be a function
call. Besides the syntactic benefit of list comprehensions, they are
often as fast or faster than equivalent use of map.