问题描述
我想选择一个介于a
和b
之间的随机整数.
I want to pick a random integer between a
and b
, inclusive.
我知道3种方式.但是,它们的表现似乎非常违反直觉:
I know 3 ways of doing it. However, their performance seems very counter-intuitive:
import timeit
t1 = timeit.timeit("n=random.randint(0, 2)", setup="import random", number=100000)
t2 = timeit.timeit("n=random.choice([0, 1, 2])", setup="import random", number=100000)
t3 = timeit.timeit("n=random.choice(ar)", setup="import random; ar = [0, 1, 2]", number=100000)
[print(t) for t in [t1, t2, t3]]
在我的机器上,这给出了:
On my machine, this gives:
0.29744589625620965
0.19716156798482648
0.17500512311108346
使用在线解释器,它可以:
0.23830216699570883
0.16536146598809864
0.15081614299560897
请注意,使用专用功能完成我正在做的事情的最直接版本(#1)比预定义数组的最奇怪的版本(#3)差50%(em)50%.然后从中随机选择.
Note how the most direct version (#1) that uses the dedicated function for doing what I'm doing is 50% worse that the strangest version (#3) which pre-defines an array and then chooses randomly from it.
这是怎么回事?
推荐答案
这只是实现细节. randint
代表 randrange
,因此它具有另一层函数调用开销,而经过大量的参数检查和其他操作.相反, choice
是一个非常简单的-内衬.
It's just implementation details. randint
delegates to randrange
, so it has another layer of function call overhead, and randrange
goes through a lot of argument checking and other crud. In contrast, choice
is a really simple one-liner.
这是此调用的代码路径randint
,其中注释和未执行的代码被删除:
Here's the code path randint
goes through for this call, with comments and unexecuted code stripped out:
def randint(self, a, b):
return self.randrange(a, b+1)
def randrange(self, start, stop=None, step=1, _int=int, _maxwidth=1L<<BPF):
istart = _int(start)
if istart != start:
# not executed
if stop is None:
# not executed
istop = _int(stop)
if istop != stop:
# not executed
width = istop - istart
if step == 1 and width > 0:
if width >= _maxwidth:
# not executed
return _int(istart + _int(self.random()*width))
这是choice
通过的代码路径:
def choice(self, seq):
return seq[int(self.random() * len(seq))]
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