New submission from Mark Dickinson <dicki...@gmail.com>:
Not a serious bug, but worth noting:
The result of randrange(n) is not even close to uniform for large n. Witness
the obvious skew in the following (this takes a minute or two to run, so you
might want to reduce the range argument):
Python 3.2a0 (py3k:81980, Jun 14 2010, 11:23:36)
[GCC 4.2.1 (SUSE Linux)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from random import randrange
>>> from collections import Counter
>>> Counter(randrange(6755399441055744) % 3 for _ in range(100000000))
Counter({1: 37508130, 0: 33323818, 2: 29168052})
(The actual probabilities here are, as you might guess from the above numbers:
{0: 1/3, 1: 3/8, 2: 7/24}.)
The cause: for n < 2**53, randrange(n) is effectively computed as int(random()
* n). For small n, there's a tiny bias involved, but this is still an
effective method. However, as n increases towards 2**53, the bias increases
significantly. (For n >= 2**53, the random module uses a different strategy
that *does* produce uniformly distributed results.)
A solution would be to lower the cutoff point where randrange() switches from
using int(random() * n) to using the _randbelow method.
----------
components: Library (Lib)
messages: 108095
nosy: mark.dickinson, rhettinger
priority: low
severity: normal
status: open
title: Non-uniformity in randrange for large arguments.
type: behavior
versions: Python 3.2
_______________________________________
Python tracker <rep...@bugs.python.org>
<http://bugs.python.org/issue9025>
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