Adam Olsen writes:
If random.shuffle() is broken for lists more than 2080 then it should raise an error.
Not really. Assuming the initial state is drawn from a uniform distribution on all possible states, if all 2080-shuffles are equiprobable, then any statistic you care to calculate based on that will come out the same as if you had 2080 statistically independent draws without replacement. Another way to put it is "if you need a random shuffle, this one is good enough for *any* such purpose". However, once you exceed that limit you have to ask whether it's good enough for the purpose at hand. For some purposes, the distribution of (2**19937-1)-shuffles might be good enough, even though they make up only 1/(2**19937-2) of the possible shuffles. (Yeah, I know, you can wait....)
Claiming it "might" be broken in the docs for moderately sized lists, without researching such a claim, is pointless fear mongering.
How about if it's phrased the way I did above? Ie, this is good enough for any N-shuffle for *any purpose whatsoever*, for N < 2081.