Tim Peters <t...@python.org> added the comment:
This is where you're not getting traction: "A randrange() function should a priori not be so strongly tied to the binary base." That's a raw assertion. _Why_ shouldn't it be? "Because I keep saying so" isn't changing minds ;-) I understand you're looking at exact equality of t-tuples. I wasn't in my example: I was looking at the individual values, one pair at a time. The extreme correlation is dead obvious by eyeball either way, despite that the only test you seem to have in mind (exact equality of t-tuples) is blind to it. Why is that test so important? Why does it not matter that, e.g., number of inversions, number of runs, distribution of run-lengths (etc) remain highly correlated regardless? Nobody else has had a problem with this, and it remains unclear why you do: what's your objection to Mark's suggestions (use different seeds, or _don't_ reset the seed)? That's the obvious approach: use the facilities in straightforward ways. In any case, we can't/won't make changes on a whim. As far as possible, we strive to keep results bit-for-bit identical across releases for people who save/set seeds, hoping to get reproducible results. Changing the results from any random module function requires strong justification. So far, I don't see that here. ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue39867> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
