(I'm assuming that you sent this personally by mistake, and am redirecting back to the list. My apologies if you specifically didn't want this to be public.) On Tue, 15 Nov 2022 at 22:34, James Johnson <jj126979@gmail.com> wrote:
It’s been a couple of years ago, but as I recall the duplicates seemed to be of two or three responses, not randomly distributed.
I looked at my code, and I DID salt the hash at every update.
At this point, my curiosity is engaged to know if this s/w solution is as good as others. I don’t have the training to test how often 9 follows 5, for example, but I am competitive enough to ask how it holds up against MTprng. I think it’s possibly very good, for s/w, and I’m emboldened to ask you to modify the code (it requires you data enter the numbers back to the machine, allowing time to pass;) to accumulate the results for 2 or 3 million, and see how it holds up. I don’t think the numbers track the bell curve on distribution . I speculate it’s more square. I suppose this is desirable in a PRNG?
I'll get you to do the first step of the modification. Turn your code into a module that has a randbelow() function which will return a random integer from 0 up to the provided argument. (This is equivalent to the standard library's random.randrange() function when given just one argument.) If you like, provide several of them, as randbelow1, randbelow2, etc. Post that code, and then I'll post a test harness that can do some analysis for you. ChrisA