[OskarS]

Additionally, I think people make a hidden assumption that they don't even realize they're making: that when you ask for random numbers from numpy, they're more or less "true" random numbers, not seeded ones. Like, I think the intention of the programmers is just "give me a bunch of random numbers, I don't really care how as long as they're random", and assumes that that is what that numpy function does. But it doesn't: it provides you a pseudo-random sequence – not true randomness – so of course the sequence is identical after the fork.

Like, they think they're reading from /dev/random, but they're not: they're just running rand() (metaphorically speaking).

[acdha]

Definitely - back when I supported a computational neuroscience group that came up multiple times (not numpy but similar contexts), along with the various quirks around floating point math. Even experienced people do things like that because they’re focused on the actual problem and this is a leaky implementation detail.