cc @colesbury

It'd be great to have the default random number generator be safe and efficient when called from multiple threads, but I think that's a bigger change that requires more discussion and maybe a PEP.

In the meantime, I think the advice should be to use individual Random objects per-thread. In other words, the program should be written as:

def monte_carlo_pi_part(n: int, idx: int, results: list[int]) -> None:
    r = random.Random()
    count = 0
    for i in range(n):
        x = r.random()
        y = r.random()

        if x*x + y*y <= 1:
            count += 1
    results[idx] = count

I think that you also would need #118112 (or deferred reference counting) for the program to be efficient, or otherwise the reference count contention is going to be a bottleneck.

In the meantime, I think the advice should be to use individual Random objects per-thread. In other words, the program should be written as:

Yeah, it works. so it should be included somewhere in the migration guide.

#118393 (comment)

We could also consider adopting a strategy like Go does, at least for the free-threaded build:

• If seed() has not been called, use a fast per-thread RNG for the global calls
• Once seed() is called, switch to the shared state RNG to preserve old behavior.