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I obviously have a version without the memory issue.

The programming flexibility is indeed the win.

    def primes ():
        yield 2
        yield 3
        f = {}
        n = 5
        for p in primes():
            if p == 2:
                continue
            p2 = p*p
            while n < p2:
                if n in f:
                    double_p = f.pop(n)
                    m = n + double_p
                    while m in f:
                        m += double_p
                    f[m] = double_p
                else:
                    yield n
                n += 2
            f[n] = 2*p



This allocates a dictionary and the primes() generator for every single prime generated though, so it still has the memory issue, unless there's something I'm missing about how it works?


Put a debugging statement in and you'll verify that the dictionary only contains primes up to the square root of the one just generated.

To do that it recursively contains a second prime generator that only produces up to the square root. Which contains one that produces up to the fourth root. And so on until you get down to 3. The work and memory for those recursive generators is a rounding error compared to the initial prime generator. The work and memory saved by not keeping unnecessary primes is a significant win.


Oh, thanks for the explanation, I get how it works now. I hadn't seen this trick for an unbounded prime sieve before, and it's a nice idea.




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