from __future__ import print_function import sys from itertools import cycle def is_prime(n): return list(zip((True, False), decompose(n)))[-1][0] class IsPrimeCached(dict): def __missing__(self, n): r = is_prime(n) self[n] = r return r is_prime_cached = IsPrimeCached() def croft(): """Yield prime integers using the Croft Spiral sieve. This is a variant of wheel factorisation modulo 30. """ # Copied from: # https://code.google.com/p/pyprimes/source/browse/src/pyprimes.py # Implementation is based on erat3 from here: # http://stackoverflow.com/q/2211990 # and this website: # http://www.primesdemystified.com/ # Memory usage increases roughly linearly with the number of primes seen. # dict ``roots`` stores an entry x:p for every prime p. for p in (2, 3, 5): yield p roots = {} # Map x*d -> 2*d. not_primeroot = tuple(x not in {1,7,11,13,17,19,23,29} for x in range(30)) q = 1 for x in cycle((6, 4, 2, 4, 2, 4, 6, 2)): # Iterate over prime candidates 7, 11, 13, 17, ... q += x # Using dict membership testing instead of pop gives a # 5-10% speedup over the first three million primes. if q in roots: p = roots.pop(q) x = q + p while not_primeroot[x % 30] or x in roots: x += p roots[x] = p else: roots[q * q] = q + q yield q primes = croft def decompose(n): for p in primes(): if p*p > n: break while n % p == 0: yield p n //=p if n > 1: yield n if __name__ == '__main__': # Example: calculate factors of Mersenne numbers to M59 # import time for m in primes(): p = 2 ** m - 1 print( "2**{0:d}-1 = {1:d}, with factors:".format(m, p) ) start = time.time() for factor in decompose(p): print(factor, end=' ') sys.stdout.flush() print( "=> {0:.2f}s".format( time.time()-start ) ) if m >= 59: break