Reputation: 142
class PrimesBelow():
def __init__(self,bound):
self.candidate_numbers = list(range(2,bound))
def __iter__(self):
return self
def __next__(self):
if len(self.candidate_numbers) == 0:
raise StopIteration
next_prime = self.candidate_numbers[0]
self.candidate_numbers = [x for x in self.candidate_numbers if x % next_prime != 0]
return next_prime
primes_to_hundread = [prime for prime in PrimesBelow(100)]
print(primes_to_hundread)
Output:
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]
Upvotes: 0
Views: 95
Reputation: 531808
For large (or possibly infinite) bounds, a more (memory-)efficient implemention would use generators:
from itertools import count
from math import gcd
class Sieve:
def __init__(self, bound=None):
self.candidates = count(2) if bound is None else iter(range(2, bound))
def __iter__(self):
return self
def __next__(self):
prime = next(self.candidates)
self.candidates = filter(lambda x, d=prime: x % d != 0, self.candidates)
return prime
When Sieve
is first instantiated, the candidates
attribute is a sequence of integers starting with 2.
__next__
has one precondition: the first element of the candidates
attribute must be a prime number. This is satisfied by the first call because 2
is a prime number.
__next__
then
candidates
and calls it prime
candidates
with a new iterable that consists only of those former candidates that are not divisible by prime
.These two actions fulfill the precondition for the next call to __next__
, as the i
th call to __next__
removes all numbers divisible by the i
th prime number. Thus each remaining candidate is not divisible by any previously seen prime number.
Upvotes: 0
Reputation: 26896
The source of the actual information is here:
[x for x in self.candidate_numbers if x % next_prime != 0]
which contain the sieve of Eratosthenes.
The __iter__
and __next__
method, are special Python methods to have a class behave like an iterator.
Upvotes: 2