Arnaud Delobelle wrote:
You could do something like this with the help of itertools.ifilter:
prime_gen = ifilter(
lambda n, P=[]: all(n%p for p in P) and not P.append(n),
count(2)
)
Formidable! (both the English and French meanings) This is the most
elegant, Sieve of Eratosthenes-like solution.
I omitted the 'if p <= sqrt(n)' as it doesn't help the generator go
faster. You could use itertools.takewhile for that:
prime_gen = ifilter(
lambda n, P=[]:
all(n%p for p in takewhile(lambda p, s=n**0.5: p<=s, P))
and not P.append(n),
count(2)
)
Do know what in the itertools implementation causes adding a 'if p <= sqrt(n)'
clause to *decrease* performance, while adding a 'takewhile()' clause
*increases* performance?
Of course there is no excuse for writing Python like that :)
+1 (but it's fun every once in a while, eh?)
Thanks a lot! -John
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