[Prateek]
> I have 3 variable length lists of sets. I need to find the common
> elements in each list (across sets) really really quickly.
. . .
> l1 = reduce(operator.add, list(x) for x in l1)
> l2 = reduce(operator.add, list(x) for x in l2)
> l3 = reduce(operator.add, list(x) for x in l3)
> s = frozenset(l1) & frozenset(l2) & frozenset(l3)
I would write it like this:
def multi_union(listofsets):
result = set()
for s in listofsets:
result |= s
return result
def multi_intersection(listofsets):
return reduce(set.intersection, sorted(listofsets, key=len))
s = multi_intersection(map(multi_union, [l1, l2, l3]))
> I'm assuming frozensets are (somehow) quicker than sets because
> they're immutable.
Frozensets share the same implementation code as regular sets.
They are not more efficient.
> Any code suggestions? Maybe using something in the new fancy-schmancy
> itertools module?
The sets.py module shows how to implement set operations using
itertools.
In general, real set objects should do as well or better than anything
you can cook-up using itertools.
Real set objects have the advantage of knowing the hash values of
their
elements. Accordingly, binary set operations can run without any
calls to element.__hash__().
Raymond Hettinger
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