Question

Which one of these is faster? Is one “better”? Basically I’ll have two sets and I want to eventually get one match from between the two lists. So really I suppose the for loop is more like:

for object in set:
    if object in other_set:
        return object

Like I said – I only need one match, but I’m not sure how intersection() is handled, so I don’t know if its any better. Also, if it helps, the other_set is a list near 100,000 components and the set is maybe a few hundred, max few thousand.

Answer 1

from timeit import timeit

setup = """
from random import sample, shuffle
a = range(100000)
b = sample(a, 1000)
a.reverse()
"""

forin = setup + """
def forin():
    # a = set(a)
    for obj in b:
        if obj in a:
            return obj
"""

setin = setup + """
def setin():
    # original method:
    # return tuple(set(a) & set(b))[0]
    # suggested in comment, doesn't change conclusion:
    return next(iter(set(a) & set(b)))
"""

print timeit("forin()", forin, number = 100)
print timeit("setin()", setin, number = 100)

Times:

>>>
0.0929054012768
0.637904308732
>>>
0.160845057616
1.08630760484
>>>
0.322059185123
1.10931801261
>>>
0.0758695262169
1.08920981403
>>>
0.247866360526
1.07724461708
>>>
0.301856152688
1.07903130641

Making them into sets in the setup and running 10000 runs instead of 100 yields

>>>
0.000413064976328
0.152831597075
>>>
0.00402408388788
1.49093627898
>>>
0.00394538156695
1.51841512101
>>>
0.00397715579584
1.52581949403
>>>
0.00421472926155
1.53156769646

So your version is much faster whether or not it makes sense to convert them to sets.