What is the advantage of iteritems?

Question

I am using Python 2.7.5 @ Mac OS X 10.9.3 with 8GB memory and 1.7GHz Core i5. I have tested time consumption as below.

d = {i:i*2 for i in xrange(10**7*3)} #WARN         


        

Answer 1

I know technically this is not an answer to the question, but the comments section is a poor place to put this sort of information. I hope that this helps people better understand the nature of the problem being discussed.

For thoroughness I've timed a bunch of different configurations. These are all timed using timeit with a repetition factor of 10. This is using CPython version 2.7.6 on Mac OS X 10.9.3 with 16GB memory and 2.3GHz Core i7.

The original configuration

python -m timeit -n 10 -s 'd={i:i*2 for i in xrange(10**7*3)}' 'for k in d: k, d[k]'
>> 10 loops, best of 3: 2.05 sec per loop

python -m timeit -n 10 -s 'd={i:i*2 for i in xrange(10**7*3)}' 'for k, v in d.iteritems(): k, v'
>> 10 loops, best of 3: 1.74 sec per loop

Bakuriu's suggestion

This suggestion involves passing in the iteritems loop, and assigning a value to a variable v in the first loop by accessing the dictionary at k.

python -m timeit -n 10 -s 'd={i:i*2 for i in xrange(10**7*3)}' 'for k in d: v = d[k]'
>> 10 loops, best of 3: 1.29 sec per loop

python -m timeit -n 10 -s 'd={i:i*2 for i in xrange(10**7*3)}' 'for k, v in d.iteritems(): pass'
>> 10 loops, best of 3: 934 msec per loop

No assignment in the first

This one removes the assignment in the first loop but keeps the dictionary access. This is not a fair comparison because the second loop creates an additional variable and assigns it a value implicitly.

python -m timeit -n 10 -s 'd={i:i*2 for i in xrange(10**7*3)}' 'for k in d: d[k]'
>> 10 loops, best of 3: 1.27 sec per loop

Interestingly, the assignment is trivial to the access itself -- the difference being a mere 20 msec total. In every comparison (even the final, unfair one), the iteritems wins out.

The times are closest, percentage wise, in the original configuration. This is probably due to the bulk of the work being creating a tuple (which is not assigned anywhere). Once that is removed from the equation, the differences between the two methods becomes more pronounced.