[Eric] >> My understanding is that the all-int-keys case is an outlier. This is due >> to how ints hash, resulting in fewer collisions and a mostly >> insertion-ordered hash table. Consequently, I'd expect the above >> microbenchmark to give roughly the same result between 3.5 and 3.6, which >> it did.
[Antoine] > Dict iteration shouldn't have any dependence on collisions or insertion > order. It's just a table scan, both in 3.5 and 3.6. Eric is correct on this one. The consecutive hashes make a huge difference for Python 3.5. While there is a table full table scan, the check for NULL entries becomes a predictable branch when all the keys are in consecutive positions. There is an astonishingly well written stack overflow post that explains this effect clearly: http://stackoverflow.com/questions/11227809 With normal randomized keys, Python 3.6 loop is dramatically better that Python 3.5: ~/py36 $ ./python.exe -m timeit -s "d=dict.fromkeys(map(str,range(10**6)))" "list(d)" 100 loops, best of 3: 12.3 msec per loop ~/py35 $ ./python.exe -m timeit -s "d=dict.fromkeys(map(str,range(10**6)))" "list(d)" 10 loops, best of 3: 54.7 msec per loop Repeating the timings, I get consistent results: 12.0 vs 46.7 and 12.0 vs 52.2 and 11.5 vs 44.8. Raymond P.S. Timings are from fresh builds on Mac OS X 10.11.6 running on a 2.6 Ghz Haswell i7 with 16Gb of 1600 Mhz ram: $ ./configure CC=gcc-6 && make _______________________________________________ Python-Dev mailing list Python-Dev@python.org https://mail.python.org/mailman/listinfo/python-dev Unsubscribe: https://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
