2016-09-15 8:31 GMT+02:00 Serhiy Storchaka <storch...@gmail.com>: > Note that this is made at the expense of the 20% slowing down an iteration. > > $ ./python -m timeit -s "d = dict.fromkeys(range(10**6))" -- "list(d)" > Python 3.5: 66.1 msec per loop > Python 3.6: 82.5 msec per loop > > Fortunately the cost of the lookup (the most critical operation for dicts) > seems left the same. > > But this can be an argument against using this technique in sets.
My small benchmarks on dict memory usage and dict lookup: http://bugs.python.org/issue27350#msg275581 It seems like the memory usage is between 20% and 25% smaller. Great job! Memory usage, Python 3.5 => Python 3.6 on Linux x86_64: ./python -c 'import sys; print(sys.getsizeof({str(i):i for i in range(10)}))' * 10 items: 480 B => 384 B (-20%) * 100 items: 6240 B => 4720 B (-24%) * 1000 items: 49248 B => 36984 B (-25%) Note: the size is the the size of the container itself, not of keys nor values. http://bugs.python.org/issue27350#msg275587 As I expected, a dictionary lookup is a _little bit_ slower (3%) between Python 3.5 and Python 3.6: $ ./python -m perf timeit -s 'd={str(i):i for i in range(100)}' 'd["10"]; d["20"]; d["30"]; d["40"]; d["50"]; d["10"]; d["20"]; d["30"]; d["40"]; d["50"]' --rigorous Median +- std dev: [lookup35] 309 ns +- 10 ns -> [lookup36] 320 ns +- 8 ns: 1.03x slower Victor _______________________________________________ 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
