Marc-Andre Lemburg added the comment: On 04.02.2016 09:01, STINNER Victor wrote: > > "In a numerics heavy application it's like that all fast paths will trigger > somewhere, but those will likely be better off using numpy or numba. For a > text heavy application such as a web server, only few fast paths will trigger > and so the various checks only add overhead." > > Hum, I disagree. See benchmark results in other messages. Examples: > > ### django_v2 ### > Min: 2.682884 -> 2.633110: 1.02x faster > > ### unpickle_list ### > Min: 1.333952 -> 1.212805: 1.10x faster > > These benchmarks are not written for numeric, but are more "general" > benchmarks. int is just a core feature of Python, simply used everywhere, as > the str type.
Sure, some integer math is used in text applications as well, e.g. for indexing, counting and slicing, but the patch puts more emphasis on numeric operations, e.g. fast_add() tests for integers and floats before then coming back to check for Unicode. It would be interesting to know how often these paths trigger or not in the various benchmarks. BTW: The django_v2 benchmark result does not really say anything much. Values of +/- 2% do not have much meaning in benchmark results :-) ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue21955> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
