Dan Gheorghe Haiduc <danuthai...@gmail.com> added the comment:
rhettinger wrote [1]: > The existing setobject code has been finely tuned and micro-optimized over > the years, giving it excellent performance on workloads we care about. This worries me also. But I suppose the tuning should make itself visible in benchmarks. Does Python have "canonical" benchmarks or speed tests like PyPy[2]? I am not sure how useful this is, but I made a naive and synthetic line_profiler benchmark of a naive implementation of set through a dict (see attached file). It resulted in roughly the following differences: * Initialization from a 1M-sized list: 41-66% slower * Inserting an item until doubling size: about the same (perhaps faster, due to the size I've chosen not triggering rebuilding of a dict hash table) * Deletion: 7-11% slower * Membership test: 2-15% slower Running them in the opposite order (first dict, then set) gave me the ranges. I have not considered memory usage (I have not profiled memory before). But I suspect this would be larger, since a dict would keep values in addition to keys. Additionally, initializing smaller structures (length = 100) seems to be slower; the initialization takes 2x longer (100% slower), but the O(1) operations take about the same. I suspect methane's implementation linked by xtreak is better (but I have not tried it). Profiled with: kernprof -l set_test.py python -m line_profiler set_test.py.lprof [1] https://mail.python.org/pipermail/python-dev/2019-February/156475.html [2] https://speed.pypy.org/ ---------- Added file: https://bugs.python.org/file49602/set_test.py _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue42368> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
