4 ms·

Of course you have a different machine but the OP was getting 2.5 us per parse in .NET versus your 89.5 us in Python. I wouldn't have expected such a difference

by yread 10y ago

Of course you have a different machine but the OP was getting 2.5 us per parse in .NET versus your 89.5 us in Python. I wouldn't have expected such a difference. No wonder it's hot path

fnord123 10y ago
Well that's dateutil (installed from pip) and not datetime (std). As part of log ingestion I would, of course, convert to UTC and drop the timezone distinctions since it does slow down python a lot when it has to worry about timezones. Working within the same units and no DST issues is much nicer/quicker. Anyway, if you're installing packages from pip, may as well just install iso8601 and get the best performance - possibly beating .Net (who knows? as you said, I have a different machine than OP).
- beagle3 10y ago
  The numpy version seems to be about 30 times faster than the iso8601 version - note the result there is in nanosecs, not microsecs like the others.
  - fnord123 10y ago
    Yeah but OP is using pypy and I don't know if numpy works on pypy fully. I think I read it does but I haven't tried it.
x1798DE 10y ago
dateutil spends most of its time inferring the format, it's not really designed as a performance component, it's designed as a "if it looks like a date we'll give you a datetime" style component.