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Hi Thanks for the reply. kcachegrind uses cProfile, so not overly useful for what I want to do Thanks Matt ________________________________ From: Nick Papior <nickpapior@xxxxxxxxx> Sent: 09 May 2016 11:46 To: Matthew Jones Cc: netcdfgroup@xxxxxxxxxxxxxxxx Subject: Re: [netcdfgroup] Fw: Profiling NetCDF4-python Have you tried: https://docs.python.org/2/library/profile.html 26.4. The Python Profilers - Python 2.7.11 documentation<https://docs.python.org/2/library/profile.html> docs.python.org 26.4.1. Introduction to the profilers¶ cProfile and profile provide deterministic profiling of Python programs. A profile is a set of statistics that describes how ... It usually works quite well for simple profiling. 2016-05-09 12:35 GMT+02:00 Matthew Jones <M.Jones3@xxxxxxxxxxxxxxxxx<mailto:M.Jones3@xxxxxxxxxxxxxxxxx>>: Hi I am trying to profile my NetCDF4-python code to see how to improve read performance, which I have identified as the bottleneck. I have done this using kcachegrind and line_profiler. I want to delve a bit deeper into the library to see where the performance is dropping. I can't work out how to use line_profiler with the @profile decorator in the variable class. I also can't work out how to get kcachegrind to delve into the library because the slicing syntax var[...] is not an explicit function call, and I can't get var.__getitem__() to do the same thing. Does anyone have any ideas how I could get more information from profiling the netcdf4 library? Many thanks Matt ---------------------------------------- Matthew Jones PhD Student Atmosphere, Oceans and Climate Department of Meteorology, University of Reading Room 288, ESSC, Harry Pitt Building, 3 Earley Gate, Reading, RG6 6AL, UK https://www.linkedin.com/pub/matthew-jones/8b/b81/25a http://www.met.reading.ac.uk/users/users/1887 _______________________________________________ NOTE: All exchanges posted to Unidata maintained email lists are recorded in the Unidata inquiry tracking system and made publicly available through the web. Users who post to any of the lists we maintain are reminded to remove any personal information that they do not to be made public. netcdfgroup mailing list netcdfgroup@xxxxxxxxxxxxxxxx<mailto:netcdfgroup@xxxxxxxxxxxxxxxx> For list information or to unsubscribe, visit: http://www.unidata.ucar.edu/mailing_lists/ -- Kind regards Nick
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