pyprof2calltree 1.0

Overview

Script to help visualize profiling data collected with the cProfile python module with the kcachegrind (screenshots) graphical calltree analyser.

This is a rebranding of the venerable http://www.gnome.org/~johan/lsprofcalltree.py script by David Allouche et Al. It aims at making it easier to distribute (e.g. through pypi) and behave more like the scripts of the debian kcachegrind-converters package. The final goal is to make it part of the official upstream kdesdk package.

Authors

• David Allouche (original author)

• Jp Calderone

• Itamar Shtull-Trauring

• Johan Dahlin

• Olivier Grisel (repackaging and pstats support)

Command line usage

Upon installation you shoould have a pyprof2calltree script in your path:

$ pyprof2calltree --help
Usage: /usr/bin/pyprof2calltree [-k] [-o output_file_path] [-i input_file_path] [-r scriptfile [args]]

Options:
  -h, --help            show this help message and exit
  -o OUTFILE, --outfile=OUTFILE
                        Save calltree stats to <outfile>
  -i INFILE, --infile=INFILE
                        Read python stats from <infile>
  -r SCRIPT, --run-script=SCRIPT
                        Name of the python script to run to collect profiling
                        data
  -k, --kcachegrind     Run the kcachegrind tool on the converted data

Python shell usage

pyprof2calltree is also best used from an interactive python shell such as the defaulft shell. For instance let us profile XML parsing:

>>> from xml.etree import ElementTree
>>> from cProfile import Profile
>>> xml_content = '<a>\n' + '\t<b/><c><d>text</d></c>\n' * 100 + '</a>'
>>> profiler = Profile()
>>> profiler.runctx(
...     "ElementTree.fromstring(xml_content)",
...     locals(), globals())

>>> from pyprof2calltree import convert, visualize
>>> visualize(profiler.getstats())                            # run kcachegrind
>>> convert(profiler.getstats(), 'profiling_results.kgrind')  # save for later

or with the ipython:

In [1]: %doctest_mode
Exception reporting mode: Plain
Doctest mode is: ON

>>> from xml.etree import ElementTree
>>> xml_content = '<a>\n' + '\t<b/><c><d>text</d></c>\n' * 100 + '</a>'
>>> %prun -D out.stats ElementTree.fromstring(xml_content)

*** Profile stats marshalled to file 'out.stats'

>>> from pyprof2calltree import convert, visualize
>>> visualize('out.stats')
>>> convert('out.stats', 'out.kgrind')

>>> results = %prun -r ElementTree.fromstring(xml_content)
>>> visualize(results)

Change log

• 1.0 - 2008-10-16: initial release under the pyprof2calltree name