PYPROF2CALLTREE(1) General Commands Manual PYPROF2CALLTREE(1)

Pyprof2calltree - visualize Python cProfile data in kcachegrind

Script to help visualize profiling data collected with the cProfile Python module with the kcachegrind 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.

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

$ pyprof2calltree --help
usage: pyprof2calltree [-h] [-o output_file_path] [-i input_file_path] [-k]
                       [-r scriptfile [args ...]]
optional arguments:
  -h, --help            show this help message and exit
  -o output_file_path, --outfile output_file_path
                        Save calltree stats to <outfile>
  -i input_file_path, --infile input_file_path
                        Read Python stats from <infile>
  -k, --kcachegrind     Run the kcachegrind tool on the converted data
  -r scriptfile [args ...], --run-script scriptfile [args ...]
                        Name of the Python script to run to collect profiling
                        data


pyprof2calltree is also best used from an interactive Python shell such as the default 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)