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README.txt
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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.
.. _kcachegrind: http://kcachegrind.sourceforge.net
.. _kcachegrind-converters: http://packages.debian.org/en/stable/kcachegrind-converters
.. _kdesdk: http://websvn.kde.org/trunk/KDE/kdesdk/kcachegrind/converters/
.. _screenshots: http://images.google.fr/images?q=kcachegrind
Command line usage
==================
Upon installation you should 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 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)
.. _ipython: http://ipython.scipy.org
Change log
==========
- 1.3.2 - 2014-07-05: Bugfix: correct source file paths (#12)
- 1.3.1 - 2013-11-27: Bugfix for broken output writing on python 3 (#8)
- 1.3.0 - 2013-11-19: qcachegrind support
- 1.2.0 - 2013-11-09: Python 3 support
- 1.1.1 - 2013-09-25: Miscellaneous bugfixes
- 1.1.0 - 2008-12-21: integrate fix in conversion by David Glick
- 1.0.3 - 2008-10-16: fix typos in 1.0 release
- 1.0 - 2008-10-16: initial release under the pyprof2calltree name