Python profiling

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The Python 2.7 documentation recommends the use of cProfile to profile Python code with reasonnably low overhead: https://docs.python.org/release/2.7/library/profile.html

If you use virtualenv, dont forget to activate it:
$ . bin/activate

How do you launch your script with cProfile enabled ?

$ python -m cProfile -o run.profile myscript.py

The output file (run.profile) will be generated when the execution terminates (including CTRL-C).

How do you analyse the results of your session?

1/ pstats

#!/usr/bin/env python
import pstats
pstats.Stats("run.profile").sort_stats("cumulative", "calls").print_stats()

2/ pyprof2calltree + kcachegrind

$ pip install pyprof2calltree
$ sudo apt-get install kcachegrind (Debian/Ubuntu)
or
$ brew install qcachegrind (OS X with Homebrew)

To launch KCacheGrind on run.profile:

$ pyprof2calltree -i run.profile -k

3/ gprof2dot + graphviz

$ pip install gprof2dot
$ sudo apt-get install graphviz (Debian/Ubuntu)
or
$ brew install graphviz (OS X with Homebrew)

To generate a png from your run.profile:

$ gprof2dot -f pstats run.profile | dot -Tpng -o output.png