valgrind.txt

http://svn.python.org/projects/python/trunk/Misc/README.valgrind
This document describes some caveats about the use of Valgrind with
Python.  Valgrind is used periodically by Python developers to try
to ensure there are no memory leaks or invalid memory reads/writes.

If you don't want to read about the details of using Valgrind, there
are still two things you must do to suppress the warnings.  First,
you must use a suppressions file.  One is supplied in
Misc/valgrind-python.supp.  Second, you must do one of the following:

  * Uncomment Py_USING_MEMORY_DEBUGGER in Objects/obmalloc.c,
    then rebuild Python
  * Uncomment the lines in Misc/valgrind-python.supp that
    suppress the warnings for PyObject_Free and PyObject_Realloc

If you want to use Valgrind more effectively and catch even more
memory leaks, you will need to configure python --without-pymalloc.
PyMalloc allocates a few blocks in big chunks and most object
allocations don't call malloc, they use chunks doled about by PyMalloc
from the big blocks.  This means Valgrind can't detect
many allocations (and frees), except for those that are forwarded
to the system malloc.  Note: configuring python --without-pymalloc
makes Python run much slower, especially when running under Valgrind.
You may need to run the tests in batches under Valgrind to keep
the memory usage down to allow the tests to complete.  It seems to take
about 5 times longer to run --without-pymalloc.
https://blogs.gnome.org/jamesh/2008/03/24/python-valgrind/
 As I don’t like having to recompile Python I took a look at Valgrind’s client API, which provides a way for a program to detect whether it is running under Valgrind. Using the client API I was able to put together a patch that automatically disables pymalloc when appropriate.


http://thomas-cokelaer.info/blog/2013/10/profiling-python-with-valgrind/
pyprof2calltree
python -m cProfile -o profile_data.pyprof run.py
pyprof2calltree -i profile_data.pyprof  # this converts the stats into a callgrind format
kcachegrind profile_data.pyprof.log
Alternatively, for visualisation, you can also use gprof2dot and graphviz (dot):
gprof2dot.py --format=callgrind --output=out.dot profile_data.pyprof.log
dot -Tsvg out.dot -o graph.svg


https://github.com/cython/cython/wiki/UsingValgrindToDebug
Here is a suppression file that you can use with Cython modules: https://github.com/lxml/lxml/raw/master/valgrind-python.supp
valgrind --tool=memcheck --leak-check=full --num-callers=30 --suppressions=valgrind-python.supp python myprogram.py






http://stackoverflow.com/questions/1519276/is-it-normal-that-running-python-under-valgrind-shows-many-errors-with-memory?rq=1