Original fork derived from
https://fedorahosted.org/gdb-heap/. This repo is now considered the official repository for the gdb-heap library.
- To get this module working with Ubuntu 16.04, make sure you have the following packages installed:
sudo apt-get install libc6-dev libc6-dbg python-gi libglib2.0-0-dbg python-ply
The original forked version assumes an "import gdb" module, which resides in
"/usr/share/glib-2.0/gdb" as part of the
libglib2.0-0-dbg package. Earlier versions
of Ubuntu have this library is located in the
There is also a conflict with the python-gobject-2 library, which are deprecated Python bindings for the GObject library. This package installs a glib/ directory inside /usr/lib/python2.7/dist-packages/glib/option.py, which many Gtk-related modules depend. You will therefore need to make sure the sys.path for /usr/share/glib-2.0/gdb is declared first for this reason (see code example).
You'll also want to install python-dbg since the package comes with the debugging symbols for the stock Python 2.7, as well as a python-dbg binary compiled with the --with-pydebug option that will only work with C extensions modules compiled with the /usr/include/python2.7_d headers.
NOTE: The Python binary that accompanies Ubuntu distributions uses link-time optimization compilation. As a result, many of the Python data structures are optimized out and prevent gdb-heap from being able to properly categorize the various data structures. To take advantage of this capability, you will need to download the Python source and recompile without using the -flto option in the CFLAGS/LDFLAGS configuration option. Normally this capability is not used in standard configure so simply compiling it should do the trick. (If you want to have SSL support in this binary, make sure to edit Modules/Setup.dist).
The python-dbg binary is compiled with the Py_TRACE_REFS conditional via the --pydebug which modifies the internal Python data structures and adds two pointers into every base PyObject, preventing previously compiled C extensions to be used. Using your own compiled version of Python is therefore the way to go if you want to take advantage of the categorize features of gdb-heap and/or inspecting the internal memory structures of Python.
- Create a file that will help automate the loading of the gdbheap library:
python import sys sys.path.insert(0, "/usr/share/glib-2.0/gdb") sys.path.append("/usr/share/glib-2.0/gdb") sys.path.append("/home/rhu/projects/gdb-heap") import gdbheap end
To attach to an existing process, you can execute as follows:
sudo gdb -p 7458 -x ~/gdb-heap-commands
To take a core dump of a process, you can do the following:
1) sudo gdb -p <pid> 2) Type "generate-core-file" at the GDB prompt. 3) Wait awhile (and be careful not to hit enter again, since it will repeat the same command) 4) Copy the core.<pid> file somewhere.
You can then use gdb to attach to this core file:
sudo gdb python <core file> -x ~/gdb-heap-commands
Commands to run
heap - print a report on memory usage, by category heap sizes - print a report on memory usage, by sizes heap used - print used heap chunks heap free - print free heap chunks heap all - print all heap chunks heap log - print a log of recorded heap states heap label - record the current state of the heap for later comparison heap diff - compare two states of the heap heap select - query used heap chunks hexdump <addr> [-c] - print a hexdump, stating at the specific region of memory (expose hex characters with -c option) heap arenas - print glibs arenas heap arena <arena> - select glibc arena number
http://blip.tv/pycon-us-videos-2009-2010-2011/pycon-2011-dude-where-s-my-ram-a-deep-dive-into-how-python-uses-memory-4896725 (Dude - Where's My RAM? A deep dive in how Python uses memory - David Malcom's PyCon 2011 video talk)
http://dmalcolm.fedorapeople.org/presentations/PyCon-US-2011/GdbPythonPresentation/GdbPython.html (David Malcom's PyCon 2011 slides)
http://code.woboq.org/userspace/glibc/malloc/malloc.c.html (malloc.c.html implementation)
Malloc per-thread arenas in glibc (http://siddhesh.in/journal/2012/10/24/malloc-per-thread-arenas-in-glibc/)
Understanding the heap by breaking it (http://www.blackhat.com/presentations/bh-usa-07/Ferguson/Whitepaper/bh-usa-07-ferguson-WP.pdf)
Building your own Python version for an easier debugging experience (http://hustoknow.blogspot.com/2014/06/how-to-troubleshoot-your-python.html)