Heap Analyzer for Python
Python Shell
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.

README.md

gdb-heap

Original fork derived from https://fedorahosted.org/gdb-heap/. This repo is now considered the official repository for the gdb-heap library.

Installation instructions

  1. 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 ibglib2.0-dev package.

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.

  1. Create a file that will help automate the loading of the gdbheap library:

gdb-heap-commands:

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

Useful resources