. Download - graph-tool: Efficent network analysis with python

logograph-toolEfficient network analysis

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Graph-tool is released under the GPLv3. For general installation instructions, please see the included INSTALL file.


Graph-tool was tested extensively only on GNU/Linux and MacOS X systems, but should also be usable on other systems where the below requirements are met.

  • A C++14 compiler (GCC version 5 or above, or clang version 3.4 or above).
  • The Boost libraries, version 1.54 or above.
  • Python version 2.7, 3 or above.
  • The expat library.
  • The SciPy python module.
  • The Numpy python module, version 1.7 or above.
  • The CGAL C++ geometry library, version 3.5 or above.
  • The sparsehash template library (optional, but recommended).
  • The GTK+ 3, cairomm, pycairo and matplotlib libraries, used for graph drawing (optional).
  • The Graphviz packaged for graph drawing, with the python bindings enabled (optional, deprecated).

Having installed the above dependencies, the module can be compiled in the usual way:

$ ./configure
$ make

After compilation, the module can be installed in the default Python module directory by running:

$ make install

Memory requirements for compilation

Graph-tool requires relatively large amounts of RAM (~3 GB) during compilation, because it uses template metaprogramming extensively. Most compilers are still not not very well optimized for this, which means that even though the program is relatively small, it will still use up lots of RAM during compilation, specially if optimizations are used (and you do want to use them). Below you can see the memory usage during compilation using GCC 5.2.0 and clang 3.7.0, on a 64-bit GNU/Linux system with an Intel(R) Core(TM) i7-5500U CPU @ 2.40GHz.

GCC finishes under 80 minutes, and uses at most slightly below 3 GB. On the other hand, clang takes around 100 minutes, and has a memory use peak around 4 GB.

Parallel algorithms

graph-tool can run several of its algorithms in parallel. It makes use of OpenMP to do this, which provides a straightforward way of converting serial code into parallel code. OpenMP is an extension to the Fortran, C and C++ languages, which uses compiler directives to achieve automated code parallelization. Since it uses compiler directives (#pragma in C/C++), it maintains backwards compatibility with compilers that do not support OpenMP, and the code is then compiled cleanly as regular serial code. Thus, support for parallel code in graph-tool is quite optional. If you wish to enable it, just pass the option "--enable-openmp" to the configure script.

Note for MacOS X users

Although graph-tool is a Python library, it is implemented in C++, and thus has C++ dependencies such as Boost, CGAL and expat, which are not installable via Python-only package management systems such as pip or EasyInstall. Unlike most GNU/Linux distributions, the MacOS X system does not include integrated package management with automated dependency tracking, which means that the dependencies would have to be installed individually by hand. Since they also have their own dependencies, this would trigger the manual installation of many libraries, which is quite time consuming, error-prone and is not recommended for inexperienced users. Instead, the best option is to use one of the third-party package management software available, such as Macports or Homebrew.

Macports allows for the installation of graph-tool with a single command:

port install py-graph-tool

With Homebrew the installation is also straightforward:

brew tap homebrew/science
brew install graph-tool

See below for more notes on installing on MacOS X, as well as the FAQ.

If you encounter an error installing graph-tool via Macports or Homebrew, please file a bug report via each respective project, not to graph-tool directly.

Pre-compiled Packages

Debian & Ubuntu

For Debian, add the following lines to your /etc/apt/sources.list,

deb http://downloads.skewed.de/apt/DISTRIBUTION DISTRIBUTION main
deb-src http://downloads.skewed.de/apt/DISTRIBUTION DISTRIBUTION main

where DISTRIBUTION can be any one of

stretch, sid

For Ubuntu, add the following lines

deb http://downloads.skewed.de/apt/DISTRIBUTION DISTRIBUTION universe
deb-src http://downloads.skewed.de/apt/DISTRIBUTION DISTRIBUTION universe

where DISTRIBUTION can be any one of

wily, xenial, yakkety, zesty

After running apt-get update, the package can be installed with

apt-get install python-graph-tool

or if you want to use Python 3

apt-get install python3-graph-tool

If you want to verify the packages, you should use the public key 612DEFB798507F25, which can be done with the command:

apt-key adv --keyserver pgp.skewed.de --recv-key 612DEFB798507F25

Afterwards, you can run apt-key list, which should give you the following details about the key:

pub   4096R/98507F25 2013-10-17 [expires: 2018-10-16]
uid                  Tiago de Paula Peixoto <tiago@skewed.de>
uid                  Tiago de Paula Peixoto <tiago@itp.uni-bremen.de>
sub   4096R/1A7ECE03 2013-10-17 [expires: 2018-10-16]
sub   4096R/23F08CAF 2013-10-17 [expires: 2018-10-16]


Packages for Arch are available in the Arch User Repository. You can install it with yaourt:

yaourt -S python2-graph-tool


yaourt -S python-graph-tool

depending on the python version.


An ebuild for graph-tool is included in the default Gentoo repository. Just do

emerge graph-tool

to install it.



A portfile is available for installation in MacOS X systems with Macports. It is included in the standard macports list. Just run the following command to install it:

port install py-graph-tool


With Homebrew the installation is also straightforward, since a formula for it is included in the "science" list:

brew tap homebrew/science
brew install graph-tool

Compiler choice in MacOS X

TL;DR : Just use clang for everything.

Make sure you use the same compiler to compile the whole stack (Python, Boost, etc) or you may lead into problems. Since more recent versions of graph-tool, a compiler which supports C++14 is required.

In an ideal world, the correct version should be the latest one from the "stock" FSF GCC, however it does not seem to be very well supported in the platform. The clang compiler seems to be the only viable option on the platform, and should therefore be used.

(If possible, a much better option would be to use a less defective platform in the first place.)

FAQ for installation in MacOS X

Q: Why can't this be installed via pip? Why so complicated?
A: See note for MacOS X users above. The short answer is that it can't be done, since graph-tool depends crucially on some (excellent) C++ libraries such as Boost, which are not installable via pip.
Q: When importing the module, I get the following errors:
ERROR:root:Could not find any typelib for Gtk
ERROR:root:Could not find any typelib for Gdk
ERROR:root:Could not find any typelib for GdkPixbuf
A: Make sure you have XQuartz installed, as well as GTK+ 3 (gtk3 port in Macports).
Q: When attempting to draw a graph to the screen, I get the error:
gi._glib.GError: Couldn't recognize the image file format for file '/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/graph_tool/draw/graph-tool-logo.svg'
Exception AttributeError: "'GraphWindow' object has no attribute 'graph'" in > ignored
A: You probably don't have the standard librsvg library installed. This can be installed with macports as follows:
port install librsvg
Q: I get unresolved symbol errors when importing the module, something like:
>>> import graph_tool
dyld: lazy symbol binding failed: Symbol not found: __ZN5boost6python7objects23register_dynamic_id_auxENS0_9type_infoEPFNSt3__14pairIPvS2_EES5_E
  Referenced from: /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/graph_tool/libgraph_tool_core.so
  Expected in: flat namespace
A: This is due to different flavors of the C++ standard library (libc++ and libstdc++) being used for Boost and graph-tool itself. This is resolved by either compiling everything using clang with c++11 mode activated (which could be cumbersome, since the same would have to be done for everything else which uses Boost), or simply by upgrading to Mavericks or newer (see here for more info).

Git Repository

We use Git for source revision control and code sharing. The whole tree can be checked out with the following command:

git clone https://git.skewed.de/count0/graph-tool.git

For further instructions on how to use Git, see the documentation.

The git public repository can be browsed online here.

The git repository is also mirrored at github.