reedkotler/graph-tool-install.adoc

## graph-tool-install.adoc

      
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    Installing graph-tool from source with Anaconda


System


OS

Arch Linux 4.9.11 x86_64

Python Distribution

Anaconda Python 3 https://www.continuum.io/downloads#linux


These installation instructions are adapted from the official ones at
https://git.skewed.de/count0/graph-tool/wikis/installation-instructions,
to match the requirements of an Anaconda distribution.


Requirements


GCC (latest version, 6.3.1 for me)


Boost libraries


Python 3.6


The expat XML library


Scipy


Numpy


CGAL C++ library


sparsehash (optional)


cairomm, matplotlib (optional, for plotting)


These packages must be installed via conda and via your package
manager (pacman for Arch), in order to satisfy dependencies at build
time. For Arch, run:


pacman -S clang boost expat cgal sparsehash cairomm


For other distributions, you should find similar packages from your
standard repositories.


Note


Do not use another compiler! You have to use the same compiler
as the one used to compile the Boost library on your system, and that
is very probably GCC.


Installation steps


First, if you don’t have Anaconda, install it by running the
official installer. By default, it installs to
/home/user/anaconda3. We will keep the assumption that the default
wasn’t changed.


Create a conda environment for graph-tool and activate it:


conda create -n graph
source activate graph


Install the required libraries:


conda install -c conda-forge python boost scipy numpy expat cgal
conda install -c conda-forge sparsehash
conda install -c conda-forge cairomm matplotlib


Note


We use the community conda-forge channel, because packages
tend to be more up-to-date compared to the official channel.


Download graph-tool from the official website
(https://graph-tool.skewed.de/), version 2.21 at the time of
writing. Decompress it.


cd ~/builds
tar xjvf graph-tool-2.21.tar.bz2
cd graph-tool-2.21


Compile


./configure --prefix=/home/dimitri/anaconda3/envs/graph/ --with-python-module-path=/home/dimitri/anaconda3/envs/graph/lib/python3.6/site-packages
make -j2
make install


If you have changed the name of the environment, adapt the paths
provided to ./configure.


Note


Adapt the -j2 parameter to your system’s number of cores, but
more importantly, to your available memory. Compilation uses a lot
of memory, and you will run quickly into an internal compiler error
if you parallelize too much. To remain conservative, use -j1 or add
some swap. Compilation may be very long (approx. 1 hour on my system).


Final touches: install jupyter to have all the usual tools from
the Anaconda distribution.


conda install -c conda-forge jupyter


Testing


Deactivate and reactivate your conda environment (so that your PATH is updated):


source deactivate
source activate graph


Open a Jupyter console session


jupyter console


Inside the console, run:


from graph_tool.all import *

g = Graph()
v1 = g.add_vertex()
v2 = g.add_vertex()
e = g.add_edge(v1, v2)
v1.out_degree()


Issues


All packages come with OpenBLAS instead of MKL. This is not optimal
if you have an Intel CPU, as MKL is usually way faster. I think that
this is due to conda-forge, as Continuum probably have an
agreement with Intel regarding the MKL license.


You can not use graph-tool builtin plotting capabilities, as
pycairo was not installed.


If you manage to solve any of this, please let me know!