Gustav, I also had to do a comparison of networkx and igraph. I really
like both projects and think they are both suitable for many
overlapping problems. I did some simple benchmarks an found that
igraph would out-perform networkx for simple metrics for larger
graphs; for example on some test graphs networkx took 8x as long to
calculate betweenness centrality. This makes sense as it is built in C
and the Python part is simply an interface to the underlying data
structures. Although, networkx had some features that igraph did not
have for some time; for example using weights in certain calculations.
Both communities are strong and both have really good project leaders
who are involved and responsive. Both are under active development as
well. In all, I really don't see there being an issue with using both
libraries. They both import and export in GraphML, so applying both
wouldn't be a big deal. I also really like the idea that there are 2
great libraries under active development because I can validate
results from one library with the other.