Graph module reccomendations?

1

NetworkX

Networkx: Easily the easiest library to use. It's written in Python and by far and away the most Pythonic. It's extremely well documented and there's a robust community that uses it. Unfortunately, because it's written in Python (with bells and whistles from Numpy and Scipy) it inherits a lot of Python's limitations: namely that it is slow as all get-out. Python is particularly bad when nested loops are involved, which is terrible in graph analysis, since many measures need to be brute-forced by iterating over all nodes, edges, paths, etc. Doesn't work well for large networks (large here being 500+ nodes).

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2

graph-tool

Graph-tool: This is the one I use the least, although it is probably one of the most powerful. It lets you quickly run advanced community detection analyses like stochastic block models, hierarchical partitions, etc. It also has a fantastic visualization suite for making gorgeous figures. It used to be a pain in the ass to compile, which is why I ended up sinking the time into igraph, although I understand that it's gotten easier recently and now conda will do all the hard stuff for you.

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