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Complex Network Analysis in Python by Dmitry Zinoviev

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Appreciate the Power of graph-tool

graph-tool developers position the module as having “a level of performance that is comparable (both in memory usage and computation time) to that of a pure C/C++ library.”[14] Just like in the case of iGraph, the performance boost comes from implementing the whole module in C/C++.

Once successfully installed, graph-tool shines. For starters, it is based on the OpenMP protocol that supports shared memory multiprocessing programming.[15] A graph-tool program is capable of using all CPUs and cores available to your system. Many CNA tasks (such as PageRank and betweenness calculation) are easily parallelizable: they can be split into N subtasks, so that each one is executed by a CPU or core, reducing the total ...

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