Journal article Open Access
Emmanouil Krasanakis; Symeon Papadopoulos; Ioannis Kompatsiaris; Andreas Symeonidis
We introduce pygrank, an open source Python package to define, run and evaluate node ranking algorithms. We provide object-oriented and extensively unit-tested algorithmic components, such as graph filters, post-processors, measures, benchmarks, and online tuning. Computations can be delegated to numpy, tensorflow, or pytorch backends and fit in back-propagation pipelines. Classes can be combined to define interoperable complex algorithms. Within the context of this paper, we compare the package with related alternatives, describe its architecture, demonstrate its flexibility and ease of use with code examples, and discuss its impact.
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