pygrank: A Python Package for Graph Node Ranking
This provides a software tool for researchers and practitioners working with graph node ranking, but it is incremental as it packages existing methods rather than introducing new algorithms.
The authors introduced pygrank, an open-source Python package for implementing and evaluating graph node ranking algorithms, demonstrating its flexibility and ease of use through comparisons with alternatives and code examples.
We introduce pygrank, an open source Python package to define, run and evaluate node ranking algorithms. We provide object-oriented and extensively unit-tested algorithm 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 and demonstrate its flexibility and ease of use with code examples.