pygrank: A Python Package for Graph Node Ranking

TL;DR

pygrank is an open-source Python package that simplifies defining, running, and evaluating graph node ranking algorithms with flexible, backend-agnostic components and extensive testing.

Contribution

It introduces a modular, extensible framework for graph node ranking algorithms with support for multiple computational backends and comprehensive evaluation tools.

Findings

Demonstrates flexibility and ease of use through code examples.

Provides extensive unit-tested components for algorithm development.

Supports multiple backends like numpy, tensorflow, and pytorch.

Abstract

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.