Abstract
Raphtory is a platform for building and analysing temporal networks. The library includes methods for creating networks from a variety of data sources; algorithms to explore their structure and evolution; and an extensible GraphQL server for deployment of applications built on top. Raphtory's core engine is built in Rust, for efficiency, with Python interfaces, for ease of use. Raphtory is developed by network scientists, with a background in Physics, Applied Mathematics, Engineering and Computer Science, for use across academia and industry.
Summary
Raphtory is an open-source platform for building and analysing temporal (time-evolving) networks. It can ingest data from a range of sources, includes algorithms for exploring a network's structure and how it changes over time, and offers an extensible GraphQL server for deploying applications built on top of it. The core engine is written in Rust for efficiency, with a Python interface for ease of use.
bibtex
@article{steer2024raphtory,
author = {Ben Steer and Naomi A. Arnold and Cheick Tidiane Ba and Renaud Lambiotte and Haaroon Yousaf and Lucas Jeub and Fabian Murariu and Shivam Kapoor and Pedro Rico and Rachel Chan and Louis Chan and James Alford and Richard G. Clegg and Felix Cuadrado and Matthew Russell Barnes and Peijie Zhong and John Pougu{\'e}-Biyong and Alhamza Alnaimi},
title = {Raphtory: The Temporal Graph Engine for Rust and Python},
journal = {Journal of Open Source Software},
year = {2024},
volume = {9},
number = {95},
doi = {10.21105/joss.05940}
}
Authors
Ben Steer, Naomi A. Arnold, Cheick Tidiane Ba, Renaud Lambiotte, Haaroon Yousaf, Lucas Jeub, Fabian Murariu, Shivam Kapoor, Pedro Rico, Rachel Chan, Louis Chan, James Alford, Richard G. Clegg, Felix Cuadrado, Matthew Russell Barnes, Peijie Zhong, John Pougué-Biyong, Alhamza Alnaimi
Venue
Journal of Open Source Software