igraph 1.0 enables fast and robust network analysis across programming languages
Networks or graphs are widely used across the sciences to represent relationships of many kinds. The igraph (https://igraph.org) software library supports graph construction, analysis, and visualisation, combining fast and robust performance with a low entry barrier. igraph pairs a fast core written in C with beginner-friendly interfaces in Python, R, and Mathematica. After twenty years of development, igraph 1.0 has been released, enabling public access to a robust and stable network analysis with over a million monthly downloads. Thanks to its cross-language design, igraph delivers both speed and flexibility: it can handle billions of edges, supports interactive plotting, integrates with notebooks, facilitates conversions to and from other network libraries, includes a rich library of graph layout and community detection algorithms, and has a detailed documentation including non-English translations. Modern testing features such as continuous integration, address sanitizers, stricter typing, and memory-managed vectors have also increased robustness. Hundreds of bug reports have been fixed and a community forum has been opened to connect users and developers. Specific effort has been made to broaden use and community participation by women, non-binary people, and other demographic groups typically underrepresented in open source software.
Authors
- Szabolcs Horvát (ORCID: https://orcid.org/0000-0002-3100-523X)
- Tamás Nepusz (ORCID: https://orcid.org/0000-0002-1451-338X)
- Daniel Noom
- Maëlle Salmon
- Brooke Foucault Welles (ORCID: https://orcid.org/0000-0002-4155-8815)
- Kirill Müller (ORCID: https://orcid.org/0000-0002-1416-3412)
- Vincent Traag (ORCID: https://orcid.org/0000-0003-3170-3879)
- Gábor Csárdi (ORCID: https://orcid.org/0000-0001-7098-9676)
- Fabio Zanini (ORCID: https://orcid.org/0000-0001-7097-8539)
- Michael Antonov
Institutions
- Leiden University (NL)
- Reykjavík University (IS)
- Northeastern University (US)
- University of Applied Sciences Leiden (NL)
- UNSW Sydney (AU)
- PTC (United States) (US)
- Zurich Chamber of Commerce (CH)
- Center for Systems Biology Dresden (DE)
- Hague Institute of Private International and Foreign Law (NL)
Publication Details
- Journal
- PLoS ONE
- Published
- 2026-08-04
- DOI
- https://doi.org/10.1371/journal.pone.0355108
- Citations
- 35
- Primary Topic
- Software System Performance and Reliability
- Type
- article
- Field-Weighted Citation Impact
- 228.26
Funders
- Chan Zuckerberg Initiative