Created and maintained by Cameron Davidson-Pilon, lifelines helps researchers answer “how long until something happens?” — whether that’s patient outcomes in cancer studies, subscriber churn, or time to failure in experiments. It’s the go-to Python library for survival analysis, used everywhere from clinical trials to product analytics.
Sustainability Snapshot via Cancer Complexity Toolkit:
- 📚 Strong documentation with README and comprehensive docs and tutorials
🔧 Active development (2,500+ stars, 120+ contributors)
✅ Quality indicators: JOSS Score 0.54 | Almanack 0.55
🌱 Opportunities for growth: Dependency documentation and expanded test coverage
Why this matters: lifelines is a sustainable, community-driven project with a JOSS publication and a “Developing” Almanack grade (0.55). For anyone working with time-to-event data, it’s a reliable, well-documented option in the CCKP toolkit.
📄 Publication: Identification of Immune complement function as a determinant of adverse SARS-CoV-2 infection outcome
