causallib and Causalis

These are competitors: causallib offers a mature, modular framework for general causal inference tasks with established adoption, while Causalis targets the same use cases (experiments and observational data) with a specialized focus on robustness, making them alternative choices depending on whether one prioritizes modularity and ecosystem maturity versus robustness guarantees.