LiNGAM is a causal discovery library that estimates linear Bayesian networks and structural equation models from data by leveraging the non-Gaussianity property of data distributions. It provides DirectLiNGAM and related algorithms for inferring causal ordering and adjacency matrices representing causal relationships. The package integrates with scikit-learn, scipy, and other scientific Python libraries for numerical computation.