Causal-learn: Causal Discovery in Python
Yujia Zheng
Biwei Huang
Wei Chen
Joseph Ramsey
Mingming Gong
Ruichu Cai
Shohei Shimizu
Peter Spirtes
Kun Zhang

Abstract
Causal discovery aims at revealing causal relations from observational data, which is a fundamental task in science and engineering. We describe , an open-source Python library for causal discovery. This library focuses on bringing a comprehensive collection of causal discovery methods to both practitioners and researchers. It provides easy-to-use APIs for non-specialists, modular building blocks for developers, detailed documentation for learners, and comprehensive methods for all. Different from previous packages in R or Java, is fully developed in Python, which could be more in tune with the recent preference shift in programming languages within related communities. The library is available at https://github.com/py-why/causal-learn.
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