Causal-learn: Causal Discovery in Python

Causal discovery aims at revealing causal relations from observational data, which is a fundamental task in science and engineering. We describe causal-learn, 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, causal-learn 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. [abs] [ pdf ][ bib ] [ code ] &copy JMLR 2024. ( edit, beta )

Authors

• Yujia Zheng
• Biwei Huang University of California San Diego
• Wei Chen
• Joseph Ramsey
• Mingming Gong University of Melbourne Mohamed bin Zayed University of Artificial Intelligence
• Ruichu Cai Guangdong University of Technology Peng Cheng Laboratory, Shenzhen, China
• Shohei Shimizu RIKEN The University of Osaka Shiga University
• Peter Spirtes
• Kun Zhang MBZUAI, Abu Dhabi, UAE, Carnegie Mellon University, Pittsburg, USA

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