Lea 3.4.1 is now released! ---> https://pypi.org/project/lea/ What is Lea? ------------ Lea is a Python module for playing with discrete probability distributions in an intuitive way. This ranges from simple dice, coin flipping, random sampling . to Bayesian networks, Probabilistic Programming (PP), machine learning and symbolic computation. One salient feature of Lea is the ability to change the probability representation, viz. float, fractions, decimals, and symbols. Lea can be used for education, AI, PP, etc. Comprehensive tutorials are available online (see Wiki pages). For a 5 minutes tour, check out the poster presented at PROBPROG2020 conference: https://probprog.cc/2020/assets/posters/fri/69.pdf What's new in Lea 3.4.1? ------------------------ 1) Reading BIF files (Bayesian Interchange Format): https://bitbucket.org/piedenis/lea/wiki/Lea3_Tutorial_2 2) Misc corrections on Markov chain advanced functions (repair dependencies): https://bitbucket.org/piedenis/lea/issues/63/ 3) Enhance the test suite, especially for information theory To learn more... ---------------- Lea on PyPI -> http://pypi.org/project/lea Lea project page -> http://bitbucket.org/piedenis/lea Documentation -> http://bitbucket.org/piedenis/lea/wiki/Home With the hope that Lea can make this universe less random (or more?), Pierre Denis