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A local-first workflow engine built the way it should be: declarative, file-based, self-contained, air-gapped ready. One binary that scales from laptop to distributed cluster. Your Workflow Operator handles creating and debugging workflows.
Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.
Directed Acyclic Graphs with a variety of methods for both Nodes and Edges, and multiple exports (NetworkX, Pandas, etc). This project is the foundation for a commercial product, so expect regular improvements. PR's and other contributions are welcomed.