Python Toolkit for Causal and Probabilistic Reasoning
github.com/pgmpy/pgmpyIndexed at bef9a8bUp to date with upstream
672 files and 4,222 symbols in 3 modules, led by Python (625 files) and Makefile (1).
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Code health
This codebase scores 6.2 out of 10 for code health, which we rate fair. It also scores maintainability 8.0 and static performance 9.9 out of 10. The three are scored separately and never blended into one number. Risk is concentrated, as it usually is: 46 of 672 files are git hotspots, and they average 4.1 — which is where the fixes pay off most.
On the leaderboards:#35 of 44 Python repos
4 things worth doing this quarter.
Break up _fit (CCN 58, 192 lines)
pgmpy/causal_discovery/GES.py:386
_fit nests its control flow deeply, and part of it is duplicated, so splitting it also removes a copy; 4 files import it, changed 6 times in 90 days.
Flatten the nesting in simulate
pgmpy/models/DiscreteBayesianNetwork.py:1620
simulate nests its control flow deeply, and part of it is duplicated, so splitting it also removes a copy; 62 files import it.
Delete 316 unused symbols and files (5,430 lines)
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[](https://repowise.dev/repo/pgmpy/pgmpy?src=badge_card)Python Toolkit for Causal and Probabilistic Reasoning This page is a map of the pgmpy/pgmpy repository, written primarily in Python, rebuilt from the source each time it is indexed. Repowise parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the architectural decisions into documentation you can read here or query through MCP.
The codebase has 672 files and 4,222 symbols in 3 modules, led by Python, Makefile and R. Code health is 6.2 out of 10, rated fair.
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