Metadata-Version: 2.4
Name: pythia-anvil
Version: 0.1.0
Summary: Deterministic ML pipeline: profile arbitrary data, pick an OSS model, surface non-obvious insights, reproduce bit-for-bit on the same inputs.
Requires-Python: >=3.11
Requires-Dist: joblib<2.0,>=1.3
Requires-Dist: jsonschema<5,>=4.18
Requires-Dist: numpy<2.0,>=1.26
Requires-Dist: openpyxl<4.0,>=3.1
Requires-Dist: pandas<3.0,>=2.2
Requires-Dist: pyarrow<19.0,>=15.0
Requires-Dist: pyyaml<7,>=6
Requires-Dist: scikit-learn<1.6,>=1.4
Provides-Extra: causal
Requires-Dist: dowhy<0.13,>=0.12; extra == 'causal'
Requires-Dist: networkx<3.4,>=3.1; extra == 'causal'
Provides-Extra: challengers
Requires-Dist: autogluon-tabular<2.0,>=1.5; extra == 'challengers'
Provides-Extra: data-versioning
Requires-Dist: dvc<4.0,>=3.0; extra == 'data-versioning'
Provides-Extra: dev
Requires-Dist: hypothesis>=6.100; extra == 'dev'
Requires-Dist: pytest>=8; extra == 'dev'
Requires-Dist: ruff>=0.5; extra == 'dev'
Provides-Extra: drift
Requires-Dist: evidently<0.5,>=0.4.20; extra == 'drift'
Provides-Extra: insights
Requires-Dist: hdbscan<0.8.40,>=0.8.33; extra == 'insights'
Requires-Dist: pyod<3.0,>=2.0; extra == 'insights'
Requires-Dist: shap<0.55,>=0.45; extra == 'insights'
Requires-Dist: umap-learn<0.5.8,>=0.5.5; extra == 'insights'
Provides-Extra: registry
Requires-Dist: mlflow<3.0,>=2.10; extra == 'registry'
Provides-Extra: training
Requires-Dist: flaml<3.0,>=2.2; extra == 'training'
Requires-Dist: interpret<0.7,>=0.6; extra == 'training'
Requires-Dist: lightgbm<5.0,>=4.0; extra == 'training'
Requires-Dist: xgboost<3.0,>=2.0; extra == 'training'
