test: regression suite for the predict.py rule/computed packs - #49
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Covers the deterministic, model-independent logic so the 🟡 "built but unvalidated" packs in BUILD-STATUS become regression-guarded — and CI actually exercises them: - test_rules: sour/salty calls (incl. MSG defers to the organic anion), allergen labeling, the documented dangerous-mixture screen (nitrite + amine -> nitrosamine). - test_physchem: physchem MW/logP/solubility, stability motif flags (vanillin's phenol + aldehyde), chemesthesis (astringent polyphenol, pungent isothiocyanate). - test_predict: predict() stays well-formed and never crashes with NO trained models (the CI case); bad-SMILES handling; predict_aroma honest placeholder. - test_substitute: graceful with no reference set; correct Tanimoto ranking against a hand-built in-memory index (no data files needed). Infra: requirements.txt (core runtime deps) and CI installs it before pytest, so the suite runs in CI without trained models or datasets. 19 tests, all green. Signed-off-by: Austin L. <86896075+rvnminers-A-and-N@users.noreply.github.com>
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Turns the 🟡 "built but unvalidated" packs in
BUILD-STATUS.mdinto regression-guarded ✅, and makes CI actually run Python tests (it previously only hadruff+ a no-op pytest skip).Coverage (19 tests, all model-independent so they run in CI)
test_rules.py) — sour/salty (incl. MSG deferring to the organic anion, NaCl firing), EU allergen labeling, dangerous-mixture screen (nitrite + secondary amine → nitrosamine), empty-mixture well-formedness.test_physchem.py) — physchem MW/logP/solubility, stability motif flags (vanillin's phenol + aldehyde), chemesthesis (astringent polyphenol, pungent isothiocyanate, silent on plain molecules).test_predict.py) — stays well-formed and never crashes with no trained models (the CI case); rejects bad SMILES;predict_aroma()honest placeholder.test_substitute.py) — graceful with no reference set; correct Tanimoto ranking via a hand-built in-memory index.Infra
requirements.txt— core runtime deps (rdkit, numpy, pandas, scikit-learn, joblib, pyarrow).ci.yml— installsrequirements.txtbeforepytest, so the suite runs without trained models or datasets.Verified locally from the repo root with no models present (mirrors CI): 19 passed,
ruffclean.