| import json, sys, unittest |
| from pathlib import Path |
| sys.path.insert(0, str(Path(__file__).resolve().parents[1])) |
| import pandas as pd |
| from predict import Predictor |
|
|
| DATA = Path('/nvme0n1-disk/cache/foundry/tabular') |
|
|
|
|
| class T(unittest.TestCase): |
| @classmethod |
| def setUpClass(cls): |
| cls.p = Predictor() |
| cls.p.setup() |
|
|
| def test_all_models(self): |
| for name, target in [('adult', 'class'), ('credit-g', 'class'), ('bank-marketing', 'Class'), |
| ('phoneme', 'Class'), ('diabetes', 'class')]: |
| f = DATA / f'{name}.parquet' |
| if not f.exists(): |
| self.skipTest('dataset cache absent') |
| df = pd.read_parquet(f).drop(columns=[target]).head(5) |
| rows = df.astype(object).where(df.notna(), None).to_json(orient='records') |
| out = json.loads(self.p.predict(name, rows)) |
| self.assertEqual(len(out), 5) |
| self.assertTrue(all(0 <= x <= 1 for x in out)) |
|
|
| def test_errors(self): |
| with self.assertRaises(ValueError): |
| self.p.predict('nope', '[]') |
| with self.assertRaises(ValueError): |
| self.p.predict('adult', '[{"age": 1}]') |
|
|
|
|
| if __name__ == '__main__': |
| unittest.main() |
|
|
