async def record(self, key: str): record = Record(key) db = self.conn # Get features await db.execute("SELECT json FROM ml_data WHERE key=%s", (key, )) dump = await db.fetchone() if dump is not None and dump[0] is not None: record.merge(Record(key, data=json.loads(dump[0]))) await db.execute("SELECT maintained FROM `status` WHERE key=%s", (key, )) maintained = await db.fetchone() if maintained is not None and maintained[0] is not None: record.evaluated({"maintained": str(maintained[0])}) return record
async def record(self, key: str): db = self.parent.db record = Record(key) # Get features features = await db.execute( "SELECT " + ", ".join(self.parent.FEATURE_COLS) + " " "FROM features WHERE key=?", (record.key, ), ) features = await features.fetchone() if features is not None: record.evaluated(features) # Get prediction prediction = await db.execute( "SELECT * FROM prediction WHERE " "key=?", (record.key, )) prediction = await prediction.fetchone() if prediction is not None: record.predicted("target_name", prediction["value"], prediction["confidence"]) return record
class TestRecord(unittest.TestCase): def setUp(self): self.null = Record("null") self.full = Record( "full", data=dict( features=dict(dead="beef"), extra=dict(extra="read all about it"), ), extra=dict(half=True), ) def test_dict(self): data = self.full.dict() self.assertIn("extra", data) def test_repr(self): repr(self.full) def test_str(self): self.full.prediction = RecordPrediction() self.assertIn("Undetermined", str(self.full)) self.full.data.prediction = { "Prediction": RecordPrediction(value="Good") } self.assertIn("Good", str(self.full)) self.full.extra.update(dict(hi=5)) self.assertIn("5", str(self.full)) self.full.extra = dict() self.assertNotIn("5", str(self.full)) def test_merge(self): null = Record("null") null.merge(self.full) self.assertIn("half", null.extra) self.assertTrue(null.extra["half"]) def test_key(self): return self.full.data.key def test_evaluated(self): old_last_updated = self.full.data.last_updated results = {"new": "feature"} self.full.evaluated({"feed": "face"}) self.assertIn("feed", self.full.data.features) self.assertEqual("face", self.full.data.features["feed"]) self.full.evaluated(results, overwrite=True) self.assertEqual(self.full.data.features, results) self.assertLessEqual(old_last_updated, self.full.data.last_updated) def test_features(self): self.assertIn("dead", self.full.features()) self.assertIn("dead", self.full.features(["dead"])) self.assertFalse(self.full.features(["dead", "beaf"])) def test_predicted(self): old_prediction = self.full.data.prediction.copy() old_last_updated = self.full.data.last_updated self.full.predicted("target_name", "feed", 1.00) self.assertNotEqual(old_prediction, self.full.data.prediction) self.assertLessEqual(old_last_updated, self.full.data.last_updated) def test_prediction(self): self.full.predicted("target_name", "feed", 1.00) self.assertTrue(self.full.prediction("target_name"))