async def test_update(self): key = "1" new_repo = Repo(key, data={"features": {"by_ten": 10}}) async with self.post(f"/source/{self.label}/update/{key}", json=new_repo.dict()) as r: self.assertEqual(await r.json(), OK) self.assertEqual((await self.sctx.repo(key)).feature("by_ten"), 10)
async def update(self, repo: Repo): db = self.conn # Just dump it (if you want a setup the queries easily, then you need to # massage the columns in this table to your liking, and perhaps add more # tables. marshall = json.dumps(repo.dict()) await db.execute( "INSERT INTO ml_data (src_url, json) VALUES(%s, %s) " "ON DUPLICATE KEY UPDATE json = %s", (repo.src_url, marshall, marshall), ) self.logger.debug("updated: %s", marshall) self.logger.debug("update: %s", await self.repo(repo.src_url))
class TestRepo(unittest.TestCase): def setUp(self): self.null = Repo("null") self.full = Repo( "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 = RepoPrediction() self.assertIn("Undetermined", str(self.full)) self.full.data.prediction = RepoPrediction(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 = Repo("null") null.merge(self.full) self.assertIn("half", null.extra) self.assertTrue(null.extra["half"]) def test_src_url(self): return self.full.data.src_url 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.assertNotEqual(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 old_last_updated = self.full.data.last_updated self.full.predicted("feed", 1.00) self.assertNotEqual(old_prediction, self.full.data.prediction) self.assertNotEqual(old_last_updated, self.full.data.last_updated) def test_prediction(self): self.full.predicted("feed", 1.00) self.assertTrue(self.full.prediction())
class TestRepo(unittest.TestCase): def setUp(self): self.null = Repo('null') self.full = Repo('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 = RepoPrediction() self.assertIn('Undetermined', str(self.full)) self.full.data.prediction = RepoPrediction(classification='Good') self.assertIn('Good', str(self.full)) self.full.data.classification = 'Great' self.assertIn('Great', 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 = Repo('null') null.merge(self.full) self.assertIn('half', null.extra) self.assertTrue(null.extra['half']) def test_src_url(self): return self.full.data.src_url 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.assertNotEqual(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 old_last_updated = self.full.data.last_updated self.full.predicted('feed', 1.00) self.assertNotEqual(old_prediction, self.full.data.prediction) self.assertNotEqual(old_last_updated, self.full.data.last_updated) def test_prediction(self): self.full.predicted('feed', 1.00) self.assertTrue(self.full.prediction()) def test_classify(self): self.full.classify('face') self.assertEqual(self.full.data.classification, 'face') def test_classified(self): self.full.classify('') self.assertFalse(self.full.classified()) self.full.classify(True) self.assertTrue(self.full.classified()) def test_classification(self): self.full.classify(True) self.assertTrue(self.full.classification()) self.full.classify('') with self.assertRaisesRegex(ValueError, 'Unclassified'): self.full.classification()