diff --git a/emission/storage/timeseries/builtin_timeseries.py b/emission/storage/timeseries/builtin_timeseries.py index 0a09ee3ab..8204b4e29 100644 --- a/emission/storage/timeseries/builtin_timeseries.py +++ b/emission/storage/timeseries/builtin_timeseries.py @@ -461,8 +461,6 @@ def find_entries_count(self, key_list = None, time_query = None, geo_query = Non For key_list = None or empty, total count of all documents are returned considering the matching entries from entire dataset. """ - print("builtin_timeseries.find_entries_count() called") - orig_tsdb = self.timeseries_db analysis_tsdb = self.analysis_timeseries_db diff --git a/emission/tests/modellingTests/TestRunGreedyModel.py b/emission/tests/modellingTests/TestRunGreedyModel.py index 540909b07..263bf3da5 100644 --- a/emission/tests/modellingTests/TestRunGreedyModel.py +++ b/emission/tests/modellingTests/TestRunGreedyModel.py @@ -163,7 +163,8 @@ def test1RoundTripGreedySimilarityBinning(self): origin=self.origin, destination=self.destination ) - prediction, n = eamur.predict_labels_with_n( + + predictions_list = eamur.predict_labels_with_n( user_id = self.user_id, trip_list = [test], model_type=eamumt.ModelType.GREEDY_SIMILARITY_BINNING, @@ -171,7 +172,6 @@ def test1RoundTripGreedySimilarityBinning(self): model_config=greedy_model_config ) - [logging.debug(p) for p in sorted(prediction, key=lambda r: r['p'], reverse=True)] - - self.assertNotEqual(len(prediction), 0, "should have a prediction") - + for prediction, n in predictions_list: + [logging.debug(p) for p in sorted(prediction, key=lambda r: r['p'], reverse=True)] + self.assertNotEqual(len(prediction), 0, "should have a prediction") diff --git a/emission/tests/storageTests/TestSectionQueries.py b/emission/tests/storageTests/TestSectionQueries.py index 0678b2e8e..01c6804c0 100644 --- a/emission/tests/storageTests/TestSectionQueries.py +++ b/emission/tests/storageTests/TestSectionQueries.py @@ -100,7 +100,6 @@ def testCleaned2InferredSectionList(self): # Total = 25 = 10 (UUID1) + 15 (UUID2) curr_predicted_entries = esds.cleaned2inferred_section_list(section_user_list) self.assertEqual(len(curr_predicted_entries), len(sections_entries)) - print(curr_predicted_entries) # Testcase 2: Null user_id value is passed curr_predicted_entries = esds.cleaned2inferred_section_list([{'section' : section_id, 'user_id' : ''}])