Fix remaining errors

Signed-off-by: Gaurav Gupta <gaugup@microsoft.com>

Author: gaugup

tests/test_data_interface/test_public_data_interface.py

@@ -67,16 +67,19 @@ def test_invalid_continuous_features(self, data_type):
         iris = load_iris(as_frame=True)
         dataset = iris.frame
 
+        import re
         if data_type == DataTypeCombinations.Incorrect:
-            with pytest.raises(ValueError) as ve:
+            with pytest.raises(
+                    ValueError,
+                    match=re.escape("should provide the name(s) of continuous features in the data as a list")):
                 dice_ml.Data(dataframe=dataset, continuous_features=np.array(iris.feature_names),
                              outcome_name='target')
-            assert "should provide the name(s) of continuous features in the data as a list" in str(ve)
         elif data_type == DataTypeCombinations.AsNone:
-            with pytest.raises(ValueError) as ve:
+            with pytest.raises(
+                    ValueError,
+                    match=re.escape("should provide the name(s) of continuous features in the data as a list")):
                 dice_ml.Data(dataframe=dataset, continuous_features=None,
                              outcome_name='target')
-            assert "should provide the name(s) of continuous features in the data as a list" in str(ve)
         else:
             with pytest.raises(
                     ValueError,

tests/test_dice_interface/test_dice_KD.py

@@ -54,7 +54,8 @@ def test_invalid_query_instance(self, desired_range, desired_class, sample_custo
         self.exp.dataset_with_predictions, self.exp.KD_tree, self.exp.predictions = \
             self.exp.build_KD_tree(self.data_df_copy, desired_range, desired_class, self.exp.predicted_outcome_name)
 
-        with pytest.raises(ValueError):
+        with pytest.raises(
+                ValueError, match="is outside the permitted range and isn't allowed to vary"):
             self.exp._generate_counterfactuals(query_instance=sample_custom_query_1, total_CFs=total_CFs,
                                                features_to_vary=features_to_vary, permitted_range=permitted_range)
 

tests/test_dice_interface/test_dice_genetic.py

@@ -54,7 +54,9 @@ def test_no_cfs(self, desired_class, sample_custom_query_1, total_CFs):
     @pytest.mark.parametrize(("features_to_vary", "permitted_range", "feature_weights"),
                              [(['Numerical'], {'Categorical': ['b', 'c']}, "inverse_mad")])
     def test_invalid_query_instance(self, sample_custom_query_1, features_to_vary, permitted_range, feature_weights):
-        with pytest.raises(ValueError):
+        with pytest.raises(
+                ValueError,
+                match="is outside the permitted range and isn't allowed to vary"):
             self.exp.setup(features_to_vary, permitted_range, sample_custom_query_1, feature_weights)
 
     # Testing that the features_to_vary argument actually varies only the features that you wish to vary
@@ -112,11 +114,10 @@ def test_permitted_range_categorical(self, desired_class, total_CFs, features_to
 
     # Testing if an error is thrown when the query instance has outcome variable
     def test_query_instance_with_target_column(self, sample_custom_query_6):
-        with pytest.raises(ValueError) as ve:
+        with pytest.raises(
+                ValueError, match="present in query instance"):
             self.exp.setup("all", None, sample_custom_query_6, "inverse_mad")
 
-        assert "present in query instance" in str(ve)
-
     # Testing if only valid cfs are found after maxiterations
     @pytest.mark.parametrize(("desired_class", "total_CFs", "initialization", "maxiterations"),
                              [(0, 7, "kdtree", 0), (0, 7, "random", 0)])

tests/test_dice_interface/test_dice_random.py

@@ -70,7 +70,8 @@ def test_no_cfs(self, desired_class, desired_range, sample_custom_query_1, total
     @pytest.mark.parametrize(("features_to_vary", "permitted_range", "feature_weights"),
                              [(['Numerical'], {'Categorical': ['b', 'c']}, "inverse_mad")])
     def test_invalid_query_instance(self, sample_custom_query_1, features_to_vary, permitted_range, feature_weights):
-        with pytest.raises(ValueError):
+        with pytest.raises(
+                ValueError, match="is outside the permitted range and isn't allowed to vary"):
             self.exp.setup(features_to_vary, permitted_range, sample_custom_query_1, feature_weights)
 
     # Testing that the features_to_vary argument actually varies only the features that you wish to vary

tests/test_model.py

@@ -53,5 +53,7 @@ def test_model_user_validation_model_type(self, create_iris_data):
             dice_ml.Model(model=trained_model, backend='sklearn', model_type='random')
 
     def test_model_user_validation_no_valid_model(self):
-        with pytest.raises(ValueError):
+        with pytest.raises(
+                ValueError,
+                match="should provide either a trained model or the path to a model"):
             dice_ml.Model(backend='sklearn')