Change the behavior of all the getters in the public API when the corresponding key is not found

Instead of raising a KeyError, a ``None`` value is returned (like the dict behavior)

Author: Thierry RAMORASOAVINA

CHANGELOG.md

@@ -15,6 +15,11 @@
 - (`core`) New way to add a variable to a dictionary using a complete specification.
 - (`sklearn`) `Text` Khiops type support at the estimator level.
 
+### Changed
+- (`core`) Dictionary API and analysis and coclustering reports, 
+  when a requested key is not found in getters, return a ``None`` value instead
+  of raising a `KeyError` exception.
+
 ### Fixed
 - (General) Inconsistency between the `tools.download_datasets` function and the
   current samples directory according to `core.api.get_samples_dir()`.

khiops/core/analysis_results.py

@@ -576,13 +576,9 @@ def get_variable_statistics(self, variable_name):
         -------
         `VariableStatistics`
             The statistics of the specified variable.
-
-        Raises
-        ------
-        `KeyError`
-            If no variable with the specified names exist.
+            A ``None`` value is returned if the variable name is not found.
         """
-        return self._variables_statistics_by_name[variable_name]
+        return self._variables_statistics_by_name.get(variable_name)
 
     def get_tree(self, tree_name):
         """Returns the tree with the specified name
@@ -596,13 +592,9 @@ def get_tree(self, tree_name):
         -------
         `Tree`
             The tree which has the specified name.
-
-        Raises
-        ------
-        `KeyError`
-            If no tree with the specified name exists.
+            A ``None`` value is returned if the tree name is not found.
         """
-        return self._trees_by_name[tree_name]
+        return self._trees_by_name.get(tree_name)
 
     def to_dict(self):
         """Transforms this instance to a dict with the Khiops JSON file structure"""
@@ -1045,15 +1037,12 @@ def get_variable_pair_statistics(self, variable_name_1, variable_name_2):
         -------
         `VariablePairStatistics`
             The statistics of the specified pair of variables.
-
-        Raises
-        ------
-        `KeyError`
-            If no pair with the specified names exist.
+             A ``None`` value is returned if no pair with the
+             specified names exist.
         """
-        return self._variables_pairs_statistics_by_name[
+        return self._variables_pairs_statistics_by_name.get(
             (variable_name_1, variable_name_2)
-        ]
+        )
 
     def to_dict(self):
         """Transforms this instance to a dict with the Khiops JSON file structure"""
@@ -1307,13 +1296,9 @@ def get_predictor(self, predictor_name):
         -------
         `TrainedPredictor`
             The predictor object for the specified name.
-
-        Raises
-        ------
-        `KeyError`
-            If there is no predictor with the specified name.
+            A ``None`` value is returned if the predictor name is not found.
         """
-        return self._trained_predictors_by_name[predictor_name]
+        return self._trained_predictors_by_name.get(predictor_name)
 
     def get_snb_predictor(self):
         """Returns the Selective Naive Bayes predictor
@@ -1322,11 +1307,8 @@ def get_snb_predictor(self):
         -------
         `TrainedPredictor`
             The predictor object for "Selective Naive Bayes".
-
-        Raises
-        ------
-        `KeyError`
-            If there is no predictor named "Selective Naive Bayes".
+            A ``None`` value is returned
+            if there is no predictor named "Selective Naive Bayes".
         """
         return self.get_predictor("Selective Naive Bayes")
 
@@ -1589,13 +1571,9 @@ def get_predictor_performance(self, predictor_name):
         -------
         `PredictorPerformance`
             The performance metrics for the specified predictor.
-
-        Raises
-        ------
-        `KeyError`
-            If no predictor with the specified name exists.
+            A ``None`` value is returned if the predictor name is not found.
         """
-        return self._predictors_performance_by_name[predictor_name]
+        return self._predictors_performance_by_name.get(predictor_name)
 
     def get_snb_performance(self):
         """Returns the performance metrics for the Selective Naive Bayes predictor
@@ -1625,21 +1603,20 @@ def get_regressor_rec_curve(self, regressor_name):
         Returns
         -------
         `PredictorCurve`
-            The REC curve for the specified regressor.
+            The REC curve for the specified regressor. A ``None`` value is
+            returned if the regressor name is not found.
 
         Raises
         ------
         `ValueError`
-            If no regressor curves available. (
-        `KeyError`
-            If no regressor with the specified name exists.
+            If no regressor curves available.
         """
         if self.learning_task != "Regression analysis":
             raise ValueError("REC curves are available only for regression")
         for curve in self.regression_rec_curves:
             if curve.name == regressor_name:
                 return curve
-        raise KeyError(regressor_name)
+        return None
 
     def get_snb_rec_curve(self):
         """Returns the REC curve for the Selective Naive Bayes regressor
@@ -1675,11 +1652,8 @@ def get_classifier_lift_curve(self, classifier_name, target_value):
         -------
         `PredictorCurve`
             The lift curve for the specified classifier and target value.
-
-        Raises
-        ------
-        `KeyError`
-            If no classifier with the specified exists or no target value with the
+            A ``None`` value is returned
+            if no classifier with the specified exists or no target value with the
             specified name exists.
         """
         if self.learning_task != "Classification analysis":
@@ -1701,8 +1675,7 @@ def get_classifier_lift_curve(self, classifier_name, target_value):
                     for lift_curve in self.classification_lift_curves[i]:
                         if lift_curve.name == classifier_name:
                             return lift_curve
-                    raise KeyError(classifier_name)
-        raise KeyError(target_value)
+        return None
 
     def get_snb_lift_curve(self, target_value):
         """Returns lift curve for the Selective Naive Bayes clf. given a target value
@@ -1716,14 +1689,8 @@ def get_snb_lift_curve(self, target_value):
         -------
         `PredictorCurve`
             The lift curve of the Selective Naive Bayes classifier for the specified
-            target value.
-
-        Raises
-        ------
-        `ValueError`
-            If the Selective Naive Bayes classifier information is not available.
-        `KeyError`
-            If no target value with the specified name exists.
+            target value. A ``None`` value is returned if no Selective Naive Bayes
+            classifier information is available.
         """
         if self.learning_task != "Classification analysis":
             raise ValueError("Lift curves are available only for classification")
@@ -1732,10 +1699,7 @@ def get_snb_lift_curve(self, target_value):
                 for lift_curve in self.classification_lift_curves[i]:
                     if lift_curve.name == "Selective Naive Bayes":
                         return lift_curve
-                raise ValueError(
-                    "Selective Naive Bayes classifier information not available"
-                )
-        raise KeyError(target_value)
+        return None
 
     def to_dict(self):
         """Transforms this instance to a dict with the Khiops JSON file structure"""

khiops/core/coclustering_results.py

@@ -479,14 +479,10 @@ def get_dimension(self, dimension_name):
         Returns
         -------
         `CoclusteringDimension`
-            The specified dimension.
-
-        Raises
-        ------
-        `KeyError`
-            If no dimension with the specified names exist.
+            The specified dimension. A ``None`` value is returned
+            if the dimension name is not found.
         """
-        return self._dimensions_by_name[dimension_name]
+        return self._dimensions_by_name.get(dimension_name)
 
     def to_dict(self):
         """Transforms this instance to a dict with the Khiops JSON file structure"""
@@ -1062,14 +1058,10 @@ def get_part(self, part_name):
         Returns
         -------
         `CoclusteringDimensionPart`
-            The part with the specified name.
-
-        Raises
-        ------
-        `KeyError`
-            If there is no part with the specified name.
+            The part with the specified name. A ``None`` value is returned
+            if the part name is not found.
         """
-        return self._parts_by_name[part_name]
+        return self._parts_by_name.get(part_name)
 
     def get_cluster(self, cluster_name):
         """Returns the specified cluster
@@ -1082,14 +1074,10 @@ def get_cluster(self, cluster_name):
         Returns
         -------
         `CoclusteringCluster`
-            The specified cluster.
-
-        Raises
-        ------
-        `KeyError`
-            If there is no cluster with the specified name.
+            The specified cluster. A ``None`` value is returned
+            if the cluster name is not found.
         """
-        return self._clusters_by_name[cluster_name]
+        return self._clusters_by_name.get(cluster_name)
 
     def to_dict(self, report_type):
         """Transforms this instance to a dict with the Khiops JSON file structure