incorporate pieter's feedback

Author: mfeurer

openml/runs/trace.py

@@ -369,6 +369,12 @@ def merge_traces(cls, traces: List['OpenMLRunTrace']) -> 'OpenMLRunTrace':
                                 list(iteration.parameters.keys()),
                             )
                         )
+
+                if key in merged_trace:
+                    raise ValueError(
+                        "Cannot merge traces because key '{}' was encountered twice".format(key)
+                    )
+
                 merged_trace[key] = iteration
                 previous_iteration = key
 

openml/tasks/task.py

@@ -119,6 +119,12 @@ def get_X_and_y(
     ) -> Union[np.ndarray, pd.DataFrame, scipy.sparse.spmatrix]:
         """Get data associated with the current task.
 
+        Parameters
+        ----------
+        dataset_format : str
+            Data structure of the returned data. See :meth:`openml.datasets.OpenMLDataset.get_data`
+            for possible options.
+
         Returns
         -------
         tuple - X and y
@@ -191,6 +197,12 @@ def get_X(
     ) -> Union[np.ndarray, pd.DataFrame, scipy.sparse.spmatrix]:
         """Get data associated with the current task.
 
+        Parameters
+        ----------
+        dataset_format : str
+            Data structure of the returned data. See :meth:`openml.datasets.OpenMLDataset.get_data`
+            for possible options.
+
         Returns
         -------
         tuple - X and y

tests/test_extensions/test_sklearn_extension/test_sklearn_extension.py

@@ -1442,7 +1442,6 @@ def predict_proba(*args, **kwargs):
             np.testing.assert_array_equal(pred_1, pred_2)
             np.testing.assert_array_almost_equal(np.sum(proba_1, axis=1), np.ones(X_test.shape[0]))
             # Test that there are predictions other than ones and zeros
-            print(proba_1, proba_2)
             self.assertLess(
                 np.sum(proba_1 == 0) + np.sum(proba_1 == 1),
                 X_test.shape[0] * len(task.class_labels),