make usable scorers backward compatible

Orange/widgets/evaluate/utils.py

@@ -12,7 +12,7 @@
     QSortFilterProxyModel
 from sklearn.exceptions import UndefinedMetricWarning
 
-from Orange.data import Table, DiscreteVariable, ContinuousVariable
+from Orange.data import Table, DiscreteVariable, ContinuousVariable, Variable
 from Orange.evaluation import scoring
 from Orange.widgets import gui
 from Orange.widgets.utils.tableview import table_selection_to_mime_data
@@ -79,17 +79,22 @@ def learner_name(learner):
     return getattr(learner, "name", type(learner).__name__)
 
 
-def usable_scorers(data: Table):
-    if not data:
+def usable_scorers(data_or_var: Union[Table, Variable]):
+    if not data_or_var:
         return []
 
-    problem_type = data.attributes.get("problem_type", None)
-    target = data.domain.class_var
-
     # 'abstract' is retrieved from __dict__ to avoid inheriting
     scorer_candidates = [cls for cls in scoring.Score.registry.values()
                          if cls.is_scalar and not cls.__dict__.get("abstract")]
 
+    data, problem_type = None, None
+    if isinstance(data_or_var, Table):
+        data = data_or_var
+        problem_type = data.attributes.get("problem_type", None)
+        target = data.domain.class_var
+    else:
+        target = data_or_var
+
     # If problem_type is not specified and 'domain.class_var' is set
     # use builtin scorers and don't brake the default behaviour.
     usable = []