make test_evaluation_functions run in parallel

Author: mfeurer

openml/evaluations/functions.py

@@ -32,8 +32,7 @@ def list_evaluations(function, offset=None, size=None, id=None, task=None, setup
 
         Returns
         -------
-        list
-            List of found evaluations.
+        dict
         """
 
     api_call = "evaluation/list/function/%s" %function

tests/test_evaluations/test_evaluation_functions.py

@@ -3,6 +3,7 @@
 from openml.testing import TestBase
 
 class TestEvaluationFunctions(TestBase):
+    _multiprocess_can_split_ = True
 
     def test_evaluation_list_filter_task(self):
         openml.config.server = self.production_server
@@ -15,7 +16,6 @@ def test_evaluation_list_filter_task(self):
         for run_id in evaluations.keys():
             self.assertEquals(evaluations[run_id].task_id, task_id)
 
-
     def test_evaluation_list_filter_uploader(self):
         openml.config.server = self.production_server
 
@@ -24,11 +24,8 @@ def test_evaluation_list_filter_uploader(self):
         evaluations = openml.evaluations.list_evaluations("predictive_accuracy", uploader=[uploader_id])
 
         self.assertGreater(len(evaluations), 100)
-        # for run_id in evaluations.keys():
-        #     self.assertEquals(evaluations[run_id].uploader, uploader_id)
-
 
-    def test_evaluation_list_filter_uploader(self):
+    def test_evaluation_list_filter_uploader_2(self):
         openml.config.server = self.production_server
 
         setup_id = 10
@@ -39,7 +36,6 @@ def test_evaluation_list_filter_uploader(self):
         for run_id in evaluations.keys():
             self.assertEquals(evaluations[run_id].setup_id, setup_id)
 
-
     def test_evaluation_list_filter_flow(self):
         openml.config.server = self.production_server
 
@@ -51,7 +47,6 @@ def test_evaluation_list_filter_flow(self):
         for run_id in evaluations.keys():
             self.assertEquals(evaluations[run_id].flow_id, flow_id)
 
-
     def test_evaluation_list_filter_run(self):
         openml.config.server = self.production_server
 
@@ -63,9 +58,8 @@ def test_evaluation_list_filter_run(self):
         for run_id in evaluations.keys():
             self.assertEquals(evaluations[run_id].run_id, run_id)
 
-
     def test_evaluation_list_limit(self):
         openml.config.server = self.production_server
 
         evaluations = openml.evaluations.list_evaluations("predictive_accuracy", size=100, offset=100)
-        self.assertEquals(len(evaluations), 100)
+        self.assertEquals(len(evaluations), 100)