fix: add step param to assess view

openassessment/xblock/ui_mixins/mfe/assessment_serializers.py

@@ -232,10 +232,11 @@ class AssessmentSubmitRequestSerializer(MfeAssessmentDataSerializer):
             ...
         ],
         overallFeedback: (String / Empty)
+        step: (String): The step for which we are submitting an assessment
     }
     """
 
-    continueGrading = BooleanField(required=False, default=False)
+    step = CharField()
 
     def to_legacy_format(self, xblock):
         """

openassessment/xblock/ui_mixins/mfe/mixin.py

@@ -290,9 +290,12 @@ def _assessment_submit_handler(self, data):
         if not serializer.is_valid():
             raise OraApiException(400, error_codes.INCORRECT_PARAMETERS, serializer.errors)
         assessment_data = serializer.to_legacy_format(self)
-        peer_data = self.peer_assessment_data(serializer.data['continueGrading'])
+        requested_step = serializer.data['step']
+        peer_data = self.peer_assessment_data()
         try:
-            if peer_data.continue_grading or self.workflow_data.is_peer:
+            if self.workflow_data.is_cancelled:
+                raise InvalidStateToAssess()
+            if requested_step == 'peer':
                 peer_assess(
                     assessment_data['options_selected'],
                     assessment_data['feedback'],
@@ -301,7 +304,7 @@ def _assessment_submit_handler(self, data):
                     self.workflow_data,
                     peer_data,
                 )
-            elif self.workflow_data.is_self:
+            elif requested_step == 'self':
                 self_assess(
                     assessment_data['options_selected'],
                     assessment_data['criterion_feedback'],
@@ -310,7 +313,7 @@ def _assessment_submit_handler(self, data):
                     self.workflow_data,
                     self.self_data
                 )
-            elif self.workflow_data.is_training:
+            elif requested_step == 'studentTraining':
                 corrections = training_assess(
                     assessment_data['options_selected'],
                     self.config_data,
@@ -324,6 +327,7 @@ def _assessment_submit_handler(self, data):
             # This catches the error we explicitly raise, as well as any that may be raised from within
             # the assessment logic itself
             context = {
+                'requested_step': requested_step,
                 'student_item': self.config_data.student_item_dict,
                 'workflow': self.workflow_data.workflow,
             }

openassessment/xblock/ui_mixins/mfe/test_assessment_serializers.py

@@ -468,9 +468,9 @@ def test_assessment_data(self):
                 }
             ],
             "overallFeedback": "Foo",
-            "continueGrading": True,
+            "step": "Wham"
         }).data
 
         self.assertEqual(assessment_submit_request_data["overallFeedback"], "Foo")
         self.assertEqual(len(assessment_submit_request_data["criteria"]), 1)
-        self.assertTrue(assessment_submit_request_data["continueGrading"])
+        self.assertEqual(assessment_submit_request_data["step"], "Wham")

openassessment/xblock/ui_mixins/mfe/test_mfe_mixin.py

@@ -38,6 +38,7 @@
 from openassessment.xblock.test.test_staff_area import NullUserService, UserStateService
 from openassessment.xblock.test.test_submission import COURSE_ID, setup_mock_team
 from openassessment.xblock.test.test_team import MOCK_TEAM_ID, MockTeamsService
+from openassessment.xblock.ui_mixins.mfe.mixin import MFE_STEP_TO_WORKFLOW_MAPPINGS
 from openassessment.xblock.ui_mixins.mfe.constants import error_codes, handler_suffixes
 from openassessment.xblock.ui_mixins.mfe.submission_serializers import DraftResponseSerializer, SubmissionSerializer
 
@@ -150,9 +151,11 @@ def request_file_callback(self, xblock, payload):
             response_format='response'
         )
 
-    def request_assessment_submit(self, xblock, payload=None):
+    def request_assessment_submit(self, xblock, step=None, payload=None):
         if payload is None:
             payload = self.DEFAULT_ASSESSMENT_SUBMIT_VALUE
+        if step is not None:
+            payload['step'] = step
         return super().request(
             xblock,
             'assessment',
@@ -936,6 +939,7 @@ def mock_assess_functions(self, self_kwargs=None, training_kwargs=None, peer_kwa
         {
             'criterionFeedback': {},
             'overallFeedback': '',
+            'step': 'peer'
         },
         {
             'optionsSelected': ['this is a list'],
@@ -949,58 +953,59 @@ def test_incorrect_params(self, xblock, payload):
         assert resp.status_code == 400
         assert resp.json['error']['errorCode'] == error_codes.INCORRECT_PARAMETERS
 
-    @ddt.data(None, 'cancelled', 'done', 'ai')
+    @ddt.data("self", "peer", "studentTraining")
     @scenario("data/basic_scenario.xml")
-    def test_not_allowed_step_error(self, xblock, status):
-        with self.mock_workflow_status(status):
-            resp = self.request_assessment_submit(xblock)
+    def test_not_allowed_to_assess_when_cancelled(self, xblock, step):
+        with self.mock_workflow_status("cancelled"):
+            resp = self.request_assessment_submit(xblock, step=step)
         assert resp.status_code == 400
         assert resp.json['error']['errorCode'] == error_codes.INVALID_STATE_TO_ASSESS
 
     @ddt.unpack
     @ddt.data(
         ('self', True, False, False),
-        ('training', False, True, False),
+        ('studentTraining', False, True, False),
         ('peer', False, False, True)
     )
     @scenario("data/basic_scenario.xml")
-    def test_assess(self, xblock, step, expect_self, expect_training, expect_peer):
-        with self.mock_workflow_status(step):
+    def test_assess(self, xblock, mfe_step, expect_self, expect_training, expect_peer):
+        workflow_step = MFE_STEP_TO_WORKFLOW_MAPPINGS[mfe_step]
+        with self.mock_workflow_status(workflow_step):
             with self.mock_assess_functions() as assess_mocks:
-                resp = self.request_assessment_submit(xblock)
+                resp = self.request_assessment_submit(xblock, step=mfe_step)
         assert resp.status_code == 200
         assert assess_mocks.self.called == expect_self
         assert assess_mocks.training.called == expect_training
         assert assess_mocks.peer.called == expect_peer
 
     @ddt.data(None, 'cancelled', 'waiting', 'self', 'training', 'done')
     @scenario("data/basic_scenario.xml")
-    def test_continue_grading(self, xblock, step):
+    def test_peer_assess_when_not_in_peer(self, xblock, step):
         with self.mock_assess_functions() as assess_mocks:
             with self.mock_workflow_status(step):
-                with self.mock_continue_grading(True):
-                    resp = self.request_assessment_submit(xblock)
+                resp = self.request_assessment_submit(xblock, step="peer")
 
         assert resp.status_code == 200
         assess_mocks.self.assert_not_called()
         assess_mocks.training.assert_not_called()
         assess_mocks.peer.assert_called()
 
-    @ddt.data('self', 'training', 'peer')
+    @ddt.data('self', 'learnerTraining', 'peer')
     @scenario("data/basic_scenario.xml")
-    def test_assess_error(self, xblock, step):
+    def test_assess_error(self, xblock, mfe_step):
         error = AssessmentError("there was a problem")
-        with self.mock_workflow_status(step):
-            with self.mock_assess_functions(**{step + '_kwargs': {'side_effect': error}}):
-                resp = self.request_assessment_submit(xblock)
+        workflow_step = MFE_STEP_TO_WORKFLOW_MAPPINGS[mfe_step]
+        with self.mock_workflow_status(workflow_step):
+            with self.mock_assess_functions(**{workflow_step + '_kwargs': {'side_effect': error}}):
+                resp = self.request_assessment_submit(xblock, step=mfe_step)
         assert_error_response(resp, 500, error_codes.INTERNAL_EXCEPTION, str(error))
 
     @scenario("data/basic_scenario.xml")
     def test_training_assess_corrections(self, xblock):
         corrections = {'ferocity': 'sublime', 'element': 'hydrogen'}
         with self.mock_workflow_status('training'):
             with self.mock_assess_functions(training_kwargs={'return_value': corrections}):
-                resp = self.request_assessment_submit(xblock)
+                resp = self.request_assessment_submit(xblock, step='studentTraining')
 
         assert_error_response(resp, 400, error_codes.TRAINING_ANSWER_INCORRECT, corrections)