enable exporting only the questions

most to allow importing these for the methodology on the scorecards
site.

crowdsourcer/management/commands/export_marks.py

@@ -44,18 +44,19 @@ def add_arguments(self, parser):
     def write_files(
         self, percent_marks, raw_marks, linear, answers=None, questions=None
     ):
-        df = pd.DataFrame.from_records(percent_marks, index="council")
-        df.to_csv(self.total_scores_file)
+        if not self.questions_only:
+            df = pd.DataFrame.from_records(percent_marks, index="council")
+            df.to_csv(self.total_scores_file)
 
-        df = pd.DataFrame.from_records(raw_marks, index="council")
-        df.to_csv(self.council_section_scores_file)
+            df = pd.DataFrame.from_records(raw_marks, index="council")
+            df.to_csv(self.council_section_scores_file)
 
-        df = pd.DataFrame.from_records(
-            linear,
-            columns=["council", "gss", "section", "score", "max_score"],
-            index="council",
-        )
-        df.to_csv(self.section_scores_file)
+            df = pd.DataFrame.from_records(
+                linear,
+                columns=["council", "gss", "section", "score", "max_score"],
+                index="council",
+            )
+            df.to_csv(self.section_scores_file)
 
         if answers is not None:
             df = pd.DataFrame(answers)
@@ -77,6 +78,8 @@ def handle(
         *args,
         **options,
     ):
+        self.questions_only = questions_only
+
         session_label = options["session"]
         try:
             session = MarkingSession.objects.get(label=session_label)
@@ -92,10 +95,11 @@ def handle(
         raw = []
         percent = []
         linear = []
-
-        scoring = get_scoring_object(session)
+        scoring = {}
 
         if not questions_only:
+            scoring = get_scoring_object(session)
+
             for council, council_score in scoring["section_totals"].items():
 
                 p = {
@@ -136,10 +140,12 @@ def handle(
 
         answer_data = None
         if output_answers or questions_only:
-            answer_data = get_all_question_data(scoring)
+            if not questions_only:
+                answer_data = get_all_question_data(scoring)
 
             questions = (
-                Question.objects.order_by("section__title", "number", "number_part")
+                Question.objects.filter(section__marking_session=session)
+                .order_by("section__title", "number", "number_part")
                 .select_related("section")
                 .all()
             )
@@ -165,7 +171,10 @@ def handle(
                 q_no = question.number_and_part
 
                 max_score = 0
-                if scoring["q_maxes"][section].get(q_no, None) is not None:
+                if (
+                    not questions_only
+                    and scoring["q_maxes"][section].get(q_no, None) is not None
+                ):
                     max_score = scoring["q_maxes"][section][q_no]
 
                 groups = [g.description for g in question.questiongroup.all()]

crowdsourcer/scoring.py

@@ -309,10 +309,13 @@ def get_maxes_for_council(scoring, group, country, council):
             pass
 
         for q in all_exceptions:
-            maxes[section][group] -= scoring["q_maxes"][section][q]
-            weighted_maxes[section][group] -= scoring["q_section_weighted_maxes"][
-                section
-            ][q]
+            try:
+                maxes[section][group] -= scoring["q_maxes"][section][q]
+                weighted_maxes[section][group] -= scoring["q_section_weighted_maxes"][
+                    section
+                ][q]
+            except KeyError:
+                print(f"no question found for exception {section}, {q}")
 
     return maxes, weighted_maxes
 
@@ -535,9 +538,12 @@ def calculate_council_totals(scoring):
 
             weighted_total += weighted_score
 
+        percent_total = 0
+        if scoring["group_maxes"][council_group] > 0:
+            percent_total = round(total / scoring["group_maxes"][council_group], 2)
         totals[council] = {
             "raw_total": total,
-            "percent_total": round(total / scoring["group_maxes"][council_group], 2),
+            "percent_total": percent_total,
             "weighted_total": round(weighted_total, 2),
         }
 
@@ -747,7 +753,11 @@ def get_all_question_data(scoring, response_type="Audit"):
 
         q_data = get_response_data(response, include_name=False, process_links=True)
 
-        max_score = scoring["q_maxes"][section][q_number]
+        try:
+            max_score = scoring["q_maxes"][section][q_number]
+        except (KeyError, TypeError):
+            print(f"No max score found for {section}, {q_number}, setting to 0")
+            max_score = 0
 
         data = [
             response.authority.name,
@@ -762,14 +772,22 @@ def get_all_question_data(scoring, response_type="Audit"):
 
         if response.question.question_type != "negative":
             negative = "No"
-            max_weighted = scoring["q_section_weighted_maxes"][section][q_number]
+            try:
+                max_weighted = scoring["q_section_weighted_maxes"][section][q_number]
+            except (KeyError, TypeError):
+                print(f"No section max weighted for {section}, {q_number}")
+                max_weighted = 0
+
             if q_data[1] == "-":
                 weighted_score = ("-",)
             else:
-                weighted_score = get_weighted_question_score(
-                    q_data[1], max_score, response.question.weighting
-                )
-                weighted_score = round(weighted_score, 2)
+                if max_score > 0:
+                    weighted_score = get_weighted_question_score(
+                        q_data[1], max_score, response.question.weighting
+                    )
+                    weighted_score = round(weighted_score, 2)
+                else:
+                    weighted_score = 0
         else:
             negative = "Yes"
             max_weighted = 0