Hardening follow-up: N+1 elimination, type validation, diversify fix

Additional fixes from parallel hardening streams:

- exercise/serializers: remove unused WorkoutEquipment import, add prefetch docs
- generator/serializers: N+1 fix in GeneratedWorkoutDetailSerializer (inline workout dict, prefetch-aware supersets)
- generator/services/plan_builder: eliminate redundant .save() after .create() via single create_kwargs dict
- generator/services/workout_generator: proper type-match validation for HIIT/cardio/core/flexibility; fix diversify type count to account for removed entry
- generator/views: request-level caching for get_registered_user helper; prefetch chain for accept_workout
- superset/serializers: guard against dangling FK in SupersetExerciseSerializer
- workout/helpers: use prefetched data instead of re-querying per superset

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

superset/serializers.py

@@ -12,13 +12,26 @@ class SupersetExerciseSerializer(serializers.ModelSerializer):
         fields = '__all__'
 
     def get_exercise(self, obj):
-        data = ExerciseSerializer(obj.exercise, many=False).data
-        return data
+        try:
+            exercise = obj.exercise
+        except (Exercise.DoesNotExist, AttributeError):
+            return None
+        if exercise is None:
+            return None
+        return ExerciseSerializer(exercise, many=False).data
 
     def get_unique_id(self, obj):
         return f"{obj.pk}-{obj.superset_id}" if hasattr(obj, 'superset_id') else str(obj.pk)
 
 class SupersetSerializer(serializers.ModelSerializer):
+    """Serializer for Superset with nested exercises.
+
+    For optimal performance, callers should prefetch related data:
+        Superset.objects.prefetch_related(
+            'superset_exercises__exercise__exercise_muscle_exercise__muscle',
+            'superset_exercises__exercise__workout_exercise_workout__equipment',
+        )
+    """
     exercises = serializers.SerializerMethodField()
 
     class Meta:
@@ -30,5 +43,4 @@ class SupersetSerializer(serializers.ModelSerializer):
             return []
         # Use prefetched data if available via superset_exercises related manager
         objs = obj.superset_exercises.all().order_by('order')
-        data = SupersetExerciseSerializer(objs, many=True).data
-        return data
+        return SupersetExerciseSerializer(objs, many=True).data