Adjustment

app/utils.py

@@ -995,8 +995,10 @@ def get_user_life_status(user_id):
             "relationship": user.relationship_score
     }
 
+    logger.info(f"{user.score_history}",extra={'user_id': user_id, 'endpoint': function_name})
+
     # Get current life score
-    if len(user.score_history)==0:
+    if len(user.score_history) == 0:
         thirtydays_life_score = cumulative_life_score
     else:
         # Calculate previous 30 days date
@@ -1004,22 +1006,48 @@ def get_user_life_status(user_id):
         thirty_days_ago = now - pd.Timedelta(days=30)
 
         # Filter the data
-        filtered_data = [entry for entry in user.score_history if thirty_days_ago <= entry["created_at"] <= now] 
+        filtered_data = [entry for entry in user.score_history if thirty_days_ago <= entry["created_at"] <= now]
+        logger.info(f"Filtered Data: {filtered_data}", extra={'user_id': user_id, 'endpoint': function_name})
+
+        # Normalize area names to match expected keys
+        area_mapping = {
+            "Personal Growth": "personal_growth",
+            "Health and Wellness": "health_and_wellness",
+            "Mental Well-being": "mental_well_being",
+            "Career Growth": "career_growth",
+            "Relationship": "relationship"
+        }
+
+        # Normalize area names in filtered data
+        for entry in filtered_data:
+            entry["area"] = area_mapping.get(entry["area"], entry["area"])
 
         # Sum points_added, group by area
         temp_df = pd.DataFrame(filtered_data)
         grouped_points = temp_df.groupby("area")["points_added"].sum()
 
-        # Structure the output
+        # Debug: Check the grouped points result
+        logger.info(f"Grouped Points: {grouped_points}", extra={'user_id': user_id, 'endpoint': function_name})
+
+        # Structure the output safely
         thirtydays_life_score = {
-            "overall": grouped_points.get("Personal Growth", 0) + grouped_points.get("Career Growth", 0) + grouped_points.get("Health and Wellness", 0) + grouped_points.get("Mental Well-being", 0) + grouped_points.get("Relationship", 0),
-            "personal_growth": grouped_points.get("Personal Growth", 0),
-            "health_and_wellness": grouped_points.get("Health and Wellness", 0),
-            "mental_well_being": grouped_points.get("Mental Well-being", 0),
-            "career_growth": grouped_points.get("Career Growth", 0),
-            "relationship": grouped_points.get("Relationship", 0)
+            "overall": sum([
+                grouped_points.get("personal_growth", 0),
+                grouped_points.get("career_growth", 0),
+                grouped_points.get("health_and_wellness", 0),
+                grouped_points.get("mental_well_being", 0),
+                grouped_points.get("relationship", 0),
+            ]),
+            "personal_growth": grouped_points.get("personal_growth", 0),
+            "health_and_wellness": grouped_points.get("health_and_wellness", 0),
+            "mental_well_being": grouped_points.get("mental_well_being", 0),
+            "career_growth": grouped_points.get("career_growth", 0),
+            "relationship": grouped_points.get("relationship", 0)
         }
 
+        # Debug: Check the final structured result
+        logger.info(f"Final Thirty Days Life Score: {thirtydays_life_score}", extra={'user_id': user_id, 'endpoint': function_name})
+
     # Get current goal
     current_goal = '' if not user.goal else user.goal[-1].content
     # Get life score achievements in list
@@ -1035,7 +1063,7 @@ def get_user_life_status(user_id):
     }
 
     # Step 4: Return the JSON reports
-    logger.info(f"User life status generated successfully for user {user_id}", extra={'user_id': user_id, 'endpoint': function_name})
+    logger.info(f"User life status generated successfully for user {user_id}: {reports}", extra={'user_id': user_id, 'endpoint': function_name})
     return reports
 
 async def get_api_key(api_key_header: str = Security(api_key_header)) -> str: