backend/calculations/nutrition_metrics.py

@@ -41,7 +41,7 @@ def calculate_energy_balance_7d(profile_id: str) -> Optional[float]:
         if len(calories) < 4:  # Need at least 4 days
             return None
 
-        avg_intake = sum(calories) / len(calories)
+        avg_intake = float(sum(calories) / len(calories))
 
         # Get estimated TDEE (simplified - could use Harris-Benedict)
         # For now, use weight-based estimate
@@ -123,7 +123,7 @@ def calculate_protein_g_per_kg(profile_id: str) -> Optional[float]:
         if len(protein_values) < 4:
             return None
 
-        avg_protein = sum(protein_values) / len(protein_values)
+        avg_protein = float(sum(protein_values) / len(protein_values))
         protein_per_kg = avg_protein / weight
 
         return round(protein_per_kg, 2)
@@ -172,7 +172,7 @@ def calculate_protein_days_in_target(profile_id: str, target_low: float = 1.6, t
         total_days = len(protein_data)
 
         for row in protein_data:
-            protein_per_kg = row['protein_g'] / weight
+            protein_per_kg = float(row['protein_g']) / weight
             if target_low <= protein_per_kg <= target_high:
                 days_in_target += 1
 
@@ -210,7 +210,7 @@ def calculate_protein_adequacy_28d(profile_id: str) -> Optional[int]:
               AND protein_g IS NOT NULL
         """, (profile_id,))
 
-        protein_values = [row['protein_g'] for row in cur.fetchall()]
+        protein_values = [float(row['protein_g']) for row in cur.fetchall()]
 
         if len(protein_values) < 18:  # 60% coverage
             return None