api

app.py

@@ -37,8 +37,24 @@ try:
     
     # Read the Excel file from the downloaded content
     excel_content = io.BytesIO(response.content)
+    def custom_date_parser(date_str):
+        try:
+            return pd.to_datetime(date_str, format='%m/%d/%Y')
+        except:
+            try:
+                return pd.to_datetime(date_str, format='%Y-%m-%d')
+            except:
+                return pd.to_datetime(date_str, format='mixed', dayfirst=False)
+            
     purchase_history = pd.read_excel(excel_content, sheet_name='Transaction History', 
-                                   parse_dates=['Purchase_Date'])
+                                   parse_dates=['Purchase_Date'],date_parser=custom_date_parser)
+    
+     # Ensure Purchase_Date is datetime
+    purchase_history['Purchase_Date'] = pd.to_datetime(
+        purchase_history['Purchase_Date'],
+        format='mixed',
+        dayfirst=False
+    )
     
     # Read Customer Profile sheet
     excel_content.seek(0)  # Reset buffer position
@@ -571,30 +587,19 @@ async def get_financial_analysis(customer_id: str):
 
         # Get customer profile and transactions
         customer_profile = customer_profiles[customer_profiles['Customer_Id'] == customer_id].iloc[0]
-        customer_transactions = purchase_history[purchase_history['Customer_Id'] == customer_id].copy()  # Create a copy
+        customer_transactions = purchase_history[purchase_history['Customer_Id'] == customer_id].copy()
 
-        # Convert Purchase_Date to datetime if it's not already
+        # Ensure Purchase_Date is in datetime format
         if not pd.api.types.is_datetime64_any_dtype(customer_transactions['Purchase_Date']):
-            try:
-                # First try M/D/YYYY format
-                customer_transactions['Purchase_Date'] = pd.to_datetime(
-                    customer_transactions['Purchase_Date'],
-                    format='%m/%d/%Y'
-                )
-            except ValueError:
-                try:
-                    # If that fails, try YYYY-MM-DD format
-                    customer_transactions['Purchase_Date'] = pd.to_datetime(
-                        customer_transactions['Purchase_Date'],
-                        format='%Y-%m-%d'
-                    )
-                except ValueError:
-                    # If both fail, try automatic parsing
-                    customer_transactions['Purchase_Date'] = pd.to_datetime(
-                        customer_transactions['Purchase_Date'],
-                        format='mixed',
-                        dayfirst=False
-                    )
+            customer_transactions['Purchase_Date'] = pd.to_datetime(
+                customer_transactions['Purchase_Date'],
+                format='mixed',
+                dayfirst=False
+            )
+
+        # Print debug information
+        logger.info(f"Date column type: {customer_transactions['Purchase_Date'].dtype}")
+        logger.info(f"Sample dates: {customer_transactions['Purchase_Date'].head()}")
 
         # Calculate basic financial metrics
         current_date = datetime.now()