Update app.py

app.py

@@ -239,7 +239,8 @@ def pull_data_from_salesforce():
         )
        
         query_inventory = "SELECT Product_Name__c, Current_Stocks__c, soldstock__c FROM Inventory_Management__c LIMIT 100"
-        query_unbillable = "SELECT Product_Name__c,Current_Stock__c, soldstock__c FROM Un_Billable__c LIMIT 100"
+        query_unbillable= "SELECT Product_Name__c, Current_Stock__c, soldstock__c FROM Un_Billable__c LIMIT 100"
+        
         
         response_inventory = sf.query_all(query_inventory)
         response_unbillable = sf.query_all(query_unbillable)
@@ -250,35 +251,25 @@ def pull_data_from_salesforce():
         if not records_inventory and not records_unbillable:
             return "No data found in Salesforce.", None, None, None
         
-        # Create separate DataFrames for each object
-        df_inventory = pd.DataFrame(records_inventory).drop(columns=['attributes'], errors='ignore')
-        df_unbillable = pd.DataFrame(records_unbillable).drop(columns=['attributes'], errors='ignore')
+        records = records_inventory + records_unbillable
+        df = pd.DataFrame(records)
+        df = df.drop(columns=['attributes'], errors='ignore')
        
         # Rename columns for better readability
-        df_inventory.rename(columns={
-            "Product_Name__c": "Product Name (Inventory)",
-            "Current_Stocks__c": "Current Stocks (Inventory)",
-            "soldstock__c": "Sold Stock (Inventory)"
-        }, inplace=True)
-        
-        df_unbillable.rename(columns={
-            "Product_Name__c": "Product Name (Unbillable)",
+        df.rename(columns={
+            "Product_Name__c": "Product Name",
+            "Modal_Name__c": "Model Name (Inventory)",
             "Model_Name__c": "Model Name (Unbillable)",
-            "Current_Stocks__c": "Current Stocks (Unbillable)",
-            "soldstock__c": "Sold Stock (Unbillable)"
+            "Current_Stocks__c": "Current Stocks",
+            "soldstock__c": "Sold Stock"
         }, inplace=True)
        
-        # Combine the DataFrames side by side
-        df_combined = pd.concat([df_inventory, df_unbillable], axis=1)
-       
         excel_path = "salesforce_data.xlsx"
-        df_combined.to_excel(excel_path, index=False)
+        df.to_excel(excel_path, index=False)
        
         # Generate interactive vertical bar graph using Matplotlib
         fig, ax = plt.subplots(figsize=(12, 8))
-        width = 0.4  # Width of the bars
-        df_inventory.plot(kind='bar', x="Product Name (Inventory)", y="Current Stocks (Inventory)", ax=ax, legend=True, color='blue', position=0, width=width)
-        df_unbillable.plot(kind='bar', x="Product Name (Unbillable)", y="Current Stocks (Unbillable)", ax=ax, legend=True, color='red', position=1, width=width)
+        df.plot(kind='bar', x="Product Name", y="Current Stocks", ax=ax, legend=False)
         ax.set_title("Stock Distribution by Product Name")
         ax.set_xlabel("Product Name")
         ax.set_ylabel("Current Stocks")
@@ -289,7 +280,7 @@ def pull_data_from_salesforce():
         buffer.seek(0)
         img = Image.open(buffer)
        
-        return "Data successfully retrieved.", df_combined, excel_path, img
+        return "Data successfully retrieved.", df, excel_path, img
     except Exception as e:
         return f"Error fetching data: {str(e)}", None, None, None
 
@@ -343,4 +334,8 @@ def app():
     ], ["📥 OCR Processing", "📊 Salesforce Data Export"])
 
 if __name__ == "__main__":
-    app().launch(share=True)
+    app().launch(share=True)
+
+if __name__ == "__main__":
+    app().launch(share=True)
+