Update app.py

app.py

@@ -229,9 +229,55 @@ def export_to_salesforce(mode, entry_type, quantity, edited_df):
     try:
         # Convert edited DataFrame back to dictionary
         edited_attributes = dict(zip(edited_df["Attribute"], edited_df["Value"]))
-       
+
         # Export to Salesforce
         message = interact_with_salesforce(mode, entry_type, quantity, edited_attributes)
+
+        # Fetch the Price__c field value from Salesforce
+        if mode == "Exit" and entry_type == "Sales":
+            sf = Salesforce(
+                username=SALESFORCE_USERNAME,
+                password=SALESFORCE_PASSWORD,
+                security_token=SALESFORCE_SECURITY_TOKEN
+            )
+            object_name = "Inventory_Management__c"
+            product_field_name = "Productname__c"
+            model_field_name = "Model__c"
+            stage_field_name = "Stage__c"
+            hp_field_name = "H_p__c"
+            price_field_name = "Price__c"
+
+            query_conditions = [f"{product_field_name} = '{edited_attributes.get('Product name', '')}'"]
+            if "Model Name" in edited_attributes and edited_attributes["Model Name"]:
+                query_conditions.append(f"{model_field_name} = '{edited_attributes['Model Name']}'")
+            if "Stage" in edited_attributes and edited_attributes["Stage"]:
+                query_conditions.append(f"{stage_field_name} = '{edited_attributes['Stage']}'")
+            if "H.P." in edited_attributes and edited_attributes["H.P."]:
+                query_conditions.append(f"{hp_field_name} = '{edited_attributes['H.P.']}'")
+
+            query = f"SELECT {product_field_name}, {model_field_name}, {stage_field_name}, {hp_field_name}, {price_field_name} FROM {object_name} WHERE {' AND '.join(query_conditions)} LIMIT 1"
+            response = sf.query(query)
+
+            if response["records"]:
+                record = response["records"][0]
+                product_name = record.get(product_field_name, "N/A")
+                model = record.get(model_field_name, "N/A")
+                stage = record.get(stage_field_name, "N/A")
+                hp = record.get(hp_field_name, "N/A")
+                price = record.get(price_field_name, "N/A")
+
+                # Append the details to the result message
+                message += (
+                    f"\nDetails:\n"
+                    f"Product Name: {product_name}\n"
+                    f"Model: {model}\n"
+                    f"Stage: {stage}\n"
+                    f"H.P.: {hp}\n"
+                    f"Price: {price}"
+                )
+            else:
+                message += "\n❌ No matching record found to fetch additional details."
+
         return message
     except Exception as e:
         return f"❌ Error exporting to Salesforce: {str(e)}"
@@ -244,21 +290,21 @@ def pull_data_from_salesforce(data_type):
             password=SALESFORCE_PASSWORD,
             security_token=SALESFORCE_SECURITY_TOKEN
         )
-       
+
         if data_type == "Inventory":
             query = "SELECT Productname__c, Model__c, H_p__c, Stage__c, Current_Stocks__c, soldstock__c, Price__c FROM Inventory_Management__c LIMIT 100"
         else:
             query = "SELECT Productname__c, Model__c, H_p__c, Stage__c, Current_Stock__c, soldstock__c, Price__c FROM Un_Billable__c LIMIT 100"
-       
+
         response = sf.query_all(query)
         records = response.get("records", [])
-       
+
         if not records:
             return "No data found in Salesforce.", None, None, None
-       
+
         df = pd.DataFrame(records)
         df = df.drop(columns=['attributes'], errors='ignore')
-       
+
         # Rename columns for better readability
         df.rename(columns={
             "Productname__c": "Product Name",
@@ -270,10 +316,10 @@ def pull_data_from_salesforce(data_type):
             "soldstock__c": "Sold Stock",
             "Price__c": "Price"
         }, inplace=True)
-       
+
         excel_path = "salesforce_data.xlsx"
         df.to_excel(excel_path, index=False)
-       
+
         # Generate interactive vertical bar graph using Matplotlib
         fig, ax = plt.subplots(figsize=(12, 8))
         df.plot(kind='bar', x="Product Name", y="Current Stocks", ax=ax, legend=False)
@@ -286,7 +332,7 @@ def pull_data_from_salesforce(data_type):
         plt.savefig(buffer, format="png")
         buffer.seek(0)
         img = Image.open(buffer)
-       
+
         return df, excel_path, img
     except Exception as e:
         return f"Error fetching data: {str(e)}", None, None, None