When debugging Python code, I frequently use the Data Wrangler "View Value in Data Viewer" feature to inspect Pandas DataFrames. However, if I restart the debug session (Ctrl+Shift+F5), the existing Data Viewer tab does not update. It holds onto the stale memory reference from the previous run.
To view the new DataFrame, I have to manually close the stale tab, go back to the debug panel, and click "View Value in Data Viewer" again. This creates significant friction during highly iterative data workflows where I am frequently tweaking code and restarting the debugger.
I would like the Data Viewer to have an option to auto-refresh or persist the current view across debug session restarts. If the debugger restarts, pauses at a breakpoint, and a variable with the exact same name (e.g., my_df) is available in the current local scope, the active Data Viewer tab should automatically bind to the new memory reference and display the updated data.
When debugging Python code, I frequently use the Data Wrangler "View Value in Data Viewer" feature to inspect Pandas DataFrames. However, if I restart the debug session (Ctrl+Shift+F5), the existing Data Viewer tab does not update. It holds onto the stale memory reference from the previous run.
To view the new DataFrame, I have to manually close the stale tab, go back to the debug panel, and click "View Value in Data Viewer" again. This creates significant friction during highly iterative data workflows where I am frequently tweaking code and restarting the debugger.
I would like the Data Viewer to have an option to auto-refresh or persist the current view across debug session restarts. If the debugger restarts, pauses at a breakpoint, and a variable with the exact same name (e.g., my_df) is available in the current local scope, the active Data Viewer tab should automatically bind to the new memory reference and display the updated data.