Troubleshooting and Debugging

Troubleshooting

If you’re having issues with your ICRN JupyterLab environment, try these basic troubleshooting steps first. If the issue persists, submit a support request and NCSA staff will work to help you resolve it.

Stop Your Server

If your code is acting in an unexpected way, the first troubleshooting step to try is to stop and re-start your server.

Warning

This will stop any processes running in your JupyterLab environment.

  1. In the File menu, select Hub Control Panel.

    File menu.
    File menu showing hub control panel option.
  2. Click the Stop My Server button.

    Stop my server button.
  3. Click the Start My Server button. This will redirect you to the server options list.

    Start my server button.
  4. Select your server and click Start to re-enter your JupyterLab environment.

Uninstall a Recently Installed Extension

If you recently installed an extension (see Extensions) prior to experiencing issues with your code, uninstall the extension to see if that resolves the issue.

  1. Click on the Extension Manager (puzzle piece) icon.

    Extension manager icon.
  2. Open the INSTALLED pane in the extension manager.

  3. Find your recently installed extension in the list and click the Uninstall button.

    Extension manager installed extensions pane.
  4. Refresh your webpage when prompted.

    Warning

    This will stop any processes running in your JupyterLab environment.

    Refresh your webpage pop-up window.

Access Built-in Help Tools

Python and R have built-in help commands that you can use to learn more about other commands. To access help, enter help() in a console or notebook and follow the prompts.

The Help menu in the JupyterLab environment also includes Jupyter, Python, and Markdown references.

JupyterLab menus with help menu highlighted.

Debugging

This section includes information to help debug common code issues that ICRN users have. If the issue persists, submit a support request and NCSA staff will work to help you resolve it.

“The kernel for <>.ipynb appears to have died. It will restart automatically.”

Pop-up window of the Kernel Restarting error. "The kernel for <untitled>.ipynb appears to have died. It will restart automatically."

If Python code in your notebook returns this error, copy the code to a Terminal and run it there as a script.

Notebooks are limited to 8GB of memory. If your notebook uses more memory than that, this is the error message you will see. Running the code in a terminal will return more informative error messages to help you diagnose the issue and/or confirm it’s a memory usage issue.