Some common errors or symptoms you may see due to memory issues:

  • "Unexpected error while saving file"
  • "Error loading notebook
    Unreadable notebook:
    <path to notebook" MemoryError()"
  • "An unknown error occurred while loading this notebook. This version can load notebook formats or earlier. See the server log for details."
  • Slow or unresponsive notebooks

Restoring your server memory:

  1. Close the notebook and any other tabs you have open.
  2. Use the Quit button on the Jupyter directory page and re-spawn your server.

Diagnosing the Problem

  1. Are you using good server "hygeine"? See below on things that help prevent memory errors.
  2. You may have a coding problem. Common examples are infinite loops or cross-products in queries.
  3. Some courses have assignments that need more memory. Make sure you are using the correct container for your course.

Some things that help prevent memory errors:

  1. Make sure to save, then go to File > Close and halt to close your notebooks when you are done with them. Also enter exit before closing a terminal tab.
  2. Minimize the number of tabs that are open.
  3. Avoid lots of output. Too much output by itself can crash your server and make it impossible to open a notebook when you re-spawn. Print just a few lines if needed for debugging.
  4. Do not leave your container running when not using it, especially for long periods of time.