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Swallow potential exceptions from showtraceback() (#13934)...
Swallow potential exceptions from showtraceback() (#13934) The nbgrader project is aware of a form of cheating where students disrupt `InteractiveShell.showtraceback` in hopes of hiding exceptions to avoid losing points. They have implemented a solution to prevent this cheating from working on the client side, and have some tests to demonstrate this technique: https://github.com/jupyter/nbgrader/blob/main/nbgrader/tests/apps/files/submitted-cheat-attempt.ipynb https://github.com/jupyter/nbgrader/blob/main/nbgrader/tests/apps/files/submitted-cheat-attempt-alternative.ipynb In essence, these attacks import the interactive shell and erase the traceback handler so that their failing tests won't report failures. ```python import IPython.core.interactiveshell IPython.core.interactiveshell.InteractiveShell.showtraceback = None ``` The problem is that this causes an exception inside the kernel, leading to a stalled execution. The kernel has stopped working, but the client continues to wait for messages. So far, nbgrader's solution to this is to require a timeout value so the client can eventually decide it is done. This prevents allowing a value of `None` for `Execute.timeout` because this would cause a test case to infinitely hang. This commit addresses the problem by making `InteractiveShell._run_cell` a little more protective around it's call to `showtraceback()`. There is already a try/except block around running the cell. This commit adds a finally clause so that the method will _always_ return an `ExecutionResult`, even if a new exception is thrown within the except clause. For the record, the exception thrown is: TypeError: 'NoneType' object is not callable Accepting this change will allow nbgrader to update `nbgrader.preprocessors.Execute` to support a type of `Integer(allow_none=True)` as the parent `NotebookClient` intended. Discussion about this is ongoing in jupyter/nbgrader#1690.

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IPython provides a rich toolkit to help you make the most out of using Python interactively. Its main components are:

  • A powerful interactive Python shell
  • A Jupyter kernel to work with Python code in Jupyter notebooks and other interactive frontends.

The enhanced interactive Python shells have the following main features:

  • Comprehensive object introspection.
  • Input history, persistent across sessions.
  • Caching of output results during a session with automatically generated references.
  • Extensible tab completion, with support by default for completion of python variables and keywords, filenames and function keywords.
  • Extensible system of 'magic' commands for controlling the environment and performing many tasks related either to IPython or the operating system.
  • A rich configuration system with easy switching between different setups (simpler than changing $PYTHONSTARTUP environment variables every time).
  • Session logging and reloading.
  • Extensible syntax processing for special purpose situations.
  • Access to the system shell with user-extensible alias system.
  • Easily embeddable in other Python programs and GUIs.
  • Integrated access to the pdb debugger and the Python profiler.

The latest development version is always available from IPython's GitHub site.