fix: address the error display issue on workbench only

[fangyh20]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @fangyh20, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enhances the user experience within Jupyter Workbench environments by refining how specific exceptions are presented. It implements a targeted exception handler that simplifies the output for DataprocSparkConnectException instances, showing only the relevant error message. This change aims to reduce visual clutter and make error diagnosis more straightforward for users in an interactive notebook setting, without altering the display of other exception types.

Highlights

• Custom Exception Handling: Introduces a custom exception handler specifically for IPython environments to modify how errors are displayed.
• Workbench-Specific Behavior: The custom exception handling logic is only activated when the code is running within a Jupyter Workbench environment, ensuring no impact on other execution contexts.
• Simplified Error Display: For instances of DataprocSparkConnectException, the system will now display only the concise error message, rather than a full traceback, to improve readability.
• Preservation of Original Behavior: For all other types of exceptions, the original IPython traceback display mechanism is preserved, maintaining expected behavior for non-custom errors.

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[gemini-code-assist]

Code Review

This pull request introduces a mechanism to simplify exception tracebacks for DataprocSparkConnectException within Jupyter Workbench environments. This is achieved by monkey-patching IPython's showtraceback method at module import time. The implementation is well-guarded to only apply in the target environment. My review includes a suggestion to improve the robustness of the patch against future changes in IPython's API.