A visual debugger extension for Jupyter notebooks, consoles, and source files, enabling step-through debugging within JupyterLab.
The JupyterLab Debugger is a visual debugging extension for JupyterLab that enables step-through debugging of code in notebooks, consoles, and source files. It integrates directly into the JupyterLab interface, allowing developers to set breakpoints, inspect variables, and control execution without leaving their interactive computing environment. It solves the problem of disjointed debugging workflows in Jupyter by bringing IDE-like debugging capabilities to the notebook.
Data scientists, researchers, and developers who use JupyterLab for interactive Python development and need robust debugging tools within their notebook environment. It is particularly valuable for those working with complex analyses or iterative code development in Jupyter.
Developers choose the JupyterLab Debugger because it provides a native, integrated debugging experience within JupyterLab, eliminating the need to switch to external IDEs. Its adherence to the Debug Adapter Protocol ensures compatibility with kernels like xeus-python and potential future extensibility, while its visual interface makes debugging interactive code more intuitive.
A visual debugger for Jupyter notebooks, consoles, and source files
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Provides a familiar debugger panel with stepping controls and breakpoint management directly in JupyterLab, eliminating the need to switch to external IDEs for debugging.
Uses the Debug Adapter Protocol for communication with kernels, ensuring compatibility with tools like xeus-python and enabling future extensibility to other kernels.
Supports debugging not only in notebook cells but also in consoles and external source files, offering flexibility across different code execution contexts.
Allows developers to examine variable values and scopes in real-time during debug sessions, enhancing debugging efficiency with live data inspection.
Currently only works with the xeus-python kernel, not with standard IPython or other kernels, restricting its use in diverse Python environments or with other languages.
For JupyterLab 2.x, installation requires a specific conda environment and dependencies like ptvsd, which is more cumbersome compared to the built-in support in JupyterLab 3.x.
This GitHub repository is archived, with development moved to the main JupyterLab repo, potentially causing confusion for users seeking issues or updates directly here.