One of the most efficient tools for a data scientist, Jupyter plays a potential role in the scientific community when it comes to working on complex scientific computations. All these years, the users of JupyterLab have been requesting to add a visual debugger so that the users need not switch into a different tool for more classical software development.
Recently, Jupyter announced the first public release of the Jupyter visual debugger. The JupyterLab debugger is the result of the collaboration and coordination of developers from several institutions, including QuantStack, Two Sigma, and Bloomberg.
Using this debugger, one can set breakpoints in notebook cells and source files, inspect variables, navigate the call stack and can do much more. The debugger extension for JupyterLab has been designed to work with any kernel that supports debugging, provides the following
- a sidebar with a variable explorer, a list of breakpoints, a source preview
- the possibility to navigate the call stack
- the ability to set breakpoints directly next to the code, namely in code cells and code consoles
- visual markers to indicate where the current execution has stopped.
- The debugger front-end can be installed as a JupyterLab extension. In the future release, the debugger front-end will be included in JupyterLab by default.
- In the back-end, a kernel implementing the Jupyter Debug Protocol will be required. Currently, the only kernel implementing this protocol is xeus-python, which is a new Jupyter kernel for the Python programming language.
For the future development of this visual debugger, the developers are planning to create support for rich mime type rendering in the variable explorer, support for conditional breakpoints in the UI, general improvements of the debugger user experience and enable the debugging of Voilà dashboards, from the JupyterLab Voilà preview extension.
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