JupyterLab 3.0 now ships with a Debugger front-end by default.
This means that notebooks, code consoles and files can now be debugged from JupyterLab directly!
For the debugger to be enabled and visible, a kernel with support for debugging is required.
Here is a list of kernels that are known to be supporting the Jupyter Debug Protocol:
xeus-python: Jupyter kernel for the Python programming language
xeus-robot: Jupyter kernel for Robot Framework
ipykernel: IPython Kernel for Jupyter
Other Jupyter Kernels can also support debugging and be compatible with the JupyterLab debugger by implementing the Jupyter Debugger Protocol.
If you know of other kernels with support for debugging, please open a PR to add them to this list.
Here is an example of how to install
xeus-python in a new
conda create -n jupyterlab-debugger -c conda-forge jupyterlab=3 "ipykernel>=6" xeus-python conda activate jupyterlab-debugger
For Python, both
ipykernel (6.0+) and
xeus-python support debugging.
Enable the debugger, set breakpoints and step into the code:
There is also a tutorial notebook to try the debugger that is available on the jupyter-ide-demo repo. and can be run on Binder here.