JupyterLab
Basic usage#
Using JupyterLab with Pixi is very simple.
You can just create a new Pixi workspace and add the jupyterlab package to it.
The full example is provided under the following Github link.
This will create a new Pixi workspace and add the jupyterlab package to it. You can then start JupyterLab using the
following command:
If you want to add more "kernels" to JupyterLab, you can simply add them to your current workspace – as well as any dependencies from the scientific stack you might need.
What kernels are available?#
You can easily install more "kernels" for JupyterLab. The conda-forge repository has a number of interesting additional kernels - not just Python!
bash_kernelA kernel for bashxeus-cppA C++ kernel based on the new clang-replxeus-clingA C++ kernel based on the slightly older Clingxeus-luaA Lua kernelxeus-sqlA kernel for SQLr-irkernelAn R kernel
Advanced usage#
If you want to have only one instance of JupyterLab running but still want per-directory Pixi environments, you can use
one of the kernels provided by the pixi-kernel
package.
Configuring JupyterLab#
To get started, create a Pixi workspace, add jupyterlab and pixi-kernel and then start JupyterLab:
This will start JupyterLab and open it in your browser.

pixi-kernel searches for a manifest file, either pixi.toml or pyproject.toml, in the same directory of your
notebook or in any parent directory. When it finds one, it will use the environment specified in the manifest file to
start the kernel and run your notebooks.