JupyterLab

Basic usage

Using JupyterLab with pixi is very simple. You can just create a new pixi project and add the jupyterlab package to it. The full example is provided under the following Github link.

pixi init
pixi add jupyterlab

This will create a new pixi project and add the jupyterlab package to it. You can then start JupyterLab using the following command:

pixi run jupyter lab

If you want to add more "kernels" to JupyterLab, you can simply add them to your current project – as well as any dependencies from the scientific stack you might need.

pixi add bash_kernel ipywidgets matplotlib numpy pandas  # ...

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_kernel A kernel for bash
• xeus-cpp A C++ kernel based on the new clang-repl
• xeus-cling A C++ kernel based on the slightly older Cling
• xeus-lua A Lua kernel
• xeus-sql A kernel for SQL
• r-irkernel An 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 project, add jupyterlab and pixi-kernel and then start JupyterLab:

pixi init
pixi add jupyterlab pixi-kernel
pixi run jupyter lab

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.

Binder

If you just want to check a JupyterLab environment running in the cloud using pixi-kernel, you can visit Binder.