nb-nebi-kernels

A custom Jupyter KernelSpecManager that automatically discovers Nebi-tracked Pixi workspaces and exposes each environment as a launchable Jupyter kernel.

How it works

1. Discovers locally-tracked workspaces via nebi workspace list
2. Enumerates pixi environments per workspace via pixi workspace environment list
3. Each (workspace, environment) pair appears as a selectable kernel in Jupyter
4. Kernels launch via pixi run in the workspace directory with full environment isolation

Installation

pip install nb-nebi-kernels

That's it — the kernel spec manager is automatically configured when installed into your JupyterLab environment.

Prerequisites

• Nebi CLI on your PATH
• Pixi on your PATH
• At least one tracked nebi workspace (nebi init in a pixi project)

Usage

Once installed, any nebi-tracked pixi workspace appears as a kernel in JupyterLab or Notebook:

• A workspace data-science with environments default and gpu shows as two kernels: data-science (default) and data-science (gpu)
• A workspace web-app with only the default environment shows as just web-app

If nebi or pixi are not installed, or no workspaces are tracked, Jupyter falls back to its default kernels — it never crashes.

Development

# Install dev dependencies
pixi install -e dev

# Run tests
pixi run test

# Run tests with coverage
pixi run test-cov

# Run linting
pixi run lint

# Format code
pixi run format

# Run type checking
pixi run typecheck

Architecture

src/nb_nebi_kernels/
├── __init__.py      # Exports NebiKernelSpecManager
├── discovery.py     # Subprocess calls to nebi + pixi CLIs
├── launcher.py      # Kernel launcher with pixi environment isolation
└── manager.py       # KernelSpecManager subclass (core logic)

• discovery.py — Parses nebi workspace list output, calls pixi workspace environment list per workspace. Filters out missing workspaces. Returns structured data.
• launcher.py — Clears PIXI_* environment variables to prevent inheriting parent context, then exec's pixi run in the workspace directory.
• manager.py — Subclasses KernelSpecManager, implements find_kernel_specs() and get_kernel_spec(). Merges parent kernels with nebi-discovered ones.

License

MIT