pyproject-local-kernel 0.7.2

Python Jupyter kernel using project/environment manangers like Rye, Uv, PDM, Poetry, Hatch etc.

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Pyproject Local Jupyter Kernel

• Use per-directory python projects to run Python Jupyter kernels
• Separate dependencies for notebooks in separate projects
• Use Rye, Uv, PDM, Poetry, Hatch, or similar project/environment managers to define and run IPython kernels with dependencies for Jupyter notebooks.

Instead of installing a myriad of jupyter kernelspecs, one per project, instead have one "meta" kernel that enables the environment for the project the notebook file resides in. This approach should be more portable, usable to anyone who checks out your project structure from git, and easier to use.

Pyproject Local supports the following systems, and reads pyproject.toml to figure out which kind of project it is:

• Rye
• Uv
• Poetry
• Hatch
• Pdm
• Custom command (for other setups)
• Use venv at path (for other setups)

Quick Start (JupyterLab)

1. Install pyproject-local-kernel in your jupyterlab environment and restart jupyterlab
2. Create a new directory and notebook
3. Select the Pyproject Local kernel for the notebook
4. Run these to setup the new project:

(Example for Rye)

• !rye init --virtual
• !rye add --sync ipykernel

(Example for Uv)

• !uv init
• !uv add "ipykernel>=6"

5. Restart the kernel and you are good to go. Use more add commands to add further dependencies.

• See the examples directory for how to setup jupyterlab and notebook projects separately. JupyterLab and the notebook are installed in separate environments.

Do you want to use pyproject-local-kernel in other environments, like VSCodium or VS Code, or maybe using Pipenv? See our FAQ for more information.

User Experience

If the Pyproject Local kernel is used in a project where Rye (or the relevant project manager) is not installed, or the project does not have an ipykernel in the environment, then starting the kernel fails.

In that case a fallback kernel is started which that shows a message that it is not setup as expected in this environment. This is a regular ipython kernel which allows you to run shell commands and hopefully fix the configuration of the project.

It will give you some hints in the Jupyter notebook interface about the next steps to get it working. Example below is for Rye.

! Failed to start kernel! The detected project type is: Rye
! Is the virtual environment created, and does it have ipykernel in the project?
!
! Run this:
! !rye add --sync ipykernel
!
! Then restart the kernel to try again.

Configuration

Only one of the custom command and virtualenv path configurations can be used at a time.

Virtualenv Path

The key tool.pyproject-local-kernel.use-venv can be a path to a virtualenv, relative to the pyproject.toml file, which should be used.

[tool.pyproject-local-kernel]
use-venv = ".venv"

Custom Command

By default python from the local pyproject is run (using rye run, poetry run, etc.). A custom command can be configured in pyproject.toml - the pyproject file closest to the notebook is used (and no other means of configuration are supported).

The key tool.pyproject-local-kernel.python-cmd should be a command that runs python in the virtual environment you want to use for the project.

[tool.pyproject-local-kernel]
python-cmd = ["my", "custom", "python"]

About Particular Project Managers

The project manager command, be it rye, uv, pdm, etc needs to be available on the path where jupyterlab runs. Either install the project manager in the jupyterlab environment, or install the project manager user-wide (using something like pipx, rye tools, uv tool, brew, or other method to install it.)

Rye

• Rye is detected if the pyproject.toml contains tool.rye.managed = true which Rye sets by default for its new projects.

Uv

• Uv is detected if the pyproject.toml contains tool.uv. It is also the default fallback if no project manager is detected from a pyproject file.

• pyproject-local-kernel requires uv 0.2.29 or later

• Uses uv run which is a preview feature (could break on future uv changes)

• The command used is uv run --with ipykernel python which means that it ensures ipykernel is used even if it's not already in the project(!). However, note that it uses an ephemeral virtual environment for ipykernel in that case. Add ipykernel to the project to avoid this.

Project Status

Status: Working proof of concept, published to PyPI. Additional interest and maintainer help is welcomed.

See also:

• https://github.com/mitsuhiko/rye
• https://github.com/astral-sh/uv
• https://github.com/goerz/python-localvenv-kernel
• https://github.com/pathbird/poetry-kernel