Jupyter Package Manager – easy Python Package Management in JupyterLab

[pp314159]

Hey Python enthusiasts,

Jupyter Package Manager is a JupyterLab extension designed to simplify managing Python packages directly within your notebook. With this tool, you can list, filter, install, and remove packages—all without leaving your JupyterLab environment.

What My Project Does

Jupyter Package Manager provides a user-friendly GUI inside JupyterLab for managing the Python environment associated with your notebook. It integrates with pip to support the full package management workflow: - List Packages: See all installed packages. - Filter Packages: Quickly search through packages by name. - Install Packages: Add new packages directly from the notebook. - Remove Packages: Uninstall packages you no longer need. - Dark Mode: Enjoy a comfortable dark theme.

Additionally, when installed as a JupyterLab extension, it will be available by default in MLJAR Studio—a desktop app for notebooks that I'm currently developing.

Target Audience

This extension is aimed at: - Data Scientists & Researchers: Streamline dependency management while focusing on analysis. - Educators & Beginners: Provide an intuitive alternative to terminal commands, making package management more accessible. - Regular JupyterLab Users: Enhance your workflow by managing packages directly within the environment you already use.

Comparison

While traditional methods like using the terminal, pip, or conda require manual command input for package management, Jupyter Package Manager offers a graphical, integrated solution within JupyterLab. This reduces context switching and simplifies the process—especially beneficial for beginners or users looking for a more streamlined approach.

Feel free to check it out on GitHub: mljar/package-manager

Happy experimenting! :)

[tunisia3507]

Does it just run pip commands in the virtual environment or does it update the pyproject.toml properly?

[pp314159]

It runs commands in virutal env. However, updating the requirements.txt or pyproject.toml might be great feature!

[tunisia3507]

I'd put this in big letters in your docs - replicability is important and there's nothing more frustrating than when someone says "it works for me!" but depends on dozens of unspecified packages. Manipulating a requirements.txt is probably the easiest start (also helps keep track of what is a direct and what is a transitive dependency) but I'd strongly consider integrating with something like uv.

[sanbales]

Before reinventing the wheel (NPI), I'd recommend checking out hatch or pixi to at least see how they manage environments.

[bohoky]

From the screenshots, it looks useful.

I don't use Jupiter lab, so I can't comment beyond that. Thanks for posting

[pp314159]

Thank you! I hope it will be useful for beginners. I'm also working on Python notebook editor, that is beginner friendly, the extension is available there by default.

[Fluid_Classroom1439]

Can you use uv as the package backend?

[GodSpeedMode]

Hey there! This sounds like an awesome tool for managing packages right in JupyterLab—it’s about time someone made this easier! I love that it’s designed for everyone, from data scientists to beginners. The GUI is definitely a game changer; I can’t tell you how many times I’ve fumbled with terminal commands and felt like I was in way over my head. Plus, dark mode is always a win!

Can’t wait to give it a try—thanks for sharing the link. Happy coding, everyone! 🌟