2 ways to list packages in Jupyter Lab | MLJAR Studio: The Ultimate Python Editor for Data Science, Machine Learning, and AI Projects

Many JupyterLab users check installed packages using the terminal, which can be slow and frustrating. However, you can list all installed packages directly from JupyterLab. In this article, I will show you two simple ways to do it without leaving your notebook.

1. Notebook shortcut

The first way to list installed packages is by running a command inside a notebook cell. This method is simple and does not require opening the terminal. Just use the following command:

import sys 
!{sys.executable} -m pip list

Here is an example of usage:

It is important to add !{sys.executable} -m before the pip list command. This makes sure the command runs in the right Python environment and prevents errors.

2. Jupyter Package Manager

There is an easier way to list your packages in Jupyter instead of running a command in a cell - Jupyter Package Manager. It has a simple user interface and offers many options to manage packages. Here's how to use it:

Installation

You can install the extension using following command:

pip install jupyter-package-manager

or download it from GitHub: https://github.com/mljar/package-manager

Open Jupyter Package Manager

After installation, a new icon should appear on the sidebar:

About the Jupyter Package Manager

Now, you have a powerful tool that lets you find any installed package, check its version, delete it, or add a new one - all without writing any code. This saves you time and effort while coding, so you can relax and enjoy a cup of coffee instead of doing all of this manually!

Here’s how it looks:

This extension, along with many others, is available in MLJAR Studio - a powerful Data Science tool that helps you code faster with an AI assistant and other useful features.

Get more information here: https://mljar.com/

Conclusion

Listing installed packages in JupyterLab is quick and easy. You can use a simple command inside a notebook or the Jupyter Package Manager for a more user-friendly experience. With these methods, you can save time and manage your packages without leaving JupyterLab. Try them out and make your workflow smoother!