Boost Your Jupyter Notebook Productivity with 5 Essential Extensions

Minimalist Tutorial

Run the following command in a terminal:

pip install jupyter_contrib_nbextensions && jupyter contrib nbextension install

Start Jupyter Notebook and open the new Nbextensions tab.

Jupyter Notebook Extensions Tab

Select the extensions you want to enable and enjoy their benefits.

If you don’t see the extensions tab, open notebook, click “edit”, then “nbextensions config”.

You can also view installed extensions in the notebook toolbar.

Extended Tutorial

If the short guide feels too simple, explore the detailed version below, which lists my five favorite extensions.

What Are Notebook Extensions?

Jupyter Notebook extensions are small plugins written in JavaScript that extend the notebook’s core functionality, such as automatic code formatting or browser notifications. They currently work only with Jupyter Notebook (not JupyterLab).

Why use extensions? While Jupyter Notebook is great for teaching, prototyping, and exploration, its native feature set is limited and can be frustrating. Extensions don’t solve every limitation, but they make daily work smoother.

Which Extensions Should You Use?

Here are the five extensions I use most often:

1. Table of Contents – Easier Navigation

When a notebook has many cells, tracking them becomes hard. The Table of Contents extension adds a TOC with links to any part of the notebook.

2. Autopep8 – One‑Click Code Beautification

Autopep8 formats your code to comply with PEP‑8 standards with a single click, saving time and keeping your code clean.

This plugin is especially handy for eliminating tedious manual formatting.

3. Variable Inspector – Track Your Workspace

Variable Inspector displays all variables created in the notebook, along with their type, size, shape, and value.

It’s invaluable for data scientists transitioning from RStudio who want to avoid repetitive print statements.

4. ExecuteTime – Show Cell Execution Duration

ExecuteTime displays how long each cell takes to run and the timestamp of the last execution, helping you identify slow cells.

While more precise timing tools exist (e.g., %%timeit), ExecuteTime is easy to use and works across all cells.

5. Hide Code Input – Show Results Only

This extension lets you hide all code cells, displaying only the output, which is useful when you want to share results without exposing the underlying code.

When someone asks to see only the results, a single click hides the code (though you should still review it regularly).

Conclusion

Install Jupyter Notebook extensions, explore which ones are useful for you, and boost your workflow efficiency. While they won’t change your life, they save valuable development time.

If you write production code, you might also consider an IDE such as VS Code, but Jupyter Notebook remains an essential part of the data‑science pipeline, and mastering its extensions maximizes its benefits.