variable-inspector 1.3.0

Variable explorer for Jupyter Lab.

Jupyter Variable Inspector

The Variable Inspector is a Jupyter Lab extension designed to help you manage and track variables within your notebook. It displays all your variables in one convenient location, allowing you to see their names, values, types, shapes, and sizes in real-time. This feature makes it easier to work without the need to manually print or check your variables. It is for Python only..

Install the extension using pip by following the instructions below. It’s also available in our desktop app, MLJAR Studio, which is designed to make Python easier for beginners.

Features

Display variables

Explore all available variables in the current notebook as a list.

Display DataFrames

You can preview the DataFrame values as an interactive table.

Display DataFrames with updates

The preview of DataFrame will be automatically refreshed when you change it in the Python code.

Customize displayed columns

You can select which properties of the variables you'd like to display:

Automatic or manual refresh

The list of variables will automatically update whenever you execute a cell. However, you can choose the Manual Refresh option to update the list at your convenience.

Dark theme

If you prefer a darker look, a Dark Theme is also available!

Variable Inspector requirements

• JupyterLab >= 4.0.0

Install extension

To install the extension, execute:

pip install variable_inspector

Uninstall extension

To remove the extension, execute:

pip uninstall variable_inspector

Contributing

Development install

Note: You will need NodeJS to build the extension package.

The jlpm command is JupyterLab's pinned version of yarn that is installed with JupyterLab. You may use yarn or npm in lieu of jlpm below.

# Clone the repo to your local environment
# Change directory to the variable_inspector directory
# Install package in development mode
pip install -e "."
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm build

You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.

# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm watch
# Run JupyterLab in another terminal
jupyter lab

With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).

By default, the jlpm build command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:

jupyter lab build --minimize=False

Development uninstall

pip uninstall variable_inspector

In development mode, you will also need to remove the symlink created by jupyter labextension develop command. To find its location, you can run jupyter labextension list to figure out where the labextensions folder is located. Then you can remove the symlink named variable-inspector within that folder.

Here’s a simple README.md you can drop into your repo 👇

Running End-to-End UI Tests

This project uses Playwright to run UI tests against JupyterLab with the MLJAR extension.

Prerequisites

• Node.js / Yarn
• Playwright installed (jlpm playwright install)

How to Run Tests

You need two terminals:

1. Start JupyterLab

In the first terminal, run:

jlpm lab

This will start JupyterLab at http://localhost:8899/lab.

2. Run UI Tests

In the second terminal, run:

jlpm test:ui:headed

This will:

• Remove any temporary Untitled*.ipynb files
• Launch Playwright in headed mode (with a visible browser)
• Run the end-to-end tests defined in tests/e2e
• Remove leftover Untitled*.ipynb files after tests finish

Notes

• Logs are printed to the console during test execution for easier debugging.
• If you encounter navigation timeout errors, make sure JupyterLab is fully started before running the tests.

Packaging the extension

See RELEASE