jupyterlab_variableinspector

Jupyterlab extension that shows currently used variables and their values. The goal is to provide a tool similar to the variable inspector in RStudio.

This project is inspired by the variable inspector extension for jupyter notebooks and by the inspector extension included in jupyterlab.

Contributions in any form are very welcome!

Features

• Allows inspection of variables for both consoles and notebooks.
  • This extension is currently targets python as a main language but also supports the following languages with different levels of feature completeness
    • R
    • scala via the almond kernel
• Allows inspection of matrices in a datagrid-viewer. This might not work for large matrices.
• Allows an inline and interactive inspection of Jupyter Widgets.

Caveat In order to allow variabale inspection, all content that is displayed first need to be sent from the kernel to the front end.
Therefore, opening large data frames with the datagrid viewer can dramatically increase your occupied memory and significantly slow down your browser.
Use at your own risk.

Requirements

• JupyterLab >= 3.0

Requirements for Python functionality

• pandas and numpy are required to enable matrix inspection.
• pyspark for spark support.
• tensorflow and keras to allow inspection of tf objects.

Requirements for ipywidgets functionality

The variable inspector can also display Jupyter interactive widgets:

The requirements for this functionality are:

• ipywidgets
• Support for widgets in JupyterLab: jupyter labextension install @jupyter-widgets/jupyterlab-manager

Requirements for R functionality

• The repr library.

Install

pip install lckr-jupyterlab-variableinspector

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 lckr_jupyterlab_variableinspector 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 run 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 run 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 run 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

Uninstall

pip uninstall lckr_jupyterlab_variableinspector