lckr-jupyterlab-variableinspector

jupyterlab_variableinspector

Jupyterlab extension that shows currently used variables and their values.
Contributions in any form are welcome!

Features

• Allows inspection of variables for both consoles and notebooks.
• Allows inspection of matrices in a datagrid-viewer. This might not work for large matrices.
• Allows an inline and interactive inspection of Jupyter Widgets.

Supported Languages

• 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

How it Works

In order to allow variable 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.
• torch for PyTorch support.

Requirements for R functionality

• The repr library.

Requirements for ipywidgets functionality

The variable inspector can also display Jupyter interactive widgets:

The requirements for this functionality are:

• ipywidgets, which can be installed with pip install ipywidgets.

Install

To install the extension, execute:

pip install lckr_jupyterlab_variableinspector

Uninstall

To remove the extension, execute:

pip uninstall 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 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 lckr_jupyterlab_variableinspector

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 @lckr/jupyterlab_variableinspector within that folder.

Testing the extension

Frontend tests

This extension is using Jest for JavaScript code testing.

To execute them, execute:

jlpm
jlpm test

Integration tests

This extension uses Playwright for the integration tests (aka user level tests). More precisely, the JupyterLab helper Galata is used to handle testing the extension in JupyterLab.

More information are provided within the ui-tests README.

Packaging the extension

See RELEASE