Jupyterlab extension that shows currently used variables and their values.
Contributions in any form are welcome!
- 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.
- This extension is currently targets
pythonas a main language but also supports the following languages with different levels of feature completeness
scalavia the almond kernel
How it Works
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.
- JupyterLab >= 3.0
numpyare required to enable matrix inspection.
pysparkfor spark support.
kerasto allow inspection of tf objects.
torchfor PyTorch support.
The variable inspector can also display Jupyter interactive widgets:
The requirements for this functionality are:
- Support for widgets in JupyterLab:
jupyter labextension install @jupyter-widgets/jupyterlab-manager
NOTE: The main way to install this extension is via pip as described below.
pip install lckr-jupyterlab-variableinspector
Alternatively, one can install the extension from npmjs via:
jupyter labextension install @lckr/jupyterlab_variableinspector
or via the extension manager that comes built-in with Jupyterlab
Note: You will need NodeJS to build the extension package.
jlpm command is JupyterLab's pinned version of
yarn that is installed with JupyterLab. You may use
npm in lieu of
# 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
pip uninstall lckr_jupyterlab_variableinspector