This repository contains a JupyterLite kernel that uses webR to execute R code. When the kernel is started, the webR WebAssembly binaries are downloaded from CDN and loaded into the page.
A demo instance of JupyterLite including the webR kernel and a sample Jupyter notebook containing R code can be found at https://jupyter.r-wasm.org.
This package is not yet available on PyPI. You can install it from GitHub:
pip install git+https://github.com/r-wasm/jupyterlite-webr-kernel.git
or from a local clone:
git clone https://github.com/r-wasm/jupyterlite-webr-kernel
cd jupyterlite-webr-kernel
pip install .
Then build your JupyterLite site:
jupyter lite build
To use the webR kernel with JupyterLite, the page must be served with certain security-related HTTP headers so that it is cross-origin isolated. By setting these headers webR's SharedArrayBuffer
based communication channel can be used:
Cross-Origin-Opener-Policy: same-origin
Cross-Origin-Embedder-Policy: require-corp
Due to limitations in the way the webR worker thread is implemented, the persistent JupyterLite file storage and the Emscripten VFS used by webR are not accessible to one another. The simplest way to import data into a webR notebook at the time of writing is by using R functions such as read.csv()
with a publicly accessible URL.
While webR supports interrupting long running computations, interrupting cell execution has not yet been implemented in JupyterLite. An infinite looping cell can only be recovered by restarting the kernel.
Note: You will need NodeJS and Python 3.8+ to build the extension package. There is an environment.yml file for conda/mamba/micromamba users to create a conda environment with the required dependencies.
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 jupyterlite-webr-kernel directory
# Install package in development mode
python -m pip install -e ".[dev]"
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm run build
# Rebuild JupyterLite after making changes
jupyter lite clean && jupyter lite build
To serve the extension with the JupyterLite server, you will need to set the required HTTP headers. The config.json
file in this repository contains the required headers. You can start the JupyterLite server with the following command:
jupyter lite serve --config=config.json
Note that making changes to the extension will not automatically re-install the extension in the JupyterLite server. You will need to re-build and restart the server to see changes in the extension.
jupyter lite clean && jupyter lite build && jupyter lite serve --config=config.json
pip uninstall jupyterlite-webr-kernel
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 jupyterlite-webr-kernel
within that folder.