scijava-jupyter-kernel aims to be a polyglot Jupyter kernel. It uses the Scijava scripting languages to execute the code in Jupyter client and it's possible to use different languages in the same notebook.
The kernel has been originally created to work with ImageJ. See here for more details.
Under the hood
scijava-jupyter-kernel uses the Beaker base kernel.
A documentation is available as a series of notebooks here.
- Install Anaconda
# Add the conda-forge channel conda config --add channels conda-forge # Create an isolated environment called `java_env` and install the kernel conda create --name java_env scijava-jupyter-kernel
- Usage :
# Activate the `java_env` environment source activate java_env # Check the kernel has been installed jupyter kernelspec list # Launch your favorite Jupyter client jupyter notebook # or jupyter lab
Note : It is strongly suggested to install the kernel in an isolated Conda environment (not in the root environment).
- CI with Travis makes sure the project builds without errors for each new commit.
- A test notebook is executed during CI with nbconvert.
- A Conda package is built for each new release.
Under Apache 2.0 license. See LICENSE.
- Hadrien Mary email@example.com