In Jupyter notebooks, because Calysto Scheme uses MetaKernel, it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel.

Take a look at our example notebook, streamlit version runs here The main idea is for you do experiment and develop in your notebook, visually see all the pieces, and then convert the notebook to .py ...