Jupyter Notebook installation and setup The easiest way to create and work with Jupyter Notebooks for Python is to set up an instance of the Anaconda distribution of Python.

Certain home server operating systems, like YunoHost, include JupyterLab/Jupyter Notebook containers, which are perfect if you want an easy method to host this neat tool on your system.

Because of the client/server architecture, it is very simple to share notebooks with other users. You can — in theory — use Jupyter for anything you could use Python for.

Another option is to keep using the Python kernel, but compile and run your C code via the operating system. This will often even work in cloud environments that don’t support the C kernel.

Jupyter Notebook is not a full-blown development environment for Python. Many of the features you would expect to find in an IDE—e.g., interactive debugging, code completion, and module ...