Jupyter newbie - Pre-reqs for Python based Jupyter notebooks

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I’ll try to help with some of these:

  1. Actually notebook files are stored as json files. They support any language there is a kernel for, including R. (Example of R in Jupyter is here if you pick Jupyter+R to launch.) The kernel gets specified towards the end of the json file. Within the notebook, individual cells can be code or markdown or raw text. The first two being the most common you would use. They get stored as json in the .ipynb file and when you open the notebook in Jupyter, the various cells get handled appropriately.
  2. I suspect when you are saying some of the Github repos, launch the notebook, you are referring to those that use MyBinder.org to launch a remote Jupyterhub session.
  3. This part I am least sure of as I don’t normally have occasion to do this beyond debugging. (The visual debugger is very cool, see here.) I suspect you want to look inside what is going on in the kernel, sort of like this. I know there is also kernelspec and maybe that is related to what you need?
    But maybe you are asking if you can run it from the command line, too? Which you can either do directly with as a notebook with nbconvert or converted to a script using jupytext, see here.
  1. I believe current Jupyter may require Python3. However, you can run Python 2 as a kernel still. Examples here and [here]https://github.com/binder-examples/python2_with_3). I’ve seen different pips aliased to Python 2 and 3 depending on what you need. At this point unless you need Python 2, just use Python 3 and then you don’t have to worry.
  2. Conda and Jupyter aren’t two different ways to build and work with .ipynb. Jupyter is needed to work with Jupyter notebooks actively as notebook. Conda is a popular package management system and environment building system that features a Python distribution as one of the many things it can do and so that is why it is highly recommended. See here for another take on that. You could do it without it, or try another package manager/Python distribution. Enthought’s Canopy used to be a popular way to go.

Jupyter also is a larger ecosystem than the Jupyter notbeook server, too. There is JupyterHub, etc. JupyterLab is the next evolution of the Jupyter notebook interface in a lot of ways. If you use RStudio a lot it will be more familiar to you in some ways. I made a page a few months ago to convince folks running a group aimed at training biologists on computing here that features an awesome image made by others and links to more about the ecosystem.

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