Jupyter is a web server. Notebooks run in the browser. iPython the kernel can run on the command line in addition to the browser.
> 1. You don’t have to install anything, so running (or forking) someone else’s notebook is as simple as clicking a link
Jupyter lets you clone notebooks with the click of a button.
Also, you can run Javascript from a Notebook cell, and there are Python libraries that interface with the JS visualization libraries, like Plotly.
Of course JS gives you full flexibility for talking to the DOM and graphics APIs, but web apps are not the main focus of data science. The web is just one possible means to presentation or collaboration.
Or was it just not an issue, because you figured 1) not having to installing anything and 2) reactive would be enough to win converts?
especially useful with data visualization/exploration, but also helps a lot if you have a complex sequence where it's easy to get lost and forget to recompute something. there's a youtube link in the comments here which explains a lot.
Although I see how that would enable rapid iteration and make e.g. creating nice visualizations much easier, I don't think it should be mandatory. The user may want to control the state their notebook and variables are in manually.
Can you share an example where you’d want that behavior? Spreadsheet cells don’t ask you when they update themselves.