The project [0] looks more like a peer to ObservableHQ [1], in the sense that both appear to be working toward combining editing source, REPL, visualization, and collaboration into an broadly adopted platform. Jupyter-next.
From my perspective, a Jupyter notebook is a kind of commented script. It integrates rendering into python REPL. Code, commentary, and charts, all in one interactive frame. Cells serve as functions. The overall navigation is linear, but you can replay the script from different cells. So, rather than REPL, read-eval-render-script.
As a pre-notebook era REPL plus IDE coder, to me notebooks offer the advantage of integrated data viz and a new kind of delivery medium for code tutorials and for analytic & data projects. They feel like a better way to script-n-tell, not a better way to develop - as long as you have an easy means to viz from the commandline.
My impression is that part of what ObservableHQ is doing is to create a substrate below a cell as an explicit evaluation graph that a developer can work with directly. And that leads to a better programming experience for developing notebooks, and for better developing within notebooks. I hope that does not mis-state the vision. But the more I work with notebooks, the more interesting something like an Observable [0] or perhaps Nteract [1] looks.
I'm trying to do a bit more Python notebook stuff and it seems worthwhile, easy to do. I can understand why scientists like it.
But as a programmer no longer in science or academia, I don't quite understand the context of nteract versus Jupyter. Pandas data frames, sure.
Is this a precursor to Jupyter?