I'm specifically referring to the use case of creating explorable apps. Most data scientists I know would love a way of, say, building a map with a few input controls that alter the data or presentation (colors, layers, filtering, aggregation).
I'm currently working on a JS-powered geospatial exploration app that is meant to be run either standalone or embedded into a Jupyter notebook. We often run into questions around how much the embeddable app should be scriptable or how much user control to allow. This would seemingly solve many of our needs.
Some years ago I tried (and admittedly failed) to do something similar (a Jupyter notebook as an app) when trying to build a domain specific application for water resource management - we ended up building a "classic" web application via Leaflet and Python at the backend.
The idea is intriguing, however it is non trivial to pass information from JS to Python and vice versa. You can do that, but it messes with Jupyter's event system and breaks the usual notebook workflow. Maybe this has changed for the better, but at that time this stuff (IPython widgets I think) was heavily in flux.
Yes, but neither shiny nor python (folium, etc) give us the level of customization or control via an actual JS bridge that this appears to.
That said, I tried to create a demo application and it seems like the require / exports / global situation isn't 100% yet. Any tips from the team on what to do here?
I'm currently working on a JS-powered geospatial exploration app that is meant to be run either standalone or embedded into a Jupyter notebook. We often run into questions around how much the embeddable app should be scriptable or how much user control to allow. This would seemingly solve many of our needs.