[openrisk]

Maybe its time to start fresh with a clean sheet? (Pun).

The spreadsheet paradigm is immensely intuitive and arguably the only alternative to the standard procedural programming currently in use in number crumching.

But therein lies also a major weakness when used for important tasks: hard to validate.

Once you further combine it with API calls and whatnot, the situation gets totally out of hand: how do you reproduce anything?

The landscape around user interfaces, computational capability and (most importantly) the ever deeper embedding of such tools in decision making suggests to start taking the humble spreadsheet seriously and maybe that requires going back to the drawing board.

[laffra]

I tried that exactly with PySheets by implementing the sheet in Python itself, rethinking how Jupyter Notebook would look if it treated the data science problem as a dependency graph rather than a linear storytelling document. See https://pysheets.app

[diggan]

https://news.ycombinator.com/item?id=40179566 - PySheets – Spreadsheet UI for Python (pysheets.app) - 287 points - 47 days ago - 74 comments

[Lukas1994]

IMO the better paradigm is coming from enterprise applications like Anaplan. Cells are not the right abstraction to work with numbers. Most of the time you work with multi-dimensional quantities (eg revenue by product, geography, month).

We’re working on a more approachable implementation of that paradigm at https://causal.app

[CPLX]

Seems to me that Airtable is pretty much what you’re talking about, and is spectacularly useful.