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points by librasteve 4 days ago | 0 comments

I’m all in favour of making spreadsheets better, with code friendly formulas. Here’s one I’m working on - somewhat earlier in dev cycle than grist and while I did consider Python (and lua) for the formula DSL decided to cook up my own.

All feedback good and bad v welcome.

https://omasheet.org

[–] StableAlkyne 4 days ago

The main problem with spreadsheets at the business level is that they're the root cause of the Data Swamp failure mode.

People fool themselves into thinking "it's tabular, therefore it's structured" then go on to do assinine shit like putting bonus calculations in random cells, or adding extra tables on the same sheet.

The big value B2B is never going to be whether it has Python. The big value is being able to pull that data and the calculations out of Excel.

[–] librasteve 4 days ago

I agree 100% with that. And I suggest that LLMs make it much easier to “pull out” business calculations. Maybe into SQL with a custom Python script even :-).

For 41 years Excel has been the dominant way to mess with numbers in a grid. Google Sheets and Apple Numbers are really just me too players, albeit with their niches. LibreOffice struggles imo since its main claim is to be fully Excel compatible but there are so many ancient Excel sheets that fail in practice (VBScript?).

I think that there will continue to be a need for folks to mess with numbers in a grid … more between a super calculator and an interactive dataset. I could have chosen a DB vernacular for Omasheet - DuckDB does this for Polars - but that lacks some of the numeric purity of the sheet. So I have gone for the core Polars query model - closer to Arrow columnar data (parquet), streaming support, lowered calculations, lazy execution … but without the DB abstraction layer.

[–] StableAlkyne 3 days ago

Yeah, it's definitely going to be around for a long time. For the average non-coder, it's probably the most logical way to structure a calculation.

Maybe a controversial take, but IMO Except is the most successful and most popular GUI framework in history. The Internet could die today, and tomorrow the world would go back to spreadsheet programs for business tasks.

[–] whizzter 3 days ago

"random business calculations in random cells" is what a lot of quick business stuff lives on, putting a few formulas instead of an entire application is what you need (not even AI's can keep up with that once you're used to it).

The danger as always, is when it becomes the entrenched business process, and as you say, being able to automatically pull out the logic when formalizing it is the win.

[–] whizzter 3 days ago

I kind-of like it, spontaneously taking tables from CSV files doesn't seem to be there (there's a mention of parquet via dataframes so perhaps it's supported implicitly, but maybe add that documentation?).

I see that import/export pipelines are there, so transform pipelines should be simple, and I guess that's a quick-n-dirty usecase it's there for (the spreadsheet part of "taco-bell programming" ala Dziuba ?).

Personally though for me often, the spreadsheet's interactive and quick recalcs is the important part, the exploratority quick checks with numbers updating, now if it can take arbitrary sheets and get out all "unstructured" calculations so one can edit them more properly later it's a win, or am I missing other major usecases?

[–] librasteve 2 days ago

that a gap in the doc … as of today (in test) uses the Polars csv import same s parquet

still working out the use cases more thoroughly, for now i would say that they range from ad hoc calculations (like a quick thrown together Excel), though LLM workflows (markdown centric reports with numeric calculated tables) to 1GB+ dataset ingestion and interactive analysis

[–] WillAdams 4 days ago

Did you consider trying pyspread?

[–] librasteve 4 days ago

not really … I did play with pyspread some time ago tbh i was put off by the basic UI and rather childlike website (sorry I know that’s not really fair, but I am a human). I’ll definitely take a fresh look at it now you mentioned it. curious: what are the standout features of pyspread that you like?

oh and omasheet is Rust and uses Polars so I am working with that rather than NumPy SciPy

[–] WillAdams 4 days ago

It supports Python and is Pythonic and being free, matches my budget.