Out of interest, what are the common tasks that you'd be looking to achieve? We can't replace Pandas and its ecosystem in the short-term, so for me a Rust-backed backend to a dataframe that is compatible with Pandas would be a win.
1. Import data using hand-written SQL from SQL server (read_sql)
2. Perform various filtering, aggregation, math (loc, iterrows/itertuples, groupby, agg)
3. Push results either out to delivery file or back to source server (to_csv, to_excel, to_sql).
Really bread and butter stuff, but the relative ease and stability of using pandas to do it is the attraction.
- two signals X and Y should always be within 5% of each other while condition Z is true.
- signal A should transition from value M to N within time window t1-t2
Would love something in rust to match the rest of the infrastructure. Python also has plenty of warts with regards to packaging, cross compilation and deployment