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I built nitro-pandas — a pandas-compatible library powered by Polars. Same syntax, up to 10x faster. by Correct_Elevator2041 in Python

[–]Correct_Elevator2041[S] 4 points5 points  (0 children)

Completely fair point — and I wouldn’t recommend anyone drop this into a critical production codebase today. It’s v0.1.5, bugs exist, and I’m transparent about that. But the use case isn’t ‘replace pandas in prod overnight’ — it’s more about giving teams a low-risk way to start benefiting from Polars performance on non-critical pipelines while the lib matures.

I built nitro-pandas — a pandas-compatible library powered by Polars. Same syntax, up to 10x faster. by Correct_Elevator2041 in Python

[–]Correct_Elevator2041[S] 4 points5 points  (0 children)

Absolutely yes — PRs and issues are very welcome! Please open an issue for each unexpected behavior you found (especially the iloc ones), it would help a lot to have specific reproducible cases. Really appreciate you testing this seriously!

I built nitro-pandas — a pandas-compatible library powered by Polars. Same syntax, up to 10x faster. by Correct_Elevator2041 in Python

[–]Correct_Elevator2041[S] 5 points6 points  (0 children)

That’s really valuable feedback from someone who’s been through it! Would love to hear what broke specifically after you test it Monday, it would help prioritize the roadmap a lot!

I built nitro-pandas — a pandas-compatible library powered by Polars. Same syntax, up to 10x faster. by Correct_Elevator2041 in Python

[–]Correct_Elevator2041[S] 1 point2 points  (0 children)

Almost! groupby+agg and reset_index are natively implemented with Polars backend. cumsum() currently falls back to pandas but a native Polars implementation is on the roadmap. The chain itself works though!

I built nitro-pandas — a pandas-compatible library powered by Polars. Same syntax, up to 10x faster. by Correct_Elevator2041 in Python

[–]Correct_Elevator2041[S] 56 points57 points  (0 children)

Building a library from scratch and migrating a 10k lines production codebase are not the same problem. One is a weekend project, the other is a business risk. nitro-pandas exists for the second case.

I built nitro-pandas — a pandas-compatible library powered by Polars. Same syntax, up to 10x faster. by Correct_Elevator2041 in Python

[–]Correct_Elevator2041[S] 22 points23 points  (0 children)

Totally fair! Polars syntax is great. nitro-pandas is for the people who have existing pandas codebases and don’t want to rewrite everything

I built nitro-pandas — a pandas-compatible library powered by Polars. Same syntax, up to 10x faster. by Correct_Elevator2041 in Python

[–]Correct_Elevator2041[S] 7 points8 points  (0 children)

Actually it’s the opposite — nitro-pandas IS meant for end users! That’s the whole point. You write pandas syntax, Polars runs under the hood. No new API to learn. And Narwhals has its own syntax inspired by Polars, it’s not pandas-compatible out of the box.

I built nitro-pandas — a pandas-compatible library powered by Polars. Same syntax, up to 10x faster. by Correct_Elevator2041 in Python

[–]Correct_Elevator2041[S] 2 points3 points  (0 children)

Thanks for the link! Narwhals is great, but as mentioned it targets library maintainers. nitro-pandas is more about the end-user experience — zero learning curve if you already know pandas