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About polars

P

polars

High-performance DataFrame library for Python ETL, analytics

polars is an agent skill for working with Polars, a high-performance columnar DataFrame library for Python and Rust with Arrow interoperability. It covers its expression-based API, its lazy evaluation framework and fast data manipulation, for efficient processing, migration from pandas, and data pipeline optimisation. The skill was reviewed against the official stable documentation and the native Polars 1.44.2 release. Local regression tests cover the corrected APIs and scientific failure cases. Cloud, GPU, BigQuery and remote database recipes are illustrative and need provider setup before they run. Fragments that use undefined columns, paths or placeholders must be adapted to your dataset before use. The installation guide recommends the verified stable release, Polars 1.44.2. Use it for ETL and analytics on tabular data, when a pandas script is too slow or too memory-hungry, or when you are moving a pandas workflow to Polars. It is part of the k-dense-ai scientific agent skills repository on GitHub, which has about 49,600 stars. The listing shows it as free, and it has about 1,900 installs. Its security audits show passes from Gen Agent Trust Hub, Socket and Snyk.

View polarsAll AI Skills apps
Price
Free
Made by
k-dense-ai
Category
AI Skills
Website
github.com/k-dense-ai/scientific-agent-skills/polars