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POLARS
Extremely fast Query Engine for DataFrames, written in Rust
MIT
ABOUT
Data scientists and engineers struggle with slow DataFrame operations and memory limitations when processing large datasets on a single machine. Polars solves this by providing a Rust-powered, vectorized query engine that achieves 30x+ performance over pandas, supports out-of-core streaming, and utilizes all CPU cores without extra configuration — all with zero required dependencies.
INSTALL
pip install polarsINTEGRATION GUIDE
1. High-performance ETL and data wrangling on single machines
2. Streaming analytics for datasets larger than available RAM
3. Replacing pandas in data science pipelines for faster query execution
4. Building data applications in Python, Rust, R, or Node.js
TAGS
dataframedata-processingrustpythonanalyticsetlquery-enginestreamingopen-source