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polars-bio is a Python library for genomics built on top ofpolars,Apache Arrow andApache DataFusion.It provides a DataFrame API for genomics data and is designed to be blazing fast, memory efficient and easy to use.

• optimized forperformance and memoryefficiency for large-scale genomics datasets analyses both when reading input data and performing operations
• popular genomicsoperations with a DataFrame API (bothPandas andpolars)
• SQL-powered bioinformatic data querying or manipulation
• native parallel engine powered by Apache DataFusion andsequila-native
• out-of-core/streaming processing (for data too large to fit into a computer's main memory) withApache DataFusion andpolars
• support forfederated andstreamed reading data fromcloud storages (e.g. S3, GCS) withApache OpenDAL enabling processing large-scale genomics data without materializing in memory
• zero-copy data exchange withApache Arrow
• bioinformatics fileformats withnoodles andexon
• fast overlap operations withCOITrees: Cache Oblivious Interval Trees
• pre-built wheel packages forLinux,Windows andMacOS (arm64 andx86_64) available onPyPI

If you usepolars-bio in your work, please cite:

@article {Wiewiorka2025.03.21.644629,author ={Wiewiorka, Marek and Khamutou, Pavel and Zbysinski, Marek and Gambin, Tomasz},title ={polars-bio - fast, scalable and out-of-core operations on large genomic interval datasets},elocation-id ={2025.03.21.644629},year ={2025},doi ={10.1101/2025.03.21.644629},publisher ={Cold Spring Harbor Laboratory},URL ={https://www.biorxiv.org/content/early/2025/03/25/2025.03.21.644629},eprint ={https://www.biorxiv.org/content/early/2025/03/25/2025.03.21.644629.full.pdf},journal ={bioRxiv}}

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