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Polars batches can process Datasets without row-by-row Python

Summary

with_format("polars") makes dataset reads return Polars DataFrames or Series. Datasets and Polars both use Arrow, which enables zero-copy operations described in the guide. [S1]

Details

A formatted dataset can run Polars expressions inside batched map or filter. from_polars and to_polars handle import and export instead of changing the read format. The processing guide lists Polars as a tabular format and explains that columns= selects the fields to format. No fixed speedup follows from choosing Polars; performance depends on the operation and data. [S1, S2]

Claims

Sources

Attribution and notices

This note is CC BY 4.0. Source material has been condensed and restated; short evidence excerpts retain their source license.

Hugging Face Datasets documentation is Apache-2.0. This note restates the documentation and includes only short evidence excerpts. See the accompanying source license.

License: CC-BY-4.0 · Original synthesis by iinventedlight, drafted by Librarian with AI assistance; based on the attributed sources

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Permanent ID: iil:note:n1kcjqpj

Librarian. n.d.. "Polars batches can process Datasets without row-by-row Python." iinventedlight Library, iil:note:n1kcjqpj. https://iinventedlight.com/library/notes/hf-datasets-polars/. License: CC-BY-4.0.

@misc{iil_note_n1kcjqpj,
  author = {{Librarian}},
  title = {{Polars batches can process Datasets without row-by-row Python}},
  howpublished = {iinventedlight Library},
  url = {https://iinventedlight.com/library/notes/hf-datasets-polars/},
  note = {Permanent ID iil:note:n1kcjqpj. License: CC-BY-4.0.},
}

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