# Polars 1.37.0 — Python Polars 1.37.0

- Product: Polars (https://whatsnew.fyi/product/polars)
- Vendor: Polars
- Date: 2026-01-10
- Version: 1.37.0
- Original notes: https://github.com/pola-rs/polars/releases/tag/py-1.37.0
- Permalink: https://whatsnew.fyi/product/polars/releases/1.37.0

What's New is an index, not a publisher: every entry below links to the vendor's own release notes, which are the authoritative source. Entries are labelled where they are hand-curated sample data, pre-releases, or drawn from a secondary source such as a developer blog.

Reuse: the summaries, labels and curation here are © What's New. Quote freely with attribution and a link back; wholesale republication of the corpus is not permitted — terms: https://whatsnew.fyi/terms. The vendors' own release notes remain their publishers'.

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- **added** — Add new pl.PartitionBy API
- **added** — Add lazy collect_all
- **added** — Add nulls support for rolling_mean_by
- **added** — Expose record batch size in {sink,write}_ipc
- **added** — Add null_on_oob parameter to expr.get
- **added** — Support streaming IPC scan from S3 object store
- **added** — Add pl.Expr.(min|max)_by
- **added** — Add Series sql method for API consistency
- **added** — Support Binary and Decimal in arg_(min|max)
- **added** — Add missing Series.arr.mean
- **changed** — Speed up SQL interface ORDER BY clauses
- **changed** — Add fast kernel for is_nan and use it for numpy NaN->null conversion
- **changed** — New streaming NDJSON sink pipeline
- **changed** — New streaming CSV sink pipeline
- **changed** — Replace ryu with faster zmij
- **changed** — Use new sink pipeline for write/sink_ipc
- **changed** — Improve handling of unqualified SQL JOIN columns that are ambiguous
- **changed** — Drop Python 3.9 support
- **fixed** — Make struct.with_fields data model coherent
- **fixed** — Ensure chunk consistency in in-memory join

##### 🚀 Performance improvements

- Speed up `SQL` interface "ORDER BY" clauses (#26037)
- Add fast kernel for is\_nan and use it for numpy NaN->null conversion (#26034)
- Optimize ArrayFromIter implementations for ObjectArray (#25712)
- New streaming NDJSON sink pipeline (#25948)
- New streaming CSV sink pipeline (#25900)
- Dispatch partitioned usage of `sink_*` functions to new-streaming by default (#25910)
- Replace ryu with faster zmij (#25885)
- Reduce memory usage for .item() count in grouped first/last (#25787)
- Skip schema inference if schema provided for `scan_csv/ndjson` (#25757)
- Add width-aware chunking to prevent degradation with wide data (#25764)
- Use new sink pipeline for write/sink\_ipc (#25746)
- Reduce memory usage when scanning multiple parquet files in streaming (#25747)
- Don't call cluster\_with\_columns optimization if not needed (#25724)

##### ✨ Enhancements

- Add new `pl.PartitionBy` API (#26004)
- ArrowStreamExportable and sink\_delta (#25994)
- Release musl builds (#25894)
- Implement streaming decompression for CSV `COUNT(*)` fast path (#25988)
- Add nulls support for rolling\_mean\_by (#25917)
- Add lazy `collect_all` (#25991)
- Add streaming decompression for NDJSON schema inference (#25992)
- Improved handling of unqualified SQL `JOIN` columns that are ambiguous (#25761)
- Drop Python 3.9 support (#25984)
- Expose record batch size in `{sink,write}_ipc` (#25958)
- Add `null_on_oob` parameter to `expr.get` (#25957)
- Suggest correct timezone if timezone validation fails (#25937)
- Support streaming IPC scan from S3 object store (#25868)
- Implement streaming CSV schema inference (#25911)
- Support hashing of meta expressions (#25916)
- Improve `SQLContext` recognition of possible table objects in the Python globals (#25749)
- Add pl.Expr.(min|max)\_by (#25905)
- Improve MemSlice Debug impl (#25913)
- Implement or fix json encode/decode for (U)Int128, Categorical, Enum, Decimal (#25896)
- Expand scatter to more dtypes (#25874)
- Implement streaming CSV decompression (#25842)
- Add Series `sql` method for API consistency (#25792)
- Mark Polars as safe for free-threading (#25677)
- Support Binary and Decimal in arg\_(min|max) (#25839)
- Allow Decimal parsing in str.json\_decode (#25797)
- Add `shift` support for Object data type (#25769)
- Add missing `Series.arr.mean` (#25774)
- Allow scientific notation when parsing Decimals (#25711)

##### 🐞 Bug fixes

- Release GIL on collect\_batches (#26033)
- Missing buffer update in String is\_in Parquet pushdown (#26019)
- Make `struct.with_fields` data model coherent (#25610)
- Incorrect output order for order sensitive operations after join\_asof (#25990)
- Use SeriesExport for pyo3-polars FFI (#26000)
- Add pl.Schema to type signature for DataFrame.cast (#25983)
- Don't write Parquet min/max statistics for i128 (#25986)
- Ensure chunk consistency in in-memory join (#25979)
- Fix varying block metadata length in IPC reader (#25975)
- Implement collect\_batches properly in Rust (#25918)
- Fix panic on arithmetic with bools in list (#25898)
- Convert to index type with strict cast in some places (#25912)
- Empty dataframe in streaming non-strict hconcat (#25903)
- Infer large u64 in json as i128 (#25904)
- Set http client timeouts to 10 minutes (#25902)
- Correct lexicographic ordering for Parquet BYTE\_ARRAY statistics (#25886)
- Raise error on duplicate `group_by` names in `upsample()` (#25811)
- Correctly export view buffer sizes nested in Extension types (#25853)
- Fix `DataFrame.estimated_size` not handling overlapping chunks correctly (#25775)
- Ensure Kahan sum does not introduce NaN from infinities (#25850)
- Trim excess bytes in parquet decode (#25829)
- Fix panic/deadlock sinking parquet with rows larger than 64MB estimated size (#25836)
- Fix quantile `midpoint` interpolation (#25824)
- Don't use cast when converting from physical in list.get (#25831)
- Invalid null count on int -> categorical cast (#25816)
- Update groups in `list.eval` (

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