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  • [Python-announce] [ANN] PyData/Sparse 0.18.0 released

    From Hameer Abbasi@hameerabbasi@yahoo.com to comp.lang.python.announce on Thu Feb 19 07:39:08 2026
    From Newsgroup: comp.lang.python.announce

    PyData/Sparse is a library providing N-dimensional sparse arrays for the PyData ecosystem.

    This release focuses on expanded array API compatibility, developer experience, and QoL fixes.

    Repo: https://github.com/pydata/sparse
    Docs: https://sparse.pydata.org/en/0.18.0/
    Issue Tracker: https://github.com/pydata/sparse/issues

    Changelog

    What's Changed
    * Implementing `repeat` function by @prady0t in https://github.com/pydata/sparse/pull/875
    * Adding `tile` function by @prady0t in https://github.com/pydata/sparse/pull/880
    * Setting `boolean indexing` flag to False by @prady0t in https://github.com/pydata/sparse/pull/884
    * Adding `unstack` function by @prady0t in https://github.com/pydata/sparse/pull/883
    * Fixing `check_zero_fill_value` by @prady0t in https://github.com/pydata/sparse/pull/886
    * Running codecov only when tests pass by @prady0t in https://github.com/pydata/sparse/pull/887
    * Adding `diff` function by @prady0t in https://github.com/pydata/sparse/pull/888
    * Making benchmarking tests deterministic by @prady0t in https://github.com/pydata/sparse/pull/891
    * Migration guide by @hameerabbasi in https://github.com/pydata/sparse/pull/898 * Lock mlir to python <3.14 by @prady0t in https://github.com/pydata/sparse/pull/906
    * feat: Add sparse.interp function for numba backend by @peanutfun in https://github.com/pydata/sparse/pull/903
    * Update Finch notebook by @mtsokol in https://github.com/pydata/sparse/pull/911
    * BUG: asarray: fix default format for `SparseArray` input by @lucascolley in https://github.com/pydata/sparse/pull/918
    * [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci[bot] in https://github.com/pydata/sparse/pull/916
    * BLD/DEV/CI: better Pixi setup by @lucascolley in https://github.com/pydata/sparse/pull/920
    * ENH: transition to SciPy sparse arrays from matrices by @lucascolley in https://github.com/pydata/sparse/pull/919
    * DEV/CI: use Pixi for examples, notebooks, and xp-tests by @lucascolley in https://github.com/pydata/sparse/pull/922

    New Contributors
    * @peanutfun made their first contribution in https://github.com/pydata/sparse/pull/903
    * @lucascolley made their first contribution in https://github.com/pydata/sparse/pull/918

    Full Changelog: https://github.com/pydata/sparse/compare/0.17.0...0.18.0
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