feat: close upstream coverage gaps for DataFusion 55.1.0 - #1763

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timsaucer wants to merge 16 commits into

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timsaucer:feat/upstream-coverage-gaps

Commits on Sep 25, 2026

feat: expose any_value, array math, array_first, and missing Spark functions

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5a0e79d
feat: add rand, substring_index, file metadata functions, and distinct kwargs

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8027fcb
feat(spark): add pyspark aliases and optional-length substr

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97e6031
feat: accept optional arguments upstream supports on trim, array_to_string, substr

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e8c2192
feat: add DataFrame.fill_nan

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2747573
feat: add null_treatment to lead and lag

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24764bd
feat: add show_statistics, analyze_level, and analyze_categories to explain

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b035c97
fix: keep existing options when chaining aggregate and window builders

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d2ac890
feat: accept a bare PyCapsule in ScalarUDF and WindowUDF

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97e5905
chore: export TableProviderFactory from datafusion.catalog

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d53a255
docs(skill): record DataFrame.to_string as not needing exposure

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5d43576
fix: resolve the _PyCapsule type alias so capsule overloads type-check

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f6d0478
fix: keep an explicit window frame that equals the default when chaining

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6345b17
fix: leave lead and lag null_treatment unset by default

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73b052d
fix: keep existing window function options in over()

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8173554
feat: accept native ints and a single argument in range and gen_series

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96f990b

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feat: close upstream coverage gaps for DataFusion 55.1.0 - #1763

feat: close upstream coverage gaps for DataFusion 55.1.0#1763
timsaucer wants to merge 16 commits into
apache:mainfrom
timsaucer:feat/upstream-coverage-gaps

Commits on Sep 25, 2026

feat: expose any_value, array math, array_first, and missing Spark functions

feat: add rand, substring_index, file metadata functions, and distinct kwargs

feat(spark): add pyspark aliases and optional-length substr

feat: accept optional arguments upstream supports on trim, array_to_string, substr

feat: add DataFrame.fill_nan

feat: add null_treatment to lead and lag

feat: add show_statistics, analyze_level, and analyze_categories to explain

fix: keep existing options when chaining aggregate and window builders

feat: accept a bare PyCapsule in ScalarUDF and WindowUDF

chore: export TableProviderFactory from datafusion.catalog

docs(skill): record DataFrame.to_string as not needing exposure

fix: resolve the _PyCapsule type alias so capsule overloads type-check

fix: keep an explicit window frame that equals the default when chaining

fix: leave lead and lag null_treatment unset by default

fix: keep existing window function options in over()

feat: accept native ints and a single argument in range and gen_series