BUG: make duplicated hashtable test levels distinct - #66786
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test_duplicated_hashtable_impl instantiated a fresh default_rng(2) inside the comprehension, so every level drew the identical sequence and the MultiIndex collapsed to only n distinct label tuples. Reuse one generator across levels so the test exercises duplicate detection over a much wider input, as it did before pandas-dev#54209. Closes pandas-dev#66774
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Thanks for the pull request, @aryansk! It's linked to #66774, but that issue isn't assigned to you yet. To make sure two people don't unknowingly work on the same thing, we ask contributors to claim an issue first. Just comment |
| - Bug in :meth:`DataFrame.select_dtypes` with an :class:`~pandas.api.extensions.ExtensionDtype` subclass such as :class:`ArrowDtype` or :class:`DatetimeTZDtype` raising ``TypeError``, emitting a spurious ``UserWarning``, or selecting the wrong columns; passing such a class now selects every column whose dtype is an instance of that class (:issue:`65366`) | ||
| - Bug in :meth:`Series.transform` and :meth:`DataFrame.transform` where passing a list of duplicate function names did not raise :class:`errors.SpecificationError` (:issue:`54929`) | ||
| - Bug in ``register_option`` where registering an option whose name was a prefix of an existing option (e.g. ``"a.b"`` when ``"a.b.c"`` was already registered) silently overwrote the existing option's namespace instead of raising (:issue:`29242`) | ||
| - Fixed ``MultiIndex`` duplicate detection tests instantiating a fresh RNG for every level, so each level received identical code arrays and the index collapsed to only ``n`` distinct label tuples (:issue:`66774`) |
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You checked the box saying you had said which AI you used, but you didn't actually do that. |
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Thanks @jbrockmendel — two fixes:
Issue #66774 is now claimed via |
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closes BUG: test_duplicated_hashtable_impl generates identical codes for every MultiIndex level #66774
Tests added and passed if fixing a bug or adding a new feature
All code checks passed.
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doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.I have reviewed and followed all the contribution guidelines
I did not use AI to develop this pull request.
I used AI to develop this pull request. I prompted it to follow
AGENTS.md, I have reviewed and understood every change, and I have described above how I used it and exactly which tool, model version, and effort setting — e.g.claude opus 4.8 (xhigh), not justclaude.What this changes
test_duplicated_hashtable_implinstantiatednp.random.default_rng(2)inside the comprehension, so a new generator with the same seed was created on every iteration and each level received the identical code sequence. TheMultiIndexthen collapsed to onlyndistinct label tuples, so the test exercised duplicate detection over a far narrower input than intended (it regressed in #54209, which used to draw once per level from a shared RNG).This reuses a single generator across levels, restoring distinct codes per level (53 distinct tuples vs 6 for the same seed) while keeping the parametrized
keepassertions intact.How I used AI
I used an AI coding agent (opencode, Anthropic Claude model family) to help analyze the issue, verify the RNG behavior against a source build, and draft this change. I reviewed and understood the final diff (a one-line RNG refactor) and validated it by running the full
test_duplicates.pymodule against a local source build — all 51 tests pass.Closes: #66774