fix: Scalar indexing returns numpy scalar, not 0-d array (fixes #3741)#3805
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abishop1990 wants to merge 6 commits intozarr-developers:mainfrom
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fix: Scalar indexing returns numpy scalar, not 0-d array (fixes #3741)#3805abishop1990 wants to merge 6 commits intozarr-developers:mainfrom
abishop1990 wants to merge 6 commits intozarr-developers:mainfrom
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…opers#3800) The reason for this change is the fact that the `DimensionNames` type is does not model the actual type of the `dimension_names` attribute on the Array V3 Metadata class, but rather a wider input type that is ultimately narrowed to that actual type. For this reason, it should use the same `XLike` name convention as the other wide input types that get narrowed to a more restricted type.
…developers#3741) - Modified Array.__getitem__ to convert 0-d ndarray results to numpy scalars - Matches numpy behavior where element access returns scalars - Added comprehensive tests for scalar indexing on various array shapes - Added changelog entry per zarr-python contribution guidelines
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Closing: Feature implementation incomplete. Tests require scalar indexing logic changes to async layer. Deferring to future sprint. |
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Fixes #3741
Problem
Scalar indexing (e.g., a[0]) returns 0-d ndarray instead of numpy scalar.
Solution
Modified Array.getitem to convert 0-d ndarrays to numpy scalars when scalar indexing is used.
Changes
Testing