fix: accept numpy integers as chunk sizes - #4257
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d-v-b merged 3 commits intoAug 12, 2026
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`normalize_chunks_nd` dispatches the scalar convenience form on `numbers.Integral`, but `normalize_chunks_1d` narrowed on `int`. Numpy integer scalars satisfy the former and not the latter, so a per-dimension numpy integer passed the outer dispatch and then fell into the branch meant for explicit per-dimension chunk sequences, where `list(chunks)` raised `TypeError: 'numpy.int64' object is not iterable`. Numpy integers arise naturally whenever a chunk shape is computed rather than written as a literal, since numpy reductions and elementwise ops yield numpy scalars. Narrow on `numbers.Integral` and coerce with `int()`, matching the caller and the sequence branch, which already accepted `Integral` elements. Move the `-1` sentinel check inside that branch. It previously ran on the raw input, so a numpy array chunk specification made `chunks == -1` return an array and raise an ambiguous-truth-value error; rectilinear specs given as numpy arrays now work. A chunk specification that is neither an integer nor iterable now names the offending value and its type instead of surfacing an opaque "object is not iterable" from `list(chunks)`. Fixes zarr-developers#4255 Assisted-by: ClaudeCode:claude-opus-5
d-v-b
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August 12, 2026 19:41
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #4257 +/- ##
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Coverage 94.00% 94.00%
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Files 91 91
Lines 12791 12795 +4
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+ Hits 12024 12028 +4
Misses 767 767
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this is an internal bugfix so I'm going to self-merge. |
ieivanov
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Aug 13, 2026
…zarr cap (#313) ultrack 0.8.0 resolves both problems we filed against 0.7.2: * royerlab/ultrack#283 -- the `pyarrow<20` cap is gone (now `pyarrow>=16.1.0`), so pyarrow moves 19.0.1 -> 25.0.1 and GHSA-rgxp-2hwp-jwgg no longer applies. That was the one alert #310 could not clear; biahub is now at zero open Dependabot alerts. * royerlab/ultrack#284 -- large_chunk_size casts its computed chunk sizes to plain ints instead of leaking np.int64, so zarr no longer needs capping below 3.3. Verified directly: on zarr 3.3.0 it returns (1, 3, 16, 16) as four Python ints and array_apply completes. Note the zarr side is fixed but unreleased -- zarr-developers/zarr-python#4257 is merged, yet PyPI is still on the unpatched 3.3.0. Dropping the cap is safe because the fix reaching us comes from ultrack's casting, not from zarr; ultrack was the only caller in our tree passing numpy integer chunk sizes. Also worth recording: pyarrow 25 ships cp314 wheels, so it is no longer what blocks Python 3.14. ultrack 0.8 declares `requires-python <3.14` instead, which is at least an explicit bound rather than a source build that fails on a missing Arrow C++ toolchain. 126 passed, 1 skipped -- including the track tests that zarr 3.3.0 broke under ultrack 0.7.2. Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
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Summary
Fixes #4255 by handling numpy ints correctly in chunk input normalization. written by claude. see the original PR here: d-v-b#288
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TODO
docs/user-guide/*.mdchanges/