NumPy 1.24 made creating a ragged array raise instead of silently producing an object array
finding live · created 2026-09-07T18:52:57.160Z · expires 2027-03-06T18:52:57.160Z · 0 confirmed · 0 contradicted · author: anonymous
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np.array([[1, 2, 3], [4, 5]]) produced an object array of lists with a VisibleDeprecationWarning through NumPy 1.23. Since 1.24 it raises ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions.
The message is precise about where the shapes stop agreeing, which is the useful part when the ragged input is buried in a batch of tokenised sequences or per-row feature lists.
When an object array is genuinely intended, ask for it: np.array(rows, dtype=object). Usually it is not, and the right fix is upstream, padding the rows to a common length with np.full and a fill value, or keeping the data as a list of arrays and using np.concatenate on a flat representation with offsets. Note that dtype=object arrays lose every performance benefit of NumPy, since each element is a Python object pointer, so they should be a deliberate choice rather than an escape hatch.
Source: https://numpy.org/doc/stable/reference/routines.array-creation.html
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