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https://issues.apache.org/jira/browse/ARROW-16081?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17515312#comment-17515312
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Jonathan Kenyon commented on ARROW-16081:
-----------------------------------------
That is fair - I am maintaining some code I didn't write so I don't necessarily
understand the motivation behind using the buffers directly. I have managed to
solve my issue (and now understand why zero copy isn't an option for bool
values). I actually think using the buffers may be overkill in this case and
will look at instead using flattened arrays which I can reshape/establish views
over.
> Incorrect results when reading a buffer of boolean values
> ---------------------------------------------------------
>
> Key: ARROW-16081
> URL: https://issues.apache.org/jira/browse/ARROW-16081
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 7.0.0
> Environment: Ubuntu 20.04, Python 3.8.10, pyarrow==7.0.0
> Reporter: Jonathan Kenyon
> Priority: Major
>
> The following reproducer demonstrates that a buffer of boolean values is not
> correctly recovered when using pyarrow.
> {code:python}
> import pyarrow.parquet as pq
> import pyarrow as pa
> import numpy as np
> if __name__ == "__main__":
> data = np.array([True, False, True, False], dtype=bool)
> length = len(data)
> buf = pa.py_buffer(data)
> array = pa.Array.from_buffers(pa.bool_(), length, [None, buf])
> np.testing.assert_array_equal(data, array.to_numpy(zero_copy_only=False))
> {code}
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