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https://issues.apache.org/jira/browse/ARROW-564?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16447731#comment-16447731
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ASF GitHub Bot commented on ARROW-564:
--------------------------------------
pitrou commented on a change in pull request #1931: ARROW-564 [Python] Add
support for return zero copy NumPy arrays
URL: https://github.com/apache/arrow/pull/1931#discussion_r183309840
##########
File path: python/pyarrow/tests/test_array.py
##########
@@ -83,6 +83,33 @@ def test_long_array_format():
assert result == expected
+def test_to_numpy_zero_copy():
Review comment:
This function isn't actually testing the zero-copy part. You should mutate
the result Numpy array and check the original Arrow array is mutated (of
course, the fact we're able to get a mutable Numpy array from an Arrow array
could be seen as a bug).
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> [Python] Add methods to return vanilla NumPy arrays (plus boolean mask array
> if there are nulls)
> ------------------------------------------------------------------------------------------------
>
> Key: ARROW-564
> URL: https://issues.apache.org/jira/browse/ARROW-564
> Project: Apache Arrow
> Issue Type: New Feature
> Components: Python
> Reporter: Wes McKinney
> Priority: Major
> Labels: beginner, pull-request-available
> Fix For: 1.0.0
>
>
> At the moment, for {{pyarrow.Array}} instances, we have a method called
> {{to_pandas}}. While this method returns NumPy Arrays, it returns them in the
> form that Pandas would use them in its {{Series}}. The difference here is
> visible for example in the case of integers with null values. For Pandas, we
> convert it into a float array and set all entries to NaN where we have null
> entries in the Arrow array. For vanilla NumPy arrays, we would return a tuple
> of a valid bytemap (not bitmap!) and a values array. The values array in this
> case should simply be a view on the underlying Arrow buffer.
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