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Posted to issues@arrow.apache.org by "Wes McKinney (JIRA)" <ji...@apache.org> on 2019/06/24 17:37:00 UTC
[jira] [Comment Edited] (ARROW-5208) [Python] Inconsistent
resulting type during casting in pa.array() when mask is present
[ https://issues.apache.org/jira/browse/ARROW-5208?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16871541#comment-16871541 ]
Wes McKinney edited comment on ARROW-5208 at 6/24/19 5:36 PM:
--------------------------------------------------------------
Cython is a very limited language. In {{C++++}} we are able to take advantage of many language features like {{C++11}} lambdas and code generation using templates that are not possible in Cython, and would yield a lot of code duplication and most likely worse performance.
BTW, I highly recommend learning {{C+++11+}}. I believe we are only going to see _more_ Python packages that are a hybrid of {{C+++11+}} (or {{C++14/17}}) and Python, with thin bindings either in Cython or pybind11.
was (Author: wesmckinn):
Cython is a very limited language. In {{C++++}} we are able to take advantage of many language features like {{C++11}} lambdas and code generation using templates that are not possible in Cython, and would yield a lot of code duplication and most likely worse performance.
BTW, I highly recommend learning {{C+++11+}}. I believe we are only going to see _more_ Python packages that are a hybrid of {{C+++11+}} (or {{C++14/17}}) and Python, with thin bindings either in Cython or pybind11.
> [Python] Inconsistent resulting type during casting in pa.array() when mask is present
> --------------------------------------------------------------------------------------
>
> Key: ARROW-5208
> URL: https://issues.apache.org/jira/browse/ARROW-5208
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.13.0
> Reporter: Artem KOZHEVNIKOV
> Assignee: Wes McKinney
> Priority: Major
> Labels: pull-request-available
> Fix For: 0.14.0
>
> Time Spent: 20m
> Remaining Estimate: 0h
>
> I would expect Int64Array type in all cases below :
> {code:java}
> >>> pa.array([4, None, 4, None], mask=np.array([False, True, False, True]))
> <pyarrow.lib.Int64Array object at 0x91fad3a98> [4, null, 4, null ]
> >>> pa.array([4, None, 4, 'rer'], mask=np.array([False, True, False, True]))
> <pyarrow.lib.Int64Array object at 0x9201f23b8> [4, null, 4, null ]
> >>> pa.array([4, None, 4, 3.], mask=np.array([False, True, False, True])) <pyarrow.lib.DoubleArray object at 0x91fab7638> [ 4, null, 4, null ]{code}
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