[
https://issues.apache.org/jira/browse/ARROW-9017?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Wes McKinney resolved ARROW-9017.
---------------------------------
Resolution: Fixed
Issue resolved by pull request 7519
[https://github.com/apache/arrow/pull/7519]
> [Python] Refactor the Scalar classes
> ------------------------------------
>
> Key: ARROW-9017
> URL: https://issues.apache.org/jira/browse/ARROW-9017
> Project: Apache Arrow
> Issue Type: Improvement
> Components: Python
> Reporter: Joris Van den Bossche
> Assignee: Krisztian Szucs
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.0.0
>
> Time Spent: 10h 10m
> Remaining Estimate: 0h
>
> The situation regarding scalars in Python is currently not optimal.
> We have two different "types" of scalars:
> - {{ArrayValue(Scalar)}} (and subclasses of that for all types): this is
> used when you access a single element of an array (eg {{arr[0]}})
> - {{ScalarValue(Scalar)}} (and subclasses of that for _some_ types): this is
> used when wrapping a C++ scalar into a python scalar, eg when you get back a
> scalar from a reduction like {{arr.sum()}}.
> And while we have two versions of scalars, neither of them can actually
> easily be used as scalar as they both can't be constructed from a python
> scalar (there is no {{scalar(1)}} function to use when calling a kernel, for
> example).
> I think we should try to unify those scalar classes? (which probably means
> getting rid of the ArrayValue scalar)
> In addition, there is an issue of trying to re-use python scalar <-> arrow
> conversion code, as this is also logic for this in the {{python_to_arrow.cc}}
> code. But this is probably a bigger change. cc [~kszucs]
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
