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https://issues.apache.org/jira/browse/ARROW-9017?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17123950#comment-17123950
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Joris Van den Bossche commented on ARROW-9017:
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And comment from Ben: relevant recent addition:
{code}
Result<std::shared_ptr<Scalar>> Array::GetScalar(int64_t i) const;
{code}
> [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
> Priority: Major
>
> 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]
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