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https://issues.apache.org/jira/browse/ARROW-15765?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17497856#comment-17497856
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Vibhatha Lakmal Abeykoon commented on ARROW-15765:
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[~jorisvandenbossche] the new typing generics look interesting. Is it practical
to adopt this now. I am referring to the Python versions we support now. Is it
wise to use it in the UDF integration and not do what I am suggesting to do in
this jira.
[~apitrou] Numba jit approach is nice and it looks like an advance feature for
UDFs someday. I will keep this in mind.
As [~westonpace] suggested, some of our main motivations are to support the
user and try to provide user friendly options when we write TPCx-BB queries and
similar applications. If the suggestion from [~jorisvandenbossche] to use
advance typing is feasible, is it wise to use that instead of doing this change
if it succeeds in solving our underlying problem.
> [Python] Extracting Type information from Python Objects
> --------------------------------------------------------
>
> Key: ARROW-15765
> URL: https://issues.apache.org/jira/browse/ARROW-15765
> Project: Apache Arrow
> Issue Type: Improvement
> Components: C++, Python
> Reporter: Vibhatha Lakmal Abeykoon
> Assignee: Vibhatha Lakmal Abeykoon
> Priority: Major
>
> When creating user defined functions or similar exercises where we want to
> extract the Arrow data types from the type hints, the existing Python API
> have some limitations.
> An example case is as follows;
> {code:java}
> def function(array1: pa.Int64Array, arrya2: pa.Int64Array) -> pa.Int64Array:
> return pc.call_function("add", [array1, array2])
> {code}
> We want to extract the fact that array1 is an `pa.Array` of `pa.Int32Type`.
> At the moment there doesn't exist a straightforward manner to get this done.
> So the idea is to expose this feature to Python.
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