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https://issues.apache.org/jira/browse/ARROW-15765?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17496792#comment-17496792
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Alessandro Molina edited comment on ARROW-15765 at 2/23/22, 2:14 PM:
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Probably exposing {{name}} in {{CDataType}} would be a starting point. For
nested types like lists, struct etc.. we will have to dive into the sub_fields,
but for basic types the {{name}} might already allow to easily identify the
type. (We could already use {{id}} but I guess that's less immediately
understandable)
was (Author: amol-):
Probably exposing `name` in `CDataType` would be a starting point. For nested
types like lists, struct etc.. we will have to dive into the sub_fields, but
for basic types the `name` might already allow to easily identify the type. (We
could already use `id` but I guess that's less immediately understandable)
> [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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