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https://issues.apache.org/jira/browse/ARROW-15765?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17496784#comment-17496784
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Vibhatha Lakmal Abeykoon commented on ARROW-15765:
--------------------------------------------------

Ah Yes you're right. Mixed up with the C++ naming. 

To expose this one, I guess we have to extend the classes
{code:java}
cdef class Int32Array(IntegerArray):
   pass{code}
 to something like 
{code:java}
cdef class Int32Array(IntegerArray):
   cdef shared_ptr[CDataType] get_type(){code}
 And expose it as property to Python? 

Or is there a better approach for this?

> [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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