[
https://issues.apache.org/jira/browse/ARROW-15765?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17496876#comment-17496876
]
Weston Pace commented on ARROW-15765:
-------------------------------------
Perhaps I am missing some key piece but don't all arrays (Int32Array,
Int64Array, etc.) extend Array which already has a type field?
{noformat}
cdef class Array(_PandasConvertible):
cdef:
shared_ptr[CArray] sp_array
CArray* ap
cdef readonly:
DataType type
{noformat}
So couldn't you do `array1.type`?
{noformat}
>>> x = pa.array([1, 2, 3])
>>> x.type
DataType(int64)
{noformat}
> [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.
--
This message was sent by Atlassian Jira
(v8.20.1#820001)
