[jira] [Commented] (ARROW-17901) [Python] pyarrow missing py.typed marker file

["Alenka Frim (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-17901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17612220#comment-17612220 ] 

Alenka Frim commented on ARROW-17901:
-------------------------------------

I think Will gave a great answer on GitHub issues: [https://github.com/apache/arrow/issues/14291], {{-DARROW_INSTALL_NAME_RPATH=OFF}} is what came to my mind also.

> [Python] pyarrow missing py.typed marker file
> ---------------------------------------------
>
>                 Key: ARROW-17901
>                 URL: https://issues.apache.org/jira/browse/ARROW-17901
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>            Reporter: Matteo Santamaria
>            Priority: Minor
>
> I understand that, in general, {{pyarrow}} does not support type hints. However, I think it is still sensible to add a {{py.typed}} marker file to the library. Let me demonstrate why,
> {code:java}
> $ pip install mypy pyarrow {code}
> {code:java}
> # test.py
> import pyarrow as pa
>  
> table = pa.Table()
>  
> reveal_type(table) {code}
> {code:java}
> $ mypy test.py
> test.py:1: error: Skipping analyzing "pyarrow": module is installed, but missing library stubs or py.typed marker
> test.py:1: note: See https://mypy.readthedocs.io/en/stable/running_mypy.html#missing-imports
> test.py:5: note: Revealed type is "Any"
> Found 1 error in 1 file (checked 1 source file) {code}
> Note that {{mypy}} identifies {{table}} as being an {{Any}} type, when obviously it is a {{{}Table{}}}. If we include a {{py.typed}} file, {{mypy}} will be able to make these trivial inferences. The motivating example is this,
> {code:java}
> @overload
> def from_arrow(a: pa.Table) -> DataFrame:
>     ...
> @overload
> def from_arrow(a: pa.Array | pa.ChunkedArray) -> Series:
>     ...
> def from_arrow(a: pa.Table | pa.Array | pa.ChunkedArray) -> DataFrame | Series:
>     pass {code}
> The problem is that since all of {{{}pa.Table{}}}, {{{}pa.Array{}}}, and {{pa.ChunkedArray}} are determined to be {{{}Any{}}}, the overloads effectively become 
> {code:java}
> @overload
> def from_arrow(a: Any) -> DataFrame:
>     ...
> @overload
> def from_arrow(a: Any) -> Series:
>     ... {code}
> and {{mypy}} complains that overload 2 is covered entirely by overload 1.
>  
> I tried to test what adding a {{py.typed}} file would do, but I ran into compilation issues. I was hoping someone with a little more experience here could quickly test this out for me :)



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