[GitHub] [spark] zero323 commented on pull request #37369: [SPARK-39942][PYTHON][PS] Need to verify the input nums is integer in nsmallest func

[GitBox <gi...@apache.org>]

zero323 commented on PR #37369:
URL: https://github.com/apache/spark/pull/37369#issuecomment-1202088146

   > is there some method to enforce the input type checking? @zero323
   
   There exist some 3rd party attempts, but as far as I'm aware none is particularly popular and well maintained (`pydantic` included `validate_arguments` on provisional basis, but I haven't seen it used in the wild).
   
   Runtime checking is officially out-of-scope for core `typing` (`@typing.runtime_checkable` is a bit different beast) so it wouldn't expect any solution emerging there.
   
   Personally, I'd say that the current behavior is acceptable ‒ there is no significant divergence compared to Pandas:
   
   ```python
   >>> df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [3, 4, 5, 6]}, columns=['A', 'B'])
   >>> df.groupby(['A'])['B'].nsmallest(5.5)
   Traceback (most recent call last):
   ...
   TypeError: cannot do positional indexing on Int64Index with these indexers [True] of type bool
   ```
   
   and the error message is meaningful enough.


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