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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