BryanCutler commented on issue #27165: [SPARK-28264][PYTHON][SQL] Support type 
hints in pandas UDF and rename/move inconsistent pandas UDF types
URL: https://github.com/apache/spark/pull/27165#issuecomment-573958567
 
 
   This looks pretty good to me @HyukjinKwon , but I have a couple concerns
   
   Using type hints can be a clear way to define the inputs/output of a UDF, 
but it might be problematic to be the only way a user can make a PandasUDF. 
What about if the user has a function they cannot modify to include type hints, 
or using lambda/partial functions? For these cases, it makes sense to use a 
wrapper like before, e.g. `pandas_udf(func)`. I'd also worry that forcing type 
hints might be off-putting to some users, since they are not that widely used 
or optional. I think it would be good to support a long-form PandasUDF 
declaration (like proposal 1) and also allow to infer the long-form from type 
hints (like this PR), so users have both options.
   
   I'm also not too sure about changing some of the PandasUDFs to use regular 
functions, like with `df.groupby.apply(udf)`. I think it makes things less 
consistent by not using a `pandas_udf` for everything, and it could be 
inconvenient for the user to keep specifying the schema as an argument for 
multiple calls, instead of just binding it once with `pandas_udf`. It should be 
possible to still remove the udf type from the API so the following could be 
done which is almost similar to the proposed change:
   ```python
   df.groupby.apply(pandas_udf(f, schema=...))
   ```
   
   Anyway, I'm not opposed to anything here and fine with the new proposal, 
just some slight concerns before we commit to any new changes

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