[jira] [Assigned] (SPARK-42235) Missing typing for pandas_udf

["Apache Spark (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-42235?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-42235:
------------------------------------

    Assignee:     (was: Apache Spark)

> Missing typing for pandas_udf
> -----------------------------
>
>                 Key: SPARK-42235
>                 URL: https://issues.apache.org/jira/browse/SPARK-42235
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 3.3.0
>            Reporter: Donggu Kang
>            Priority: Minor
>
> The typing stub {{site-packages/pyspark/sql/pandas/functions.pyi}} has a list of possible signatures of {{pandas_udf}}. It is missing a case
> {code:python}
> import pyspark.sql.functions as F
> # PySpark3's typing stub error
> @F.pandas_udf(
>     returnType=LongType()
> )
> def my_udf(dummy_col: pd.Series) -> pd.Series:
>     ...
> {code}
> The stub defined {{pandas_udf(f, returnType, functionType)}} but not {{pandas_udf(f, returnType)}}. The official documentation recommends using a return type hint instead of {{returnType}}.
>  
> {code:python}
> # defined
> @overload
> def pandas_udf( f: PandasScalarToScalarFunction, returnType: Union[AtomicDataTypeOrString, ArrayType], functionType: PandasScalarUDFType, ) -> UserDefinedFunctionLike: ...
>  
> # not defined
> @overload
> def pandas_udf( f: PandasScalarToScalarFunction, returnType: Union[AtomicDataTypeOrString, ArrayType]) -> UserDefinedFunctionLike: ...
> {code}
>  



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