zero323#394: Use Union[List[Column], List[str]] for select()

as @zero323 pointed out in zero323#395 (review),
we can use only List, not Sequence (as originally suggested by mypy)

test-data/unit/sql-dataframe.test

@@ -21,6 +21,57 @@ df.sample(withReplacement=False) # E: No overload variant of "sample" of "DataFr
 
 [out]
 
+[case selectColumns]
+from pyspark.sql import SparkSession
+from pyspark.sql.functions import col
+
+spark = SparkSession.builder.getOrCreate()
+
+data = [('Alice', 1)]
+df = spark.createDataFrame(data, schema="name str, age int")
+
+df.select(["name", "age"])
+df.select([col("name"), col("age")])
+
+df.select(["name", col("age")])  # E: Argument 1 to "select" of "DataFrame" has incompatible type "List[object]"; expected "Union[List[Column], List[str]]"
+
+[out]
+
+[case groupBy]
+from pyspark.sql import SparkSession
+from pyspark.sql.functions import col
+
+spark = SparkSession.builder.getOrCreate()
+
+data = [('Alice', 1)]
+df = spark.createDataFrame(data, schema="name str, age int")
+
+df.groupBy(["name", "age"])
+df.groupBy([col("name"), col("age")])
+
+
+df.groupBy(["name", col("age")])  # E: Argument 1 to "groupBy" of "DataFrame" has incompatible type "List[object]"; expected "Union[List[Column], List[str]]"
+
+[out]
+
+[case rollup]
+from pyspark.sql import SparkSession
+from pyspark.sql.functions import col
+
+spark = SparkSession.builder.getOrCreate()
+
+data = [('Alice', 1)]
+df = spark.createDataFrame(data, schema="name str, age int")
+
+df.rollup(["name", "age"])
+df.rollup([col("name"), col("age")])
+
+
+df.rollup(["name", col("age")])  # E: Argument 1 to "rollup" of "DataFrame" has incompatible type "List[object]"; expected "Union[List[Column], List[str]]"
+
+[out]
+
+
 
 [case dropColumns]
 from pyspark.sql import SparkSession

third_party/3/pyspark/sql/dataframe.pyi

@@ -1,5 +1,15 @@
 from typing import overload
-from typing import Any, Callable, Dict, Iterator, List, Optional, Tuple, TypeVar, Union
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    Iterator,
+    List,
+    Optional,
+    Tuple,
+    TypeVar,
+    Union,
+)
 
 import pandas.core.frame  # type: ignore
 from py4j.java_gateway import JavaObject  # type: ignore
@@ -135,7 +145,7 @@ class DataFrame(PandasMapOpsMixin, PandasConversionMixin):
     @overload
     def select(self, *cols: ColumnOrName) -> DataFrame: ...
     @overload
-    def select(self, __cols: List[ColumnOrName]) -> DataFrame: ...
+    def select(self, __cols: Union[List[Column], List[str]]) -> DataFrame: ...
     @overload
     def selectExpr(self, *expr: str) -> DataFrame: ...
     @overload
@@ -144,15 +154,15 @@ class DataFrame(PandasMapOpsMixin, PandasConversionMixin):
     @overload
     def groupBy(self, *cols: ColumnOrName) -> GroupedData: ...
     @overload
-    def groupBy(self, __cols: List[ColumnOrName]) -> GroupedData: ...
+    def groupBy(self, __cols: Union[List[Column], List[str]]) -> GroupedData: ...
     @overload
     def rollup(self, *cols: ColumnOrName) -> GroupedData: ...
     @overload
-    def rollup(self, __cols: List[ColumnOrName]) -> GroupedData: ...
+    def rollup(self, __cols: Union[List[Column], List[str]]) -> GroupedData: ...
     @overload
     def cube(self, *cols: ColumnOrName) -> GroupedData: ...
     @overload
-    def cube(self, __cols: List[ColumnOrName]) -> GroupedData: ...
+    def cube(self, __cols: Union[List[Column], List[str]]) -> GroupedData: ...
     def agg(self, *exprs: Union[Column, Dict[str, str]]) -> DataFrame: ...
     def union(self, other: DataFrame) -> DataFrame: ...
     def unionAll(self, other: DataFrame) -> DataFrame: ...
@@ -220,7 +230,7 @@ class DataFrame(PandasMapOpsMixin, PandasConversionMixin):
     @overload
     def groupby(self, *cols: ColumnOrName) -> GroupedData: ...
     @overload
-    def groupby(self, __cols: List[ColumnOrName]) -> GroupedData: ...
+    def groupby(self, __cols: Union[List[Column], List[str]]) -> GroupedData: ...
     def drop_duplicates(self, subset: Optional[List[str]] = ...) -> DataFrame: ...
     def where(self, condition: ColumnOrName) -> DataFrame: ...