pylint

python/pyspark/sql/pandas/serializers.py

@@ -22,7 +22,7 @@
 from typing import Optional
 
 from pyspark.serializers import Serializer, read_int, write_int, UTF8Deserializer
-from pyspark.sql.types import ArrayType, DataType, UserDefinedType
+from pyspark.sql.types import ArrayType, DataType, UserDefinedType, StructType
 from pyspark.sql.pandas.types import to_arrow_type
 
 
@@ -193,7 +193,7 @@ def create_array(s, t: pa.DataType, dt: Optional[DataType] = None):
                     raise e
             return array
 
-        def create_arrs_names(s, t: pa.DataType, dt: Optional[DataType] = None):
+        def create_arrs_names(s, t: pa.DataType, dt: Optional[StructType] = None):
             # If input s is empty with zero columns, return empty Arrays with struct
             if len(s) == 0 and len(s.columns) == 0:
                 return [(pa.array([], type=field.type), field.name) for field in t]
@@ -240,6 +240,8 @@ def create_arrs_names(s, t: pa.DataType, dt: Optional[DataType] = None):
                     raise ValueError("A field of type StructType expects a pandas.DataFrame, "
                                      "but got: %s" % str(type(s)))
                 if isinstance(dt, DataType):
+                    type_not_match = "dt must be instance of StructType when t is pyarrow struct"
+                    assert isinstance(dt, StructType), type_not_match
                     arrs_names = create_arrs_names(s, t, dt)
                 else:
                     arrs_names = create_arrs_names(s, t)