class_docstr: Serializer used by Python worker to evaluate Pandas UDFs
class_docstr_tok: ["Serializer","used","by","Python","worker","to","evaluate","Pandas","UDFs"]
code: def __init__(
      self,
      timezone,
      safecheck,
      assign_cols_by_name,
      df_for_struct=False,
      struct_in_pandas="dict",
      ndarray_as_list=False,
      arrow_cast=False,
  ):
      super(ArrowStreamPandasUDFSerializer, self).__init__(
          timezone, safecheck
      )
      self._assign_cols_by_name = assign_cols_by_name
      self._df_for_struct = df_for_struct
      self._struct_in_pandas = struct_in_pandas
      self._ndarray_as_list = ndarray_as_list
      self._arrow_cast = arrow_cast
  
imports: from pyspark.errors import PySparkRuntimeError, PySparkTypeError, PySparkValueError
  from pyspark.loose_version import LooseVersion
  from pyspark.serializers import Serializer, read_int, write_int, UTF8Deserializer, CPickleSerializer
  from pyspark.sql.pandas.types import from_arrow_type, to_arrow_type, _create_converter_from_pandas, _create_converter_to_pandas
  from pyspark.sql.types import DataType, StringType, StructType, BinaryType, StructField, LongType, IntegerType
label_desc: Use image node_id 1 to create a new ArrowStreamPandasUDFSerializer object from inherited base classes: ArrowStreamPandasSerializer with example: obj = ArrowStreamPandasUDFSerializer(timezone, safecheck, assign_cols_by_name, df_for_struct, struct_in_pandas, ndarray_as_list, arrow_cast)