code: def _determine_type_mapper(
      cls, *, dtype_backend=None, convert_string=False, **kwargs
  ):
      user_mapper = kwargs.get("arrow_to_pandas", {}).get(
          "types_mapper"
      )
      type_mappers = []
  
      def pyarrow_type_mapper(pyarrow_dtype):
          # Special case pyarrow strings to use more feature complete dtype
          # See https://github.com/pandas-dev/pandas/issues/50074
          if pyarrow_dtype == pa.string():
              return pd.StringDtype("pyarrow")
          else:
              return pd.ArrowDtype(pyarrow_dtype)
  
      # always use the user-defined mapper first, if available
      if user_mapper is not None:
          type_mappers.append(user_mapper)
  
      # next in priority is converting strings
      if convert_string:
          type_mappers.append(
              {pa.string(): pd.StringDtype("pyarrow")}.get
          )
          type_mappers.append(
              {pa.date32(): pd.ArrowDtype(pa.date32())}.get
          )
          type_mappers.append(
              {pa.date64(): pd.ArrowDtype(pa.date64())}.get
          )
  
          def _convert_decimal_type(type):
              if pa.types.is_decimal(type):
                  return pd.ArrowDtype(type)
              return None
  
          type_mappers.append(_convert_decimal_type)
  
      # and then nullable types
      if dtype_backend == "numpy_nullable":
          type_mappers.append(PYARROW_NULLABLE_DTYPE_MAPPING.get)
      elif dtype_backend == "pyarrow":
          type_mappers.append(pyarrow_type_mapper)
  
      def default_types_mapper(pyarrow_dtype):
          """Try all type mappers in order, starting from the user type mapper."""
          for type_converter in type_mappers:
              converted_type = type_converter(pyarrow_dtype)
              if converted_type is not None:
                  return converted_type
  
      if len(type_mappers) > 0:
          return default_types_mapper
  
imports: from __future__ import annotations
  import json
  import operator
  import textwrap
  import warnings
  from collections import defaultdict
  from datetime import datetime
  from functools import reduce
  import numpy
  import pandas
  import pyarrow
  import pyarrow.parquet
  from fsspec.core import expand_paths_if_needed, stringify_path
  from fsspec.implementations.arrow import ArrowFSWrapper
  from pyarrow import dataset
  from pyarrow import fs
  import dask
  from dask.base import tokenize
  from dask.core import flatten
  from dask.dataframe.backends import pyarrow_schema_dispatch
  from dask.dataframe.io.parquet.utils import Engine, _get_aggregation_depth, _infer_split_row_groups, _normalize_index_columns, _process_open_file_options, _row_groups_to_parts, _set_gather_statistics, _set_metadata_task_size, _sort_and_analyze_paths
  from dask.dataframe.io.utils import _get_pyarrow_dtypes, _is_local_fs, _open_input_files
  from dask.dataframe.utils import clear_known_categories, pyarrow_strings_enabled
  from dask.delayed import Delayed
  from dask.utils import getargspec, natural_sort_key
label_desc: Use image node_id 15 for calling the ArrowDatasetEngine obj's underlying member method code with example usage: obj._determine_type_mapper(cls) and returns: default_types_mapper, pd, pd, None, pd, converted_type