class_docstr: Wrapper for the pyarrow engine for read_csv()
docstr: Rename some arguments to pass to pyarrow
docstr_tok: ["Rename","some","arguments","to","pass","to","pyarrow"]
code: def _get_pyarrow_options(self) -> None:
      """
      Rename some arguments to pass to pyarrow
      """
      mapping = {
          "usecols": "include_columns",
          "na_values": "null_values",
          "escapechar": "escape_char",
          "skip_blank_lines": "ignore_empty_lines",
          "decimal": "decimal_point",
          "quotechar": "quote_char",
      }
      for pandas_name, pyarrow_name in mapping.items():
          if (
              pandas_name in self.kwds
              and self.kwds.get(pandas_name) is not None
          ):
              self.kwds[pyarrow_name] = self.kwds.pop(pandas_name)
  
      # Date format handling
      # If we get a string, we need to convert it into a list for pyarrow
      # If we get a dict, we want to parse those separately
      date_format = self.date_format
      if isinstance(date_format, str):
          date_format = [date_format]
      else:
          # In case of dict, we don't want to propagate through, so
          # just set to pyarrow default of None
  
          # Ideally, in future we disable pyarrow dtype inference (read in as string)
          # to prevent misreads.
          date_format = None
      self.kwds["timestamp_parsers"] = date_format
  
      self.parse_options = {
          option_name: option_value
          for option_name, option_value in self.kwds.items()
          if option_value is not None
          and option_name
          in (
              "delimiter",
              "quote_char",
              "escape_char",
              "ignore_empty_lines",
          )
      }
  
      on_bad_lines = self.kwds.get("on_bad_lines")
      if on_bad_lines is not None:
          if callable(on_bad_lines):
              self.parse_options["invalid_row_handler"] = on_bad_lines
          elif on_bad_lines == ParserBase.BadLineHandleMethod.ERROR:
              self.parse_options[
                  "invalid_row_handler"
              ] = None  # PyArrow raises an exception by default
          elif on_bad_lines == ParserBase.BadLineHandleMethod.WARN:
  
              def handle_warning(invalid_row) -> str:
                  warnings.warn(
                      f"Expected {invalid_row.expected_columns} columns, but found "
                      f"{invalid_row.actual_columns}: {invalid_row.text}",
                      ParserWarning,
                      stacklevel=find_stack_level(),
                  )
                  return "skip"
  
              self.parse_options["invalid_row_handler"] = handle_warning
          elif on_bad_lines == ParserBase.BadLineHandleMethod.SKIP:
              self.parse_options[
                  "invalid_row_handler"
              ] = lambda _: "skip"
  
      self.convert_options = {
          option_name: option_value
          for option_name, option_value in self.kwds.items()
          if option_value is not None
          and option_name
          in (
              "include_columns",
              "null_values",
              "true_values",
              "false_values",
              "decimal_point",
              "timestamp_parsers",
          )
      }
      self.convert_options["strings_can_be_null"] = (
          "" in self.kwds["null_values"]
      )
      # autogenerated column names are prefixed with 'f' in pyarrow.csv
      if (
          self.header is None
          and "include_columns" in self.convert_options
      ):
          self.convert_options["include_columns"] = [
              f"f{n}" for n in self.convert_options["include_columns"]
          ]
  
      self.read_options = {
          "autogenerate_column_names": self.header is None,
          "skip_rows": self.header
          if self.header is not None
          else self.kwds["skiprows"],
          "encoding": self.encoding,
      }
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING
  import warnings
  from pandas._config import using_pyarrow_string_dtype
  from pandas._libs import lib
  from pandas.compat._optional import import_optional_dependency
  from pandas.errors import ParserError, ParserWarning
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.common import pandas_dtype
  from pandas.core.dtypes.inference import is_integer
  import pandas
  from pandas import DataFrame
  from pandas.io._util import _arrow_dtype_mapping, arrow_string_types_mapper
  from pandas.io.parsers.base_parser import ParserBase
label_desc: Use image node_id 3 for calling the ArrowParserWrapper obj's underlying member method code with example usage: obj._get_pyarrow_options() and returns: str