class_docstr: Passed dialect overrides any of the related parser options
class_docstr_tok: ["Passed","dialect","overrides","any","of","the","related","parser","options"]
code: def _clean_options(
      self, options: dict[str, Any], engine: CSVEngine
  ) -> tuple[dict[str, Any], CSVEngine]:
      result = options.copy()
  
      fallback_reason = None
  
      # C engine not supported yet
      if engine == "c":
          if options["skipfooter"] > 0:
              fallback_reason = (
                  "the 'c' engine does not support skipfooter"
              )
              engine = "python"
  
      sep = options["delimiter"]
      delim_whitespace = options["delim_whitespace"]
  
      if sep is None and not delim_whitespace:
          if engine in ("c", "pyarrow"):
              fallback_reason = (
                  f"the '{engine}' engine does not support "
                  "sep=None with delim_whitespace=False"
              )
              engine = "python"
      elif sep is not None and len(sep) > 1:
          if engine == "c" and sep == r"\s+":
              result["delim_whitespace"] = True
              del result["delimiter"]
          elif engine not in ("python", "python-fwf"):
              # wait until regex engine integrated
              fallback_reason = (
                  f"the '{engine}' engine does not support "
                  "regex separators (separators > 1 char and "
                  r"different from '\s+' are interpreted as regex)"
              )
              engine = "python"
      elif delim_whitespace:
          if "python" in engine:
              result["delimiter"] = r"\s+"
      elif sep is not None:
          encodeable = True
          encoding = sys.getfilesystemencoding() or "utf-8"
          try:
              if len(sep.encode(encoding)) > 1:
                  encodeable = False
          except UnicodeDecodeError:
              encodeable = False
          if not encodeable and engine not in ("python", "python-fwf"):
              fallback_reason = (
                  f"the separator encoded in {encoding} "
                  f"is > 1 char long, and the '{engine}' engine "
                  "does not support such separators"
              )
              engine = "python"
  
      quotechar = options["quotechar"]
      if quotechar is not None and isinstance(quotechar, (str, bytes)):
          if (
              len(quotechar) == 1
              and ord(quotechar) > 127
              and engine not in ("python", "python-fwf")
          ):
              fallback_reason = (
                  "ord(quotechar) > 127, meaning the "
                  "quotechar is larger than one byte, "
                  f"and the '{engine}' engine does not support such quotechars"
              )
              engine = "python"
  
      if fallback_reason and self._engine_specified:
          raise ValueError(fallback_reason)
  
      if engine == "c":
          for arg in _c_unsupported:
              del result[arg]
  
      if "python" in engine:
          for arg in _python_unsupported:
              if (
                  fallback_reason
                  and result[arg] != _c_parser_defaults[arg]
              ):
                  raise ValueError(
                      "Falling back to the 'python' engine because "
                      f"{fallback_reason}, but this causes {repr(arg)} to be "
                      "ignored as it is not supported by the 'python' engine."
                  )
              del result[arg]
  
      if fallback_reason:
          warnings.warn(
              (
                  "Falling back to the 'python' engine because "
                  f"{fallback_reason}; you can avoid this warning by specifying "
                  "engine='python'."
              ),
              ParserWarning,
              stacklevel=find_stack_level(),
          )
  
      index_col = options["index_col"]
      names = options["names"]
      converters = options["converters"]
      na_values = options["na_values"]
      skiprows = options["skiprows"]
  
      validate_header_arg(options["header"])
  
      if index_col is True:
          raise ValueError("The value of index_col couldn't be 'True'")
      if is_index_col(index_col):
          if not isinstance(index_col, (list, tuple, np.ndarray)):
              index_col = [index_col]
      result["index_col"] = index_col
  
      names = list(names) if names is not None else names
  
      # type conversion-related
      if converters is not None:
          if not isinstance(converters, dict):
              raise TypeError(
                  "Type converters must be a dict or subclass, "
                  f"input was a {type(converters).__name__}"
              )
      else:
          converters = {}
  
      # Converting values to NA
      keep_default_na = options["keep_default_na"]
      na_values, na_fvalues = _clean_na_values(
          na_values, keep_default_na
      )
  
      # handle skiprows; this is internally handled by the
      # c-engine, so only need for python and pyarrow parsers
      if engine == "pyarrow":
          if not is_integer(skiprows) and skiprows is not None:
              # pyarrow expects skiprows to be passed as an integer
              raise ValueError(
                  "skiprows argument must be an integer when using "
                  "engine='pyarrow'"
              )
      else:
          if is_integer(skiprows):
              skiprows = list(range(skiprows))
          if skiprows is None:
              skiprows = set()
          elif not callable(skiprows):
              skiprows = set(skiprows)
  
      # put stuff back
      result["names"] = names
      result["converters"] = converters
      result["na_values"] = na_values
      result["na_fvalues"] = na_fvalues
      result["skiprows"] = skiprows
  
      return result, engine
  
imports: from __future__ import annotations
  from collections import abc
  import csv
  import sys
  from textwrap import fill
  from types import TracebackType
  from typing import IO, Any, Callable, Hashable, Literal, NamedTuple, Sequence, overload
  import warnings
  import numpy
  from pandas._libs import lib
  from pandas._libs.parsers import STR_NA_VALUES
  from pandas._typing import CompressionOptions, CSVEngine, DtypeArg, DtypeBackend, FilePath, IndexLabel, ReadCsvBuffer, StorageOptions
  from pandas.errors import AbstractMethodError, ParserWarning
  from pandas.util._decorators import Appender
  from pandas.util._exceptions import find_stack_level
  from pandas.util._validators import check_dtype_backend
  from pandas.core.dtypes.common import is_file_like, is_float, is_integer, is_list_like
  from pandas.core.frame import DataFrame
  from pandas.core.indexes.api import RangeIndex
  from pandas.core.shared_docs import _shared_docs
  from pandas.io.common import IOHandles, get_handle, stringify_path, validate_header_arg
  from pandas.io.parsers.arrow_parser_wrapper import ArrowParserWrapper
  from pandas.io.parsers.base_parser import ParserBase, is_index_col, parser_defaults
  from pandas.io.parsers.c_parser_wrapper import CParserWrapper
  from pandas.io.parsers.python_parser import FixedWidthFieldParser, PythonParser
label_desc: Use image node_id 5 for calling the TextFileReader obj's underlying member method code with example usage: obj._clean_options(options, engine) and returns: result,  engine