code: def _make_date_converter(
      date_parser=lib.no_default,
      dayfirst: bool = False,
      cache_dates: bool = True,
      date_format: dict[Hashable, str] | str | None = None,
  ):
      if date_parser is not lib.no_default:
          warnings.warn(
              "The argument 'date_parser' is deprecated and will "
              "be removed in a future version. "
              "Please use 'date_format' instead, or read your data in as 'object' dtype "
              "and then call 'to_datetime'.",
              FutureWarning,
              stacklevel=find_stack_level(),
          )
      if date_parser is not lib.no_default and date_format is not None:
          raise TypeError(
              "Cannot use both 'date_parser' and 'date_format'"
          )
  
      def unpack_if_single_element(arg):
          # NumPy 1.25 deprecation: https://github.com/numpy/numpy/pull/10615
          if (
              isinstance(arg, np.ndarray)
              and arg.ndim == 1
              and len(arg) == 1
          ):
              return arg[0]
          return arg
  
      def converter(*date_cols, col: Hashable):
          if len(date_cols) == 1 and date_cols[0].dtype.kind in "Mm":
              return date_cols[0]
  
          if date_parser is lib.no_default:
              strs = parsing.concat_date_cols(date_cols)
              date_fmt = (
                  date_format.get(col)
                  if isinstance(date_format, dict)
                  else date_format
              )
  
              result = tools.to_datetime(
                  ensure_object(strs),
                  format=date_fmt,
                  utc=False,
                  dayfirst=dayfirst,
                  errors="ignore",
                  cache=cache_dates,
              )
              if isinstance(result, DatetimeIndex):
                  arr = result.to_numpy()
                  arr.flags.writeable = True
                  return arr
              return result._values
          else:
              try:
                  result = tools.to_datetime(
                      date_parser(
                          *(
                              unpack_if_single_element(arg)
                              for arg in date_cols
                          )
                      ),
                      errors="ignore",
                      cache=cache_dates,
                  )
                  if isinstance(result, datetime.datetime):
                      raise Exception("scalar parser")
                  return result
              except Exception:
                  return tools.to_datetime(
                      parsing.try_parse_dates(
                          parsing.concat_date_cols(date_cols),
                          parser=date_parser,
                      ),
                      errors="ignore",
                  )
  
      return converter
  
imports: from __future__ import annotations
  from collections import defaultdict
  from copy import copy
  import csv
  import datetime
  from enum import Enum
  import itertools
  from typing import TYPE_CHECKING, Any, Callable, Hashable, Iterable, List, Mapping, Sequence, Tuple, cast, final, overload
  import warnings
  import numpy
  from pandas._libs import lib, parsers
  import pandas._libs.ops
  from pandas._libs.parsers import STR_NA_VALUES
  from pandas._libs.tslibs import parsing
  from pandas._typing import ArrayLike, DtypeArg, DtypeObj, Scalar
  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.astype import astype_array
  from pandas.core.dtypes.common import ensure_object, is_bool_dtype, is_dict_like, is_dtype_equal, is_extension_array_dtype, is_float_dtype, is_integer, is_integer_dtype, is_list_like, is_object_dtype, is_scalar, is_string_dtype, pandas_dtype
  from pandas.core.dtypes.dtypes import CategoricalDtype, ExtensionDtype
  from pandas.core.dtypes.missing import isna
  from pandas import ArrowDtype, DatetimeIndex, StringDtype
  from pandas.core import algorithms
  from pandas.core.arrays import ArrowExtensionArray, BooleanArray, Categorical, ExtensionArray, FloatingArray, IntegerArray
  from pandas.core.arrays.boolean import BooleanDtype
  from pandas.core.indexes.api import Index, MultiIndex, default_index, ensure_index_from_sequences
  from pandas.core.series import Series
  from pandas.core.tools import datetimes
  from pandas.io.common import is_potential_multi_index
label_desc: Use image node_id 1 for calling a global function with example usage: _make_date_converter(date_parser, dayfirst, cache_dates, date_format) and returns: converter, arg, arg, date_cols, result, arr, result, tools