code: def TextParser(*args, **kwds) -> TextFileReader:
      """
      Converts lists of lists/tuples into DataFrames with proper type inference
      and optional (e.g. string to datetime) conversion. Also enables iterating
      lazily over chunks of large files
  
      Parameters
      ----------
      data : file-like object or list
      delimiter : separator character to use
      dialect : str or csv.Dialect instance, optional
          Ignored if delimiter is longer than 1 character
      names : sequence, default
      header : int, default 0
          Row to use to parse column labels. Defaults to the first row. Prior
          rows will be discarded
      index_col : int or list, optional
          Column or columns to use as the (possibly hierarchical) index
      has_index_names: bool, default False
          True if the cols defined in index_col have an index name and are
          not in the header.
      na_values : scalar, str, list-like, or dict, optional
          Additional strings to recognize as NA/NaN.
      keep_default_na : bool, default True
      thousands : str, optional
          Thousands separator
      comment : str, optional
          Comment out remainder of line
      parse_dates : bool, default False
      keep_date_col : bool, default False
      date_parser : function, optional
  
          .. deprecated:: 2.0.0
      date_format : str or dict of column -> format, default ``None``
  
          .. versionadded:: 2.0.0
      skiprows : list of integers
          Row numbers to skip
      skipfooter : int
          Number of line at bottom of file to skip
      converters : dict, optional
          Dict of functions for converting values in certain columns. Keys can
          either be integers or column labels, values are functions that take one
          input argument, the cell (not column) content, and return the
          transformed content.
      encoding : str, optional
          Encoding to use for UTF when reading/writing (ex. 'utf-8')
      float_precision : str, optional
          Specifies which converter the C engine should use for floating-point
          values. The options are `None` or `high` for the ordinary converter,
          `legacy` for the original lower precision pandas converter, and
          `round_trip` for the round-trip converter.
  
          .. versionchanged:: 1.2
      """
      kwds["engine"] = "python"
      return TextFileReader(*args, **kwds)
  
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 18 for calling a global function with example usage: TextParser() and returns: TextFileReader