docstr: Checks whether the file begins with the BOM character.
  If it does, remove it. In addition, if there is quoting
  in the field subsequent to the BOM, remove it as well
  because it technically takes place at the beginning of
  the name, not the middle of it.
docstr_tok: ["Checks","whether","the","file","begins","with","the","BOM","character",".","If","it","does",",","remove","it",".","In","addition",",","if","there","is","quoting","in","the","field","subsequent","to","the","BOM",",","remove","it","as","well","because","it","technically","takes","place","at","the","beginning","of","the","name",",","not","the","middle","of","it","."]
code: def _check_for_bom(self, first_row: list[Scalar]) -> list[Scalar]:
      """
      Checks whether the file begins with the BOM character.
      If it does, remove it. In addition, if there is quoting
      in the field subsequent to the BOM, remove it as well
      because it technically takes place at the beginning of
      the name, not the middle of it.
      """
      # first_row will be a list, so we need to check
      # that that list is not empty before proceeding.
      if not first_row:
          return first_row
  
      # The first element of this row is the one that could have the
      # BOM that we want to remove. Check that the first element is a
      # string before proceeding.
      if not isinstance(first_row[0], str):
          return first_row
  
      # Check that the string is not empty, as that would
      # obviously not have a BOM at the start of it.
      if not first_row[0]:
          return first_row
  
      # Since the string is non-empty, check that it does
      # in fact begin with a BOM.
      first_elt = first_row[0][0]
      if first_elt != _BOM:
          return first_row
  
      first_row_bom = first_row[0]
      new_row: str
  
      if len(first_row_bom) > 1 and first_row_bom[1] == self.quotechar:
          start = 2
          quote = first_row_bom[1]
          end = first_row_bom[2:].index(quote) + 2
  
          # Extract the data between the quotation marks
          new_row = first_row_bom[start:end]
  
          # Extract any remaining data after the second
          # quotation mark.
          if len(first_row_bom) > end + 1:
              new_row += first_row_bom[end + 1 :]
  
      else:
          # No quotation so just remove BOM from first element
          new_row = first_row_bom[1:]
  
      new_row_list: list[Scalar] = [new_row]
      return new_row_list + first_row[1:]
  
imports: from __future__ import annotations
  from collections import abc, defaultdict
  import csv
  from io import StringIO
  import re
  import sys
  from typing import IO, TYPE_CHECKING, DefaultDict, Hashable, Iterator, List, Literal, Mapping, Sequence, cast
  import numpy
  from pandas._libs import lib
  from pandas._typing import ArrayLike, ReadCsvBuffer, Scalar
  from pandas.errors import EmptyDataError, ParserError
  from pandas.core.dtypes.common import is_integer
  from pandas.core.dtypes.inference import is_dict_like
  from pandas.io.common import dedup_names, is_potential_multi_index
  from pandas.io.parsers.base_parser import ParserBase, parser_defaults
label_desc: Use image node_id 10 for calling the PythonParser obj's underlying member method code with example usage: obj._check_for_bom(first_row) and returns: unknown, first_row, first_row, first_row, first_row