code: def _ParseTimestamp(self, parser_mediator, row):
      
      timestamp = row.get('timestamp', None)
      if timestamp is not None:
        try:
          timestamp = int(timestamp, 10)
        except (ValueError, TypeError):
          parser_mediator.ProduceExtractionWarning(
              'Unable to parse timestamp value: {0!s}'.format(timestamp))
  
        return dfdatetime_posix_time.PosixTime(timestamp=timestamp)
  
      # The timestamp is not available; parse the local date and time instead.
      try:
        return self._ConvertToTimestamp(row['date'], row['time'])
      except ValueError as exception:
        parser_mediator.ProduceExtractionWarning((
            'Unable to parse time string: "{0:s} {1:s}" with error: '
            '{2!s}').format(repr(row['date']), repr(row['time']), exception))
docs: Provides a timestamp for the given row.
  
      If the Trend Micro log comes from a version that provides a POSIX timestamp,
      use that directly; it provides the advantages of UTC and of second
      precision. Otherwise fall back onto the local-timezone date and time.
  
      Args:
        parser_mediator (ParserMediator): mediates interactions between parsers
            and other components, such as storage and dfvfs.
        row (dict[str, str]): fields of a single row, as specified in COLUMNS.
  
      Returns:
        dfdatetime.interface.DateTimeValue: date and time value.