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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _ParseTimestamp(self, parser_mediator, row):
 """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. """

    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))