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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 GetEntries(self, parser_mediator, data=None, **unused_kwargs):
 """Extracts uTorrent active torrents. This is the main parsing engine for the plugin. It determines if the selected file is the proper file to parse and extracts current running torrents. interface.Process() checks for the given BENCODE_KEYS set, ensures that it matches, and then passes the bencoded data to this function for parsing. This plugin then parses the entire set of bencoded data to extract the variable file-name keys to retrieve their values. uTorrent creates a file, resume.dat, and a backup, resume.dat.old, to for all active torrents. This is typically stored in the user's application data folder. These files, at a minimum, contain a '.fileguard' key and a dictionary with a key name for a particular download with a '.torrent' file extension. Args: parser_mediator (ParserMediator):
 mediates interactions between parsers and other components, such as storage and dfvfs. data (Optional[dict[str, object]]):
 bencode data values. """

    # Walk through one of the torrent keys to ensure it's from a valid file.
    for key, value in iter(data.items()):
      if not '.torrent' in key:
        continue

      caption = value.get('caption')
      path = value.get('path')
      seedtime = value.get('seedtime')
      if not caption or not path or seedtime < 0:
        raise errors.WrongBencodePlugin(self.NAME)

    for torrent, value in iter(data.items()):
      if not '.torrent' in torrent:
        continue

      event_data = UTorrentEventData()
      event_data.caption = value.get('caption', None)
      event_data.path = value.get('path', None)

      # Convert seconds to minutes.
      seedtime = value.get('seedtime', None)
      event_data.seedtime, _ = divmod(seedtime, 60)

      # Create timeline events based on extracted values.
      for event_key, event_value in iter(value.items()):
        if event_key == 'added_on':
          date_time = dfdatetime_posix_time.PosixTime(timestamp=event_value)
          event = time_events.DateTimeValuesEvent(
              date_time, definitions.TIME_DESCRIPTION_ADDED)
          parser_mediator.ProduceEventWithEventData(event, event_data)

        elif event_key == 'completed_on':
          date_time = dfdatetime_posix_time.PosixTime(timestamp=event_value)
          event = time_events.DateTimeValuesEvent(
              date_time, definitions.TIME_DESCRIPTION_FILE_DOWNLOADED)
          parser_mediator.ProduceEventWithEventData(event, event_data)

        elif event_key == 'modtimes':
          for modtime in event_value:
            # Some values are stored as 0, skip those.
            if not modtime:
              continue

            date_time = dfdatetime_posix_time.PosixTime(timestamp=modtime)
            event = time_events.DateTimeValuesEvent(
                date_time, definitions.TIME_DESCRIPTION_MODIFICATION)
            parser_mediator.ProduceEventWithEventData(event, event_data)