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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 delete_row_range(self, format_str, start_game, end_game):
 """Delete rows related to the given game range. Args: format_str: a string to `.format()` by the game numbers in order to create the row prefixes. start_game: the starting game number of the deletion. end_game: the ending game number of the deletion. """

        row_keys = make_single_array(
            self.tf_table.keys_by_range_dataset(
                format_str.format(start_game),
                format_str.format(end_game)))
        row_keys = list(row_keys)
        if not row_keys:
            utils.dbg('No rows left for games %d..%d' % (
                start_game, end_game))
            return
        utils.dbg('Deleting %d rows:  %s..%s' % (
            len(row_keys), row_keys[0], row_keys[-1]))

        # Reverse the keys so that the queue is left in a more
        # sensible end state if you change your mind (say, due to a
        # mistake in the timestamp) and abort the process: there will
        # be a bit trimmed from the end, rather than a bit
        # trimmed out of the middle.
        row_keys.reverse()
        total_keys = len(row_keys)
        utils.dbg('Deleting total of %d keys' % total_keys)
        concurrency = min(MAX_BT_CONCURRENCY,
                          multiprocessing.cpu_count() * 2)
        with multiprocessing.Pool(processes=concurrency) as pool:
            batches = []
            with tqdm(desc='Keys', unit_scale=2, total=total_keys) as pbar:
                for b in utils.iter_chunks(bigtable.row.MAX_MUTATIONS,
                                           row_keys):
                    pbar.update(len(b))
                    batches.append((self.btspec, b))
                    if len(batches) >= concurrency:
                        pool.map(_delete_rows, batches)
                        batches = []
                pool.map(_delete_rows, batches)
                batches = []