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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 _organize_lanes(info_iter, barcode_ids):
 """Organize flat lane information into nested YAML structure. """

    all_lanes = []
    for (fcid, lane, sampleref), info in itertools.groupby(info_iter, lambda x: (x[0], x[1], x[1])):
        info = list(info)
        cur_lane = dict(flowcell_id=fcid, lane=lane, genome_build=info[0][3], analysis="Standard")
        if not _has_barcode(info):
            cur_lane["description"] = info[0][1]
        else: # barcoded sample
            cur_lane["description"] = "Barcoded lane %s" % lane
            multiplex = []
            for (_, _, sample_id, _, bc_seq) in info:
                bc_type, bc_id = barcode_ids[bc_seq]
                multiplex.append(dict(barcode_type=bc_type,
                                      barcode_id=bc_id,
                                      sequence=bc_seq,
                                      name=sample_id))
            cur_lane["multiplex"] = multiplex
        all_lanes.append(cur_lane)
    return all_lanes