How to use the snakemake.io.glob_wildcards function in snakemake

all_files = []
        for wc, filename in inputmap:
            try:
                wc = eval(wc)
            except:
                pass
            wc = update_wildcard_constraints(wc, wildcard_constraints, {})
            all_wc.append(wc)
            if filename is None:
                continue
            if isinstance(filename, str):
                filename = [filename]
            all_files = all_files + filename
        for f in all_files:
            for wc in all_wc:
                wildcards = glob_wildcards(wc, [os.path.basename(f)])
                for k, v in wildcards._asdict().items():
                    if len(v) > 0:
                        d[k] = v[0]
    except:
        logger.debug("Failed to get wildcards for inputmap ", inputmap)
        raise
    return d

def get_batch_ids_raw(runname, config, tag=None, checkpoints=None):
    tag_barcode = get_tag_barcode(tag, runname, config) if tag else None
    if tag_barcode and checkpoints:
        if hasattr(checkpoints, config['demux_default'] + '_barcode'):
            barcode_batch_dir = getattr(checkpoints, config['demux_default'] + '_barcode').get(runname=runname).output.barcodes
        else:
            raise NotImplementedError("Demultiplexing with {} is not implemented.".format(config['demux_default']))
        barcode_batch = os.path.join(barcode_batch_dir, tag_barcode, '{id}.txt')
        batches_txt, = glob_wildcards(barcode_batch)
        return batches_txt
    else:
        batches_tar, = glob_wildcards("{datadir}/{runname}/reads/{{id}}.tar".format(datadir=config["storage_data_raw"], runname=runname))
        batches_fast5, = glob_wildcards("{datadir}/{runname}/reads/{{id}}.fast5".format(datadir=config["storage_data_raw"], runname=runname))
        return batches_tar + batches_fast5

def rename_genomes(input_folder,mapfile_genomes,mapfile_contigs,output_dir):

    file_name = f"{input_folder}/{{binid}}.fasta"
    bin_ids, = glob_wildcards(file_name)

    old2new_name= dict(zip(bin_ids,utils.gen_names_for_range(len(bin_ids),prefix='MAG')))
    os.makedirs(output_dir)


    with open(mapfile_contigs,'w') as out_contigs, open(mapfile_genomes,'w') as old2new_mapping_file :
        old2new_mapping_file.write(f"BinID\tMAG\n")
        for binid in bin_ids:

            fasta_in = file_name.format(binid=binid)
            new_name= old2new_name[binid]

            old2new_mapping_file.write(f"{binid}\t{new_name}\n")

            fasta_out = os.path.join(output_dir,f"{new_name}.fasta")

def predict_genes_genomes(in_dir,out_dir,log):

    path= os.path.join(in_dir,'{genome}.fasta')
    os.makedirs(out_dir,exist_ok=True)

    for genome in glob_wildcards(path).genome:
        predict_genes(genome,path.format(genome=genome),out_dir,log)

def get_batch_ids_raw(runname, config, tag=None, checkpoints=None):
    tag_barcode = get_tag_barcode(tag, runname, config) if tag else None
    if tag_barcode and checkpoints:
        if hasattr(checkpoints, config['demux_default'] + '_barcode'):
            barcode_batch_dir = getattr(checkpoints, config['demux_default'] + '_barcode').get(runname=runname).output.barcodes
        else:
            raise NotImplementedError("Demultiplexing with {} is not implemented.".format(config['demux_default']))
        barcode_batch = os.path.join(barcode_batch_dir, tag_barcode, '{id}.txt')
        batches_txt, = glob_wildcards(barcode_batch)
        return batches_txt
    else:
        batches_tar, = glob_wildcards("{datadir}/{runname}/reads/{{id}}.tar".format(datadir=config["storage_data_raw"], runname=runname))
        batches_fast5, = glob_wildcards("{datadir}/{runname}/reads/{{id}}.fast5".format(datadir=config["storage_data_raw"], runname=runname))
        return batches_tar + batches_fast5