How to use the toolz.update_in function in toolz

def update(cls, config, value):
        if checker and not checker(value):
            logger.error("%s fails check %s." % (value, checker))
            sys.exit(1)
        return tz.update_in(config, keys, lambda x: value, default=value)
    return update

def _symlink_to_workdir(data, key):
    """For CWL support, symlink files into a working directory if in read-only imports.
    """
    orig_file = tz.get_in(key, data)
    if orig_file and not orig_file.startswith(dd.get_work_dir(data)):
        variantcaller = genotype.get_variantcaller(data)
        if not variantcaller:
            variantcaller = "precalled"
        out_file = os.path.join(dd.get_work_dir(data), variantcaller, os.path.basename(orig_file))
        utils.safe_makedir(os.path.dirname(out_file))
        utils.symlink_plus(orig_file, out_file)
        data = tz.update_in(data, key, lambda x: out_file)
    return data

mask = ["rnaseq", "transcripts_mask"]
        index = ["rnaseq", "transcriptome_index", "tophat"]
        dexseq = ["rnaseq", "dexseq"]
        refflat = ["rnaseq", "refflat"]
        rRNA_fa = ["rnaseq", "rRNA_fa"]
        resource_dict = tz.update_in(resource_dict, transcripts,
                                     lambda x: "../rnaseq/ref-transcripts.gtf")
        resource_dict = tz.update_in(resource_dict, mask,
                                     lambda x: "../rnaseq/ref-transcripts-mask.gtf")
        resource_dict = tz.update_in(resource_dict, index,
                                     lambda x: "../rnaseq/tophat/%s_transcriptome.ver" % args.build)
        resource_dict = tz.update_in(resource_dict, refflat,
                                     lambda x: "../rnaseq/ref-transcripts.refFlat")
        resource_dict = tz.update_in(resource_dict, dexseq,
                                     lambda x: "../rnaseq/ref-transcripts.dexseq.gff3")
        resource_dict = tz.update_in(resource_dict, rRNA_fa,
                                     lambda x: "../rnaseq/rRNA.fa")
    if args.mirbase:
        srna_gtf = ["srnaseq", "srna_transcripts"]
        srna_mirbase = ["srnaseq", "mirbase_hairpin"]
        resource_dict = tz.update_in(resource_dict, srna_gtf,
                                     lambda x: "../srnaseq/srna-transcripts.gtf")
        resource_dict = tz.update_in(resource_dict, srna_mirbase,
                                     lambda x: "../srnaseq/hairpin.fa")
    # write out resource dictionarry
    with file_transaction(resource_file) as tx_resource_file:
        with open(tx_resource_file, "w") as out_handle:
            out_handle.write(yaml.dump(resource_dict, default_flow_style=False))

    print("Updating Galaxy .loc files.")
    galaxy_base = os.path.join(_get_data_dir(), "galaxy")
    for index, index_file in indexed.items():

def run_and_save(data):
    """Run QC, saving file outputs in data dictionary.
    """
    run(None, data)
    stats_file, idxstats_file = _get_stats_files(data)
    data = tz.update_in(data, ["depth", "samtools", "stats"], lambda x: stats_file)
    data = tz.update_in(data, ["depth", "samtools", "idxstats"], lambda x: idxstats_file)
    return data

extract_fns = {("variants", "samples"): _get_vcf_samples,
                   ("align_bam",): _get_bam_samples}
    complex = {k: {} for k in extract_fns.keys()}
    for data in items:
        for k in complex:
            v = tz.get_in(k, data)
            if v is not None:
                for s in extract_fns[k](v, items):
                    if s:
                        complex[k][s] = v
    out = []
    for data in items:
        for k in complex:
            newv = tz.get_in([k, dd.get_sample_name(data)], complex)
            if newv:
                data = tz.update_in(data, k, lambda x: newv)
        out.append(data)
    return out

ref_file = dd.get_ref_file(data)
    for target in ["variant_regions", "sv_regions", "coverage"]:
        val = tz.get_in(["config", "algorithm", target], data)
        if val and not os.path.exists(val) and not objectstore.is_remote(val):
            installed_vals = []
            # Check prioritize directory
            for ext in [".bed", ".bed.gz"]:
                installed_vals += glob.glob(os.path.normpath(os.path.join(os.path.dirname(ref_file), os.pardir,
                                                                          "coverage", val + ext)))
            if len(installed_vals) == 0:
                if target not in special_targets or not val.startswith(special_targets[target]):
                    raise ValueError("Configuration problem. BED file not found for %s: %s" %
                                     (target, val))
            else:
                assert len(installed_vals) == 1, installed_vals
                data = tz.update_in(data, ["config", "algorithm", target], lambda x: installed_vals[0])
    return data

def _compare_dicts(self, orig, new, ns):
        out = {}
        for key, val in new.items():
            nskey = ns + [key]
            orig_val = tz.get_in([key], orig)
            if isinstance(val, dict) and isinstance(orig_val, dict):
                for nkey, nval in self._compare_dicts(orig_val or {}, val or {}, nskey).items():
                    out = self._merge(out, {nkey: nval})
            elif val != orig_val:
                out = tz.update_in(out, nskey, lambda x: copy.deepcopy(val))
        return out

return (val == "File" or (isinstance(val, (list, tuple)) and
                                  ("File" in val or any(isinstance(x, dict) and _is_file(val)) for x in val)))
    secondary_files = inp_tool.pop("secondaryFiles", None)
    if secondary_files:
        key = []
        while (not _is_file(tz.get_in(key + ["type"], inp_tool))
               and not _is_file(tz.get_in(key + ["items"], inp_tool))
               and not _is_file(tz.get_in(key + ["items", "items"], inp_tool))):
            key.append("type")
        if tz.get_in(key, inp_tool):
            inp_tool["secondaryFiles"] = secondary_files
        elif inp_binding:
            nested_inp_binding = copy.deepcopy(inp_binding)
            nested_inp_binding["prefix"] = "ignore="
            nested_inp_binding["secondaryFiles"] = secondary_files
            inp_tool = tz.update_in(inp_tool, key, lambda x: nested_inp_binding)
    return inp_tool

print("Dumping genome resources to %s." % resource_file)
    resource_dict = {"version": 1}
    if args.gtf:
        transcripts = ["rnaseq", "transcripts"]
        mask = ["rnaseq", "transcripts_mask"]
        index = ["rnaseq", "transcriptome_index", "tophat"]
        dexseq = ["rnaseq", "dexseq"]
        refflat = ["rnaseq", "refflat"]
        rRNA_fa = ["rnaseq", "rRNA_fa"]
        resource_dict = tz.update_in(resource_dict, transcripts,
                                     lambda x: "../rnaseq/ref-transcripts.gtf")
        resource_dict = tz.update_in(resource_dict, mask,
                                     lambda x: "../rnaseq/ref-transcripts-mask.gtf")
        resource_dict = tz.update_in(resource_dict, index,
                                     lambda x: "../rnaseq/tophat/%s_transcriptome.ver" % args.build)
        resource_dict = tz.update_in(resource_dict, refflat,
                                     lambda x: "../rnaseq/ref-transcripts.refFlat")
        resource_dict = tz.update_in(resource_dict, dexseq,
                                     lambda x: "../rnaseq/ref-transcripts.dexseq.gff3")
        resource_dict = tz.update_in(resource_dict, rRNA_fa,
                                     lambda x: "../rnaseq/rRNA.fa")
    if args.mirbase:
        srna_gtf = ["srnaseq", "srna_transcripts"]
        srna_mirbase = ["srnaseq", "mirbase_hairpin"]
        resource_dict = tz.update_in(resource_dict, srna_gtf,
                                     lambda x: "../srnaseq/srna-transcripts.gtf")
        resource_dict = tz.update_in(resource_dict, srna_mirbase,
                                     lambda x: "../srnaseq/hairpin.fa")
    # write out resource dictionarry
    with file_transaction(resource_file) as tx_resource_file:
        with open(tx_resource_file, "w") as out_handle:
            out_handle.write(yaml.dump(resource_dict, default_flow_style=False))