human
I wrote the below code

    def _mapfn(iter):
        for i in iter:
            worker_num = i
        spec = {}
        host = util.get_ip_address()
        ppid = os.getppid()
        job_name = ''
        task_index = (-1)
        os.environ['HADOOP_USER_NAME'] = getpass.getuser()
        if ('HADOOP_PREFIX' in os.environ):
            classpath = os.environ['CLASSPATH']
            hadoop_path = os.path.join(os.environ['HADOOP_PREFIX'], 'bin', 'hadoop')
            hadoop_classpath = subprocess.check_output([hadoop_path, 'classpath', '--glob']).decode()
            logging.debug('CLASSPATH:    {0}'.format(hadoop_classpath))
            os.environ['CLASSPATH'] = ((classpath + os.pathsep) + hadoop_classpath)
        for node in cluster_info:
            logging.info('node:    {0}'.format(node))
            (njob, nhost, nport, nppid) = (node['job_name'], node['host'], node['port'], node['ppid'])
            hosts = ([] if (njob not in spec) else spec[njob])
            hosts.append('{0}:{1}'.format(nhost, nport))
            spec[njob] = hosts
            if ((nhost == host) and (nppid == ppid)):
                (worker_num, job_name, task_index) = (node['worker_num'], node['job_name'], node['task_index'])
        mgr = _get_manager(cluster_info, host, ppid)
        ctx = TFNodeContext(worker_num, job_name, task_index, spec, defaultFS, working_dir, mgr)
        if background:
            if ((os.name == 'nt') or (platform.system() == 'Windows')):
                raise Exception('Background    mode    is    not    supported    on    Windows.')
            if (not os.environ.get('SPARK_REUSE_WORKER')):
                raise Exception("Background    mode    relies    reuse    of    python    worker    on    Spark.    This    config    'spark.python.worker.reuse'    is    not    enabled    on    Spark.    Please    enable    it    before    using    background.")
        if ((job_name == 'ps') or background):
            logging.info('Starting    TensorFlow    {0}:{1}    on    cluster    node    {2}    on    background   ...

What's a good function header?
 Here's a good function header?
assistant
#Here's a good function header.

def start(fn, tf_args, cluster_info, defaultFS, working_dir, background):