How to use the pympler.muppy.get_objects function in Pympler

def request(ctx, flow):
    global step, ssl
    print("==========")
    print("GC: {}".format(gc.collect()))
    print("Threads: {}".format(threading.active_count()))

    step += 1
    if step == 1:
        all_objects = muppy.get_objects()
        ssl = muppy.filter(all_objects, SSL.Connection)[0]
    if step == 2:
        ib = refbrowser.InteractiveBrowser(ssl, 2, str_fun, repeat=False)
        del ssl  # do this to unpollute view
        ib.main(True)
        # print("\r\n".join(str(x)[:100] for x in gc.get_referrers(ssl)))

def _get_stats():
        from pympler import muppy, summary
        all_objects = muppy.get_objects()
        result = summary.summarize(all_objects)
        result = result[0:20]
        summary = '\n'.join([l for l in summary.format_(result)])
        result = '%s\n\n%s' % (summary, json.dumps(result))
        return result, 200, {'content-type': 'text/plain'}

def printmemory(sig, currentframe):
    try:
        from pympler import muppy, summary

        muppy.get_objects
    except ImportError:
        return

    all_objects = muppy.get_objects()
    sum1 = summary.summarize(all_objects)
    path = mempathformat % {"time": time.time(), "pid": os.getpid()}
    with open(path, "w") as f:
        f.write("\n".join(summary.format_(sum1, limit=50, sort="#")))

def summary_track (now):
	global summary_tracker

	all_objects = muppy.get_objects ()
	#all_objects = muppy.filter (all_objects, Type = dict)
	#for each in all_objects:
	#	print (each)
	sum1 = summary.summarize (all_objects)
	summary.print_ (sum1)
	print ('-' * 79)
	if summary_tracker is None:
		summary_tracker = tracker.SummaryTracker ()
	summary_tracker.print_diff ()

def pympler_summary():
    if pympler is None:
        return "pympler not installed / not enabled"
    all_objects = pympler.muppy.get_objects()
    summ = pympler.summary.summarize(all_objects)
    pympler.summary.print_(summ)
    return "Printed to console"

except ImportError:
        print("WARNING: pympler not installed")
        return
    # from pympler.classtracker import ClassTracker
    # from pympler.classtracker_stats import HtmlStats
    global all_objects, obj_summary, class_tracker
    if all_objects is None:
        all_objects = muppy.get_objects()
        obj_summary = summary.summarize(all_objects)
        summary.print_(obj_summary)

        # class_tracker = ClassTracker()
        # class_tracker.track_class(FICSPlayer, trace=1)
        # class_tracker.track_class(ICGameModel, resolution_level=2, trace=1)
    else:
        obj_summary2 = summary.summarize(muppy.get_objects())
        diff = summary.get_diff(obj_summary, obj_summary2)
        summary.print_(diff, limit=200)

def dump_objs():
	global TRACKER
	if TRACKER is None:
		TRACKER = tracker.SummaryTracker()

	with open("obj_log.txt", "a") as fp:
		fp.write("Memory at {}\n".format(str(datetime.datetime.now())))
		try:
			all_objects = muppy.get_objects()
			sum1 = summary.summarize(all_objects)
			str_sum  = summary.format_(sum1)

			fp.write("Summary:\n")
			for line in str_sum:
				fp.write("	{}\n".format(line))
		except Exception:
			err = traceback.format_exc()
			fp.write("Error: \n")
			fp.write(err)

		try:
			str_diff = TRACKER.format_diff()
			fp.write("Diff:\n")
			for line in str_diff:
				fp.write("	{}\n".format(line))

def create_summary(self):
        """Return a summary.

        See also the notes on ignore_self in the class as well as the
        initializer documentation.

        """
        if not self.ignore_self:
            res = summary.summarize(muppy.get_objects())
        else:
            # If the user requested the data required to store summaries to be
            # ignored in the summaries, we need to identify all objects which
            # are related to each summary stored.
            # Thus we build a list of all objects used for summary storage as
            # well as a dictionary which tells us how often an object is
            # referenced by the summaries.
            # During this identification process, more objects are referenced,
            # namely int objects identifying referenced objects as well as the
            # corresponding count.
            # For all these objects it will be checked whether they are
            # referenced from outside the monitor's scope. If not, they will be
            # subtracted from the snapshot summary, otherwise they are
            # included (as this indicates that they are relevant to the
            # application).