Gauge and Counter allocate alot of memory

Hey, I've noticed that a prometheus Gauge or Counter object needs alot of memory. Is this a normal/expected behaviour?

import prometheus_client
import objsize
labels={}
labels['test']='test'

print("Memory Registry at Start: " +str(objsize.get_deep_size(prometheus_client.REGISTRY)))
print("Memory Labels as dict: "+ str(objsize.get_deep_size(labels)))
gauge = prometheus_client.Gauge("test", "", list(sorted(labels.keys())))
gauge.labels(**labels).set(10)
print("Memory Gauge object: "+ str(objsize.get_deep_size(gauge)))
print("Memory Registry after one Gauge: "+str(objsize.get_deep_size(prometheus_client.REGISTRY)))
gauge2 = prometheus_client.Gauge("test2", "")
gauge2.set(10)
print("Memory Gauge object: "+ str(objsize.get_deep_size(gauge2)))
print("Memory Registry after second Gauge: "+str(objsize.get_deep_size(prometheus_client.REGISTRY)))
counter = prometheus_client.Counter("test3", "", list(sorted(labels.keys())))
counter.labels(**labels).inc(10)
print("Memory counter object: "+str(objsize.get_deep_size(counter)))
print("Memory Registry after Counter: "+str(objsize.get_deep_size(prometheus_client.REGISTRY)))
labels={}
labels['test']='test2'
gauge.labels(**labels).set(10)
print("Memory Gauge second label: "+str(objsize.get_deep_size(gauge)))
print("Memory Registry end: "+str(objsize.get_deep_size(prometheus_client.REGISTRY)))

results in this memory usage:

Memory Registry at Start: 3988
Memory Labels as dict: 285
Memory Gauge object: 2418
Memory Registry after one Gauge: 6725
Memory Gauge object: 1051
Memory Registry after second Gauge: 7723
Memory counter object: 2108
Memory Registry after Counter: 10027
Memory Gauge second label: 3376
Memory Registry end: 10931

In this Blog Post https://www.robustperception.io/memory-usage-of-prometheus-client-libraries/ ( I know it's old) a counter needed way less memory than in my usecase. I'm using python 3.9, on windows(but i've got the same problem in a docker container) and prometheus-client 0.17.0

Commencez par exécuter le reproducteur Python fourni avec prometheus-client 0.17.0 et Python 3.9, en mesurant à la fois les objets métriques individuels et prometheus_client.REGISTRY. Le travail est considéré comme terminé lorsqu’il est établi que les allocations signalées sont attendues ou qu’une régression mémoire concrète est identifiée, avec une cible de test ou de documentation précise si le dépôt en fournit une.