JQ vs Python for Kubernetes Object Parsing

Using JQ or Python for same results.

These days it’s hard to work with Kubernetes without touching JSON + JQ. However, I always struggle with its language. Some concepts are very hard to cover and I usually end up looking it up at Google, Stack Overflow. I generally struggle with easy tasks as printing output in one line etc.

See one real life example:

kubectl get deploy -A -o json | jq -c '.items[] | select((.metadata.name | contains("editor")) or (.metadata.name | contains("tool")) or (.metadata.name | contains("world"))) | {name: .metadata.name, chart: .metadata.labels.chart, appVersion: .metadata.labels.appVersion}'        

As you can see, this lists all deployments in your Kubernetes cluster as JSON objects and if existing deployment matches some sub-strings it will print different labels in one line. I tried to implement the same thing in Python and it came out great. It was surely a more pleasant experience than using?JQ.

from kubernetes import client, config


config.load_kube_config()


v1 = client.AppsV1Api()


deployments=v1.list_deployment_for_all_namespaces(pretty=True)


for i in deployments.items:
    if any (sub in i.metadata.name for sub in ['-tool', 'editor', 'xml', 'world']):
        print("name = {name}, chart={chart}, appVersion={appVersion}".format(name = i.metadata.name, chart=i.metadata.labels['chart'], appVersion=i.metadata.labels['appVersion']))        

Which method do you prefer?