catalog/task/openshift-client-python/0.1

Python OpenShift Runner

OpenShift is a Kubernetes distribution from Red Hat which provides oc, the OpenShift CLI that complements kubectl for simplifying deployment and configuration applications on OpenShift. The following task can be used to interact with the openshift cluster via oc commands in a python script.

The set of possible scripts can be found in the docs here.

Pre-requisites

1. Need to have an OpenShift cluster up and running.
2. config file of the cluster needs to be mounted via the Secrets to the default location ~/.kube/ in order to obtain the cluster details.

Install the Task

kubectl apply -f https://raw.githubusercontent.com/tektoncd/catalog/master/task/openshift-client-python/0.1/openshift-client-python.yaml

Parameters

• SCRIPT: The python script which you want to run in the task. Default script would be :-

#!/usr/bin/python

import openshift as oc
print('OpenShift client version: {}'.format(oc.get_client_version()))
print('OpenShift server version: {}'.format(oc.get_server_version()))

Workspaces

• kubeconfig-mount: The following workspace is used to mount the config file of the kubeconfig from the Secrets.

The Secrets can be created by

oc create secret generic kubeconfig --from-file=config

TaskRun

apiVersion: tekton.dev/v1beta1
kind: TaskRun
metadata:
  name: openshift-client-python-run
spec:
  taskRef:
    name: openshift-client-python
  params:
    - name: SCRIPT
      value: |
        #!/usr/bin/python

        import openshift as oc

        print('OpenShift client version: {}'.format(oc.get_client_version()))
        print('OpenShift server version: {}'.format(oc.get_server_version()))
        
        # Set a project context for all inner `oc` invocations and limit execution to 10 minutes
        with oc.project('openshift-infra'), oc.timeout(10*60):
          # Print the list of qualified pod names (e.g. ['pod/xyz', 'pod/abc', ...]  in the current project
          print('Found the following pods in {}: {}'.format(oc.get_project_name(), oc.selector('pods').qnames()))

          # Read in the current state of the pod resources and represent them as python objects
          for pod_obj in oc.selector('pods').objects():
            
            # The APIObject class exposes several convenience methods for interacting with objects
            print('Analyzing pod: {}'.format(pod_obj.name()))
            pod_obj.print_logs(timestamps=True, tail=15)
            
            # If you need access to the underlying resource definition, get a Model instance for the resource
            pod_model = pod_obj.model
            
            # Model objects enable dot notation and allow you to navigate through resources
            # to an arbitrary depth without checking if any ancestor elements exist.
            # In the following example, there is no need for boilerplate like:
            #    `if .... 'ownerReferences' in pod_model['metadata'] ....`
            # Fields that do not resolve will always return oc.Missing which 
            # is a singleton and can also be treated as an empty dict.
            for owner in pod_model.metadata.ownerReferences:  # ownerReferences == oc.Missing if not present in resource
              # elements of a Model are also instances of Model or ListModel
              if owner.kind is not oc.Missing:  # Compare as singleton
                print('  pod owned by a {}'.format(owner.kind))  # e.g. pod was created by a StatefulSet
    
  workspaces:
    - name: kubeconfig-mount
      secret:
        secretName: kubeconfig