homelab/jobrunner/run_pipeline.py
2023-11-05 19:05:34 -06:00

48 lines
1.5 KiB
Python

from kubernetes import client, config
import string
import random
# Load the default kubeconfig
config.load_kube_config()
# Define the API client for batch jobs
api_instance = client.BatchV1Api()
def get_random_string(length):
# choose from all lowercase letter
letters = string.ascii_lowercase
result_str = "".join(random.choice(letters) for i in range(length))
return result_str
# Create a new job object
job = client.V1Job(
api_version="batch/v1",
kind="Job",
metadata=client.V1ObjectMeta(name=f"myjob{get_random_string(5)}"),
spec=client.V1JobSpec(
ttl_seconds_after_finished=100,
template=client.V1PodTemplateSpec(
metadata=client.V1ObjectMeta(
labels={"app": f"myjobspod{get_random_string(5)}"}
),
spec=client.V1PodSpec(
containers=[
client.V1Container(
name=f"myjobrunnercontainer{get_random_string(5)}",
image="registry.wayl.one/dummypipe:alpine",
command=["python", "pipeline.py"],
image_pull_policy="Always",
),
],
restart_policy="Never",
image_pull_secrets=[client.V1LocalObjectReference(name="regcred")],
),
),
backoff_limit=1,
),
)
# Call the Kubernetes API to create the job
api_instance.create_namespaced_job(namespace="jobrunner", body=job)