When using KubernetesJobOperator in Apache Airflow and encountering issues where Jinja templating for jinja_job_args is treating Airflow time macros as string, shall we provide a mechanism similar to the templates_dict in KubernetesPodOperator?
e.g.
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.kubernetes_pod_operator import KubernetesPodOperator
default_args = {
'owner': 'airflow',
'start_date': datetime(2024, 1, 1),
'retries': 1,
'retry_delay': timedelta(minutes=5),
}
dag = DAG(
'my_dag',
default_args=default_args,
schedule_interval='@daily',
)
my_task = KubernetesPodOperator(
task_id='my_task',
namespace='my_namespace',
image='my_image:latest',
cmds=['/bin/bash', '-c'],
arguments=['echo', '{{ ds }}'], # Using time macro directly
templates_dict={'my_jinja_template': '{{ ds }}'}, # Template for Jinja templating
dag=dag,
)
When using KubernetesJobOperator in Apache Airflow and encountering issues where Jinja templating for jinja_job_args is treating Airflow time macros as string, shall we provide a mechanism similar to the templates_dict in KubernetesPodOperator? e.g.