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"""
This is an example dag for using the KubernetesPodOperator.
"""
from __future__ import annotations
import os
from datetime import datetime
from kubernetes.client import models as k8s
from airflow import DAG
from airflow.operators.bash import BashOperator
from airflow.providers.cncf.kubernetes.operators.pod import KubernetesPodOperator
from airflow.providers.cncf.kubernetes.secret import Secret
# [START howto_operator_k8s_cluster_resources]
[docs]secret_file = Secret("volume", "/etc/sql_conn", "airflow-secrets", "sql_alchemy_conn")
[docs]secret_env = Secret("env", "SQL_CONN", "airflow-secrets", "sql_alchemy_conn")
[docs]secret_all_keys = Secret("env", None, "airflow-secrets-2")
[docs]volume_mount = k8s.V1VolumeMount(
name="test-volume", mount_path="/root/mount_file", sub_path=None, read_only=True
)
[docs]configmaps = [
k8s.V1EnvFromSource(config_map_ref=k8s.V1ConfigMapEnvSource(name="test-configmap-1")),
k8s.V1EnvFromSource(config_map_ref=k8s.V1ConfigMapEnvSource(name="test-configmap-2")),
]
[docs]volume = k8s.V1Volume(
name="test-volume",
persistent_volume_claim=k8s.V1PersistentVolumeClaimVolumeSource(claim_name="test-volume"),
)
[docs]port = k8s.V1ContainerPort(name="http", container_port=80)
[docs]init_container_volume_mounts = [
k8s.V1VolumeMount(mount_path="/etc/foo", name="test-volume", sub_path=None, read_only=True)
]
[docs]init_environments = [k8s.V1EnvVar(name="key1", value="value1"), k8s.V1EnvVar(name="key2", value="value2")]
[docs]init_container = k8s.V1Container(
name="init-container",
image="ubuntu:16.04",
env=init_environments,
volume_mounts=init_container_volume_mounts,
command=["bash", "-cx"],
args=["echo 10"],
)
[docs]affinity = k8s.V1Affinity(
node_affinity=k8s.V1NodeAffinity(
preferred_during_scheduling_ignored_during_execution=[
k8s.V1PreferredSchedulingTerm(
weight=1,
preference=k8s.V1NodeSelectorTerm(
match_expressions=[
k8s.V1NodeSelectorRequirement(key="disktype", operator="In", values=["ssd"])
]
),
)
]
),
pod_affinity=k8s.V1PodAffinity(
required_during_scheduling_ignored_during_execution=[
k8s.V1WeightedPodAffinityTerm(
weight=1,
pod_affinity_term=k8s.V1PodAffinityTerm(
label_selector=k8s.V1LabelSelector(
match_expressions=[
k8s.V1LabelSelectorRequirement(key="security", operator="In", values="S1")
]
),
topology_key="failure-domain.beta.kubernetes.io/zone",
),
)
]
),
)
[docs]tolerations = [k8s.V1Toleration(key="key", operator="Equal", value="value")]
# [END howto_operator_k8s_cluster_resources]
[docs]ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
[docs]DAG_ID = "example_kubernetes_operator_async"
with DAG(
dag_id=DAG_ID,
schedule=None,
start_date=datetime(2021, 1, 1),
tags=["example"],
) as dag:
[docs] k = KubernetesPodOperator(
task_id="kubernetes_task_async",
namespace="default",
image="ubuntu:16.04",
cmds=["bash", "-cx"],
arguments=["echo", "10"],
labels={"foo": "bar"},
secrets=[secret_file, secret_env, secret_all_keys],
ports=[port],
volumes=[volume],
volume_mounts=[volume_mount],
env_from=configmaps,
name="airflow-test-pod",
affinity=affinity,
on_finish_action="delete_pod",
hostnetwork=False,
tolerations=tolerations,
init_containers=[init_container],
priority_class_name="medium",
deferrable=True,
)
# [START howto_operator_async_log]
kubernetes_task_async_log = KubernetesPodOperator(
task_id="kubernetes_task_async_log",
namespace="kubernetes_task_async_log",
in_cluster=False,
name="astro_k8s_test_pod",
image="ubuntu",
cmds=[
"bash",
"-cx",
(
"i=0; "
"while [ $i -ne 100 ]; "
"do i=$(($i+1)); "
"echo $i; "
"sleep 1; "
"done; "
"mkdir -p /airflow/xcom/; "
'echo \'{"message": "good afternoon!"}\' > /airflow/xcom/return.json'
),
],
do_xcom_push=True,
deferrable=True,
get_logs=True,
logging_interval=5,
)
# [END howto_operator_async_log]
# [START howto_operator_k8s_private_image_async]
quay_k8s_async = KubernetesPodOperator(
task_id="kubernetes_private_img_task_async",
namespace="default",
image="quay.io/apache/bash",
image_pull_secrets=[k8s.V1LocalObjectReference("testquay")],
cmds=["bash", "-cx"],
arguments=["echo", "10", "echo pwd"],
labels={"foo": "bar"},
name="airflow-private-image-pod",
on_finish_action="delete_pod",
in_cluster=True,
get_logs=True,
deferrable=True,
)
# [END howto_operator_k8s_private_image_async]
# [START howto_operator_k8s_write_xcom_async]
write_xcom_async = KubernetesPodOperator(
task_id="kubernetes_write_xcom_task_async",
namespace="default",
image="alpine",
cmds=["sh", "-c", "mkdir -p /airflow/xcom/;echo '[1,2,3,4]' > /airflow/xcom/return.json"],
name="write-xcom",
do_xcom_push=True,
on_finish_action="delete_pod",
in_cluster=True,
get_logs=True,
deferrable=True,
)
pod_task_xcom_result_async = BashOperator(
task_id="pod_task_xcom_result_async",
bash_command="echo \"{{ task_instance.xcom_pull('write-xcom')[0] }}\"",
)
write_xcom_async >> pod_task_xcom_result_async
# [END howto_operator_k8s_write_xcom_async]
from tests.system.utils.watcher import watcher
# This test needs watcher in order to properly mark success/failure
# when "tearDown" task with trigger rule is part of the DAG
list(dag.tasks) >> watcher()
from tests.system.utils import get_test_run # noqa: E402
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)