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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


port = k8s.V1ContainerPort(name="http", container_port=80)

init_environments = [k8s.V1EnvVar(name="key1", value="value1"), k8s.V1EnvVar(name="key2", value="value2")]

init_container = k8s.V1Container(
    name="init-container",
    image="ubuntu:16.04",
    env=init_environments,
    command=["bash", "-cx"],
    args=["echo 10"],
)

tolerations = [k8s.V1Toleration(key="key", operator="Equal", value="value")]

# [END howto_operator_k8s_cluster_resources]

ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
DAG_ID = "example_kubernetes_operator_async"

with DAG(
    dag_id=DAG_ID,
    schedule=None,
    start_date=datetime(2021, 1, 1),
    tags=["example"],
) as dag:
    k = KubernetesPodOperator(
        task_id="task_1aa",
        namespace="airflow",
        in_cluster=False,
        image="ubuntu:16.04",
        cmds=["bash", "-cx"],
        arguments=["echo", "10"],
        labels={"foo": "bar"},
        ports=[port],
        name="task_1a",
        on_finish_action="delete_pod",
        hostnetwork=False,
        tolerations=tolerations,
        init_containers=[init_container],
        deferrable=True,
    )

    # [START howto_operator_k8s_write_xcom_async]
    write_xcom_async = KubernetesPodOperator(
        task_id="task_1bb",
        namespace="airflow",
        image="alpine",
        cmds=["sh", "-c", "mkdir -p /airflow/xcom/;echo '[1,2,3,4]' > /airflow/xcom/return.json"],
        name="task_1b",
        do_xcom_push=True,
        on_finish_action="delete_pod",
        in_cluster=False,
        get_logs=True,
        deferrable=True,
    )