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from __future__ import annotations

from datetime import datetime

from airflow import DAG
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.providers.amazon.aws.hooks.rds import RdsHook
from airflow.providers.amazon.aws.operators.rds import (
    RdsCancelExportTaskOperator,
    RdsCreateDbInstanceOperator,
    RdsCreateDbSnapshotOperator,
    RdsDeleteDbInstanceOperator,
    RdsDeleteDbSnapshotOperator,
    RdsStartExportTaskOperator,
)
from airflow.providers.amazon.aws.operators.s3 import S3CreateBucketOperator, S3DeleteBucketOperator
from airflow.providers.amazon.aws.sensors.rds import RdsExportTaskExistenceSensor, RdsSnapshotExistenceSensor
from airflow.utils.trigger_rule import TriggerRule
from tests.system.providers.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder

DAG_ID = "example_rds_export"

# Externally fetched variables:
KMS_KEY_ID_KEY = "KMS_KEY_ID"
ROLE_ARN_KEY = "ROLE_ARN"

sys_test_context_task = (
    SystemTestContextBuilder().add_variable(KMS_KEY_ID_KEY).add_variable(ROLE_ARN_KEY).build()
)


@task
def get_snapshot_arn(snapshot_name: str) -> str:
    result = RdsHook().conn.describe_db_snapshots(DBSnapshotIdentifier=snapshot_name)
    return result["DBSnapshots"][0]["DBSnapshotArn"]


with DAG(
    dag_id=DAG_ID,
    schedule="@once",
    start_date=datetime(2021, 1, 1),
    tags=["example"],
    catchup=False,
) as dag:
    test_context = sys_test_context_task()
    env_id = test_context[ENV_ID_KEY]

    bucket_name: str = f"{env_id}-bucket"

    rds_db_name: str = f"{env_id}_db"
    rds_instance_name: str = f"{env_id}-instance"
    rds_snapshot_name: str = f"{env_id}-snapshot"
    rds_export_task_id: str = f"{env_id}-export-task"

    create_bucket = S3CreateBucketOperator(
        task_id="create_bucket",
        bucket_name=bucket_name,
    )

    create_db_instance = RdsCreateDbInstanceOperator(
        task_id="create_db_instance",
        db_instance_identifier=rds_instance_name,
        db_instance_class="db.t4g.micro",
        engine="postgres",
        rds_kwargs={
            "MasterUsername": "rds_username",
            # NEVER store your production password in plaintext in a DAG like this.
            # Use Airflow Secrets or a secret manager for this in production.
            "MasterUserPassword": "rds_password",
            "AllocatedStorage": 20,
            "DBName": rds_db_name,
            "PubliclyAccessible": False,
        },
    )

    create_snapshot = RdsCreateDbSnapshotOperator(
        task_id="create_snapshot",
        db_type="instance",
        db_identifier=rds_instance_name,
        db_snapshot_identifier=rds_snapshot_name,
    )

    await_snapshot = RdsSnapshotExistenceSensor(
        task_id="snapshot_sensor",
        db_type="instance",
        db_snapshot_identifier=rds_snapshot_name,
        target_statuses=["available"],
    )

    snapshot_arn = get_snapshot_arn(rds_snapshot_name)

    # [START howto_operator_rds_start_export_task]
    start_export = RdsStartExportTaskOperator(
        task_id="start_export",
        export_task_identifier=rds_export_task_id,
        source_arn=snapshot_arn,
        s3_bucket_name=bucket_name,
        s3_prefix="rds-test",
        iam_role_arn=test_context[ROLE_ARN_KEY],
        kms_key_id=test_context[KMS_KEY_ID_KEY],
    )
    # [END howto_operator_rds_start_export_task]

    # RdsStartExportTaskOperator waits by default, setting as False to test the Sensor below.
    start_export.wait_for_completion = False

    # [START howto_operator_rds_cancel_export]
    cancel_export = RdsCancelExportTaskOperator(
        task_id="cancel_export",
        export_task_identifier=rds_export_task_id,
    )
    # [END howto_operator_rds_cancel_export]
    cancel_export.check_interval = 10
    cancel_export.max_attempts = 120

    # [START howto_sensor_rds_export_task_existence]
    export_sensor = RdsExportTaskExistenceSensor(
        task_id="export_sensor",
        export_task_identifier=rds_export_task_id,
        target_statuses=["canceled"],
    )
    # [END howto_sensor_rds_export_task_existence]

    delete_snapshot = RdsDeleteDbSnapshotOperator(
        task_id="delete_snapshot",
        db_type="instance",
        db_snapshot_identifier=rds_snapshot_name,
        trigger_rule=TriggerRule.ALL_DONE,
    )

    delete_bucket = S3DeleteBucketOperator(
        task_id="delete_bucket",
        bucket_name=bucket_name,
        force_delete=True,
        trigger_rule=TriggerRule.ALL_DONE,
    )

    delete_db_instance = RdsDeleteDbInstanceOperator(
        task_id="delete_db_instance",
        db_instance_identifier=rds_instance_name,
        rds_kwargs={"SkipFinalSnapshot": True},
        trigger_rule=TriggerRule.ALL_DONE,
    )

    chain(
        # TEST SETUP
        test_context,
        create_bucket,
        create_db_instance,
        create_snapshot,
        await_snapshot,
        snapshot_arn,
        # TEST BODY
        start_export,
        cancel_export,
        export_sensor,
        # TEST TEARDOWN
        delete_snapshot,
        delete_bucket,
        delete_db_instance,
    )

    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)
test_run = get_test_run(dag)
