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#
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#
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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
[docs]DAG_ID = "example_rds_export"
# Externally fetched variables:
[docs]KMS_KEY_ID_KEY = "KMS_KEY_ID"
[docs]ROLE_ARN_KEY = "ROLE_ARN"
[docs]sys_test_context_task = (
SystemTestContextBuilder().add_variable(KMS_KEY_ID_KEY).add_variable(ROLE_ARN_KEY).build()
)
@task
[docs]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:
[docs] 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
# [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)
[docs]test_run = get_test_run(dag)
