Source code for tests.system.amazon.aws.example_mwaa
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# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
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# software distributed under the License is distributed on an
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# KIND, either express or implied. See the License for the
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from __future__ import annotations
from datetime import datetime
from typing import TYPE_CHECKING
import boto3
from airflow.providers.amazon.aws.hooks.mwaa import MwaaHook
from airflow.providers.amazon.aws.hooks.sts import StsHook
from airflow.providers.amazon.aws.operators.mwaa import MwaaTriggerDagRunOperator
from airflow.providers.amazon.aws.sensors.mwaa import MwaaDagRunSensor
from tests_common.test_utils.version_compat import AIRFLOW_V_3_0_PLUS
if TYPE_CHECKING:
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
else:
if AIRFLOW_V_3_0_PLUS:
from airflow.sdk import DAG, chain, task
else:
# Airflow 2.10 compat
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from system.amazon.aws.utils import SystemTestContextBuilder
[docs]
DAG_ID = "example_mwaa"
# Externally fetched variables:
[docs]
EXISTING_ENVIRONMENT_NAME_KEY = "ENVIRONMENT_NAME"
[docs]
EXISTING_DAG_ID_KEY = "DAG_ID"
[docs]
ROLE_WITHOUT_INVOKE_REST_API_ARN_KEY = "ROLE_WITHOUT_INVOKE_REST_API_ARN"
[docs]
sys_test_context_task = (
SystemTestContextBuilder()
# NOTE: Creating a functional MWAA environment is time-consuming and requires
# manually creating and configuring an S3 bucket for DAG storage and a VPC with
# private subnets which is out of scope for this demo. To simplify this demo and
# make it run in a reasonable time, an existing MWAA environment already
# containing a DAG is required.
# Here's a quick start guide to create an MWAA environment using AWS CloudFormation:
# https://docs.aws.amazon.com/mwaa/latest/userguide/quick-start.html
# If creating the environment using the AWS console, make sure to have a VPC with
# at least 1 private subnet to be able to select the VPC while going through the
# environment creation steps in the console wizard.
# Make sure to set the environment variables with appropriate values
.add_variable(EXISTING_ENVIRONMENT_NAME_KEY)
.add_variable(EXISTING_DAG_ID_KEY)
.add_variable(ROLE_WITHOUT_INVOKE_REST_API_ARN_KEY)
.build()
)
@task
[docs]
def unpause_dag(env_name: str, dag_id: str):
mwaa_hook = MwaaHook()
response = mwaa_hook.invoke_rest_api(
env_name=env_name, path=f"/dags/{dag_id}", method="PATCH", body={"is_paused": False}
)
return not response["RestApiResponse"]["is_paused"]
# This task in the system test verifies that the MwaaHook's IAM fallback mechanism continues to work with
# the live MWAA API. This fallback depends on parsing a specific error message from the MWAA API, so we
# want to ensure we find out if the API response format ever changes. Unit tests cover this with mocked
# responses, but this system test validates against the real API.
@task
[docs]
def test_iam_fallback(role_to_assume_arn, mwaa_env_name):
assumed_role = StsHook().conn.assume_role(
RoleArn=role_to_assume_arn, RoleSessionName="MwaaSysTestIamFallback"
)
credentials = assumed_role["Credentials"]
session = boto3.Session(
aws_access_key_id=credentials["AccessKeyId"],
aws_secret_access_key=credentials["SecretAccessKey"],
aws_session_token=credentials["SessionToken"],
)
mwaa_hook = MwaaHook()
mwaa_hook.conn = session.client("mwaa")
response = mwaa_hook.invoke_rest_api(env_name=mwaa_env_name, path="/dags", method="GET")
return "dags" in response["RestApiResponse"]
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_name = test_context[EXISTING_ENVIRONMENT_NAME_KEY]
trigger_dag_id = test_context[EXISTING_DAG_ID_KEY]
restricted_role_arn = test_context[ROLE_WITHOUT_INVOKE_REST_API_ARN_KEY]
# [START howto_operator_mwaa_trigger_dag_run]
trigger_dag_run = MwaaTriggerDagRunOperator(
task_id="trigger_dag_run",
env_name=env_name,
trigger_dag_id=trigger_dag_id,
wait_for_completion=True,
)
# [END howto_operator_mwaa_trigger_dag_run]
# [START howto_sensor_mwaa_dag_run]
wait_for_dag_run = MwaaDagRunSensor(
task_id="wait_for_dag_run",
external_env_name=env_name,
external_dag_id=trigger_dag_id,
external_dag_run_id="{{ task_instance.xcom_pull(task_ids='trigger_dag_run')['RestApiResponse']['dag_run_id'] }}",
poke_interval=5,
)
# [END howto_sensor_mwaa_dag_run]
chain(
# TEST SETUP
test_context,
# TEST BODY
unpause_dag(env_name, trigger_dag_id),
trigger_dag_run,
wait_for_dag_run,
test_iam_fallback(restricted_role_arn, env_name),
)
from tests_common.test_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_common.test_utils.system_tests 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)