Source code for tests.system.providers.amazon.aws.example_step_functions
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from __future__ import annotations
import json
from datetime import datetime
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from airflow.providers.amazon.aws.hooks.step_function import StepFunctionHook
from airflow.providers.amazon.aws.operators.step_function import (
StepFunctionGetExecutionOutputOperator,
StepFunctionStartExecutionOperator,
)
from airflow.providers.amazon.aws.sensors.step_function import StepFunctionExecutionSensor
from tests.system.providers.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder
[docs]DAG_ID = "example_step_functions"
# Externally fetched variables:
[docs]ROLE_ARN_KEY = "ROLE_ARN"
[docs]sys_test_context_task = SystemTestContextBuilder().add_variable(ROLE_ARN_KEY).build()
[docs]STATE_MACHINE_DEFINITION = {
"StartAt": "Wait",
"States": {"Wait": {"Type": "Wait", "Seconds": 7, "Next": "Success"}, "Success": {"Type": "Succeed"}},
}
@task
[docs]def create_state_machine(env_id, role_arn):
# Create a Step Functions State Machine and return the ARN for use by
# downstream tasks.
return (
StepFunctionHook()
.get_conn()
.create_state_machine(
name=f"{DAG_ID}_{env_id}",
definition=json.dumps(STATE_MACHINE_DEFINITION),
roleArn=role_arn,
)["stateMachineArn"]
)
@task
[docs]def delete_state_machine(state_machine_arn):
StepFunctionHook().get_conn().delete_state_machine(stateMachineArn=state_machine_arn)
with DAG(
dag_id=DAG_ID,
schedule="@once",
start_date=datetime(2021, 1, 1),
tags=["example"],
catchup=False,
) as dag:
# This context contains the ENV_ID and any env variables requested when the
# task was built above. Access the info as you would any other TaskFlow task.
[docs] test_context = sys_test_context_task()
env_id = test_context[ENV_ID_KEY]
role_arn = test_context[ROLE_ARN_KEY]
state_machine_arn = create_state_machine(env_id, role_arn)
# [START howto_operator_step_function_start_execution]
start_execution = StepFunctionStartExecutionOperator(
task_id="start_execution", state_machine_arn=state_machine_arn
)
# [END howto_operator_step_function_start_execution]
execution_arn = start_execution.output
# [START howto_sensor_step_function_execution]
wait_for_execution = StepFunctionExecutionSensor(
task_id="wait_for_execution", execution_arn=execution_arn
)
# [END howto_sensor_step_function_execution]
wait_for_execution.poke_interval = 1
# [START howto_operator_step_function_get_execution_output]
get_execution_output = StepFunctionGetExecutionOutputOperator(
task_id="get_execution_output", execution_arn=execution_arn
)
# [END howto_operator_step_function_get_execution_output]
chain(
# TEST SETUP
test_context,
state_machine_arn,
# TEST BODY
start_execution,
wait_for_execution,
get_execution_output,
# TEST TEARDOWN
delete_state_machine(state_machine_arn),
)
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)