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 import DAG
from airflow.decorators import task
from airflow.models.baseoperator import chain
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] # [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)

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