Source code for tests.system.providers.amazon.aws.example_emr_notebook_execution

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from __future__ import annotations

from datetime import datetime

from airflow.models.baseoperator import chain
from airflow.models.dag import DAG
from airflow.providers.amazon.aws.operators.emr import (
    EmrStartNotebookExecutionOperator,
    EmrStopNotebookExecutionOperator,
)
from airflow.providers.amazon.aws.sensors.emr import EmrNotebookExecutionSensor
from tests.system.providers.amazon.aws.utils import ENV_ID_KEY, SystemTestContextBuilder

[docs]DAG_ID = "example_emr_notebook"
# Externally fetched variables:
[docs]EDITOR_ID_KEY = "EDITOR_ID"
[docs]CLUSTER_ID_KEY = "CLUSTER_ID"
[docs]sys_test_context_task = ( SystemTestContextBuilder().add_variable(EDITOR_ID_KEY).add_variable(CLUSTER_ID_KEY).build() )
with DAG( dag_id=DAG_ID, start_date=datetime(2021, 1, 1), schedule="@once", catchup=False, tags=["example"], ) as dag:
[docs] test_context = sys_test_context_task()
env_id = test_context[ENV_ID_KEY] editor_id = test_context[EDITOR_ID_KEY] cluster_id = test_context[CLUSTER_ID_KEY] # [START howto_operator_emr_start_notebook_execution] start_execution = EmrStartNotebookExecutionOperator( task_id="start_execution", editor_id=editor_id, cluster_id=cluster_id, relative_path="EMR-System-Test.ipynb", service_role="EMR_Notebooks_DefaultRole", ) # [END howto_operator_emr_start_notebook_execution] notebook_execution_id_1 = start_execution.output # [START howto_sensor_emr_notebook_execution] wait_for_execution_start = EmrNotebookExecutionSensor( task_id="wait_for_execution_start", notebook_execution_id=notebook_execution_id_1, target_states={"RUNNING"}, poke_interval=5, ) # [END howto_sensor_emr_notebook_execution] # [START howto_operator_emr_stop_notebook_execution] stop_execution = EmrStopNotebookExecutionOperator( task_id="stop_execution", notebook_execution_id=notebook_execution_id_1, ) # [END howto_operator_emr_stop_notebook_execution] wait_for_execution_stop = EmrNotebookExecutionSensor( task_id="wait_for_execution_stop", notebook_execution_id=notebook_execution_id_1, target_states={"STOPPED"}, poke_interval=5, ) finish_execution = EmrStartNotebookExecutionOperator( task_id="finish_execution", editor_id=editor_id, cluster_id=cluster_id, relative_path="EMR-System-Test.ipynb", service_role="EMR_Notebooks_DefaultRole", ) notebook_execution_id_2 = finish_execution.output wait_for_execution_finish = EmrNotebookExecutionSensor( task_id="wait_for_execution_finish", notebook_execution_id=notebook_execution_id_2, poke_interval=5, ) chain( # TEST SETUP test_context, # TEST BODY start_execution, wait_for_execution_start, stop_execution, wait_for_execution_stop, finish_execution, # TEST TEARDOWN wait_for_execution_finish, ) 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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