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from __future__ import annotations

from datetime import datetime
from operator import itemgetter

import boto3

from airflow import DAG
from airflow.decorators import task
from airflow.models.baseoperator import chain
from import EC2StartInstanceOperator, EC2StopInstanceOperator
from import EC2InstanceStateSensor
from airflow.utils.trigger_rule import TriggerRule
from import ENV_ID_KEY, SystemTestContextBuilder

[docs]DAG_ID = "example_ec2"
[docs]sys_test_context_task = SystemTestContextBuilder().build()
def _get_latest_ami_id(): """Returns the AMI ID of the most recently-created Amazon Linux image""" # Amazon is retiring AL2 in 2023 and replacing it with Amazon Linux 2022. # This image prefix should be futureproof, but may need adjusting depending # on how they name the new images. This page should have AL2022 info when # it comes available: image_prefix = "Amazon Linux*" images = boto3.client("ec2").describe_images( Filters=[{"Name": "description", "Values": [image_prefix]}], Owners=["amazon"] ) # Sort on CreationDate sorted_images = sorted(images["Images"], key=itemgetter("CreationDate"), reverse=True) return sorted_images[0]["ImageId"] @task
[docs]def create_key_pair(key_name: str): client = boto3.client("ec2") key_pair_id = client.create_key_pair(KeyName=key_name)["KeyName"] # Creating the key takes a very short but measurable time, preventing race condition: client.get_waiter("key_pair_exists").wait(KeyNames=[key_pair_id]) return key_pair_id
[docs]def create_instance(instance_name: str, key_pair_id: str): client = boto3.client("ec2") # Create the instance instance_id = client.run_instances( ImageId=_get_latest_ami_id(), MinCount=1, MaxCount=1, InstanceType="t2.micro", KeyName=key_pair_id, TagSpecifications=[{"ResourceType": "instance", "Tags": [{"Key": "Name", "Value": instance_name}]}], )["Instances"][0]["InstanceId"] # Wait for it to exist waiter = client.get_waiter("instance_exists") waiter.wait(InstanceIds=[instance_id]) return instance_id
[docs]def terminate_instance(instance: str): boto3.client("ec2").terminate_instances(InstanceIds=[instance])
[docs]def delete_key_pair(key_pair_id: str): boto3.client("ec2").delete_key_pair(KeyName=key_pair_id)
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] key_name = create_key_pair(key_name=f"{env_id}_key_pair") instance_id = create_instance(instance_name=f"{env_id}-instance", key_pair_id=key_name) # [START howto_operator_ec2_start_instance] start_instance = EC2StartInstanceOperator( task_id="start_instance", instance_id=instance_id, ) # [END howto_operator_ec2_start_instance] # [START howto_sensor_ec2_instance_state] await_instance = EC2InstanceStateSensor( task_id="await_instance", instance_id=instance_id, target_state="running", ) # [END howto_sensor_ec2_instance_state] # [START howto_operator_ec2_stop_instance] stop_instance = EC2StopInstanceOperator( task_id="stop_instance", instance_id=instance_id, ) # [END howto_operator_ec2_stop_instance] stop_instance.trigger_rule = TriggerRule.ALL_DONE chain( # TEST SETUP test_context, key_name, instance_id, # TEST BODY start_instance, await_instance, stop_instance, # TEST TEARDOWN terminate_instance(instance_id), delete_key_pair(key_name), ) 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/
[docs]test_run = get_test_run(dag)

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