def create_cluster()

in airflow_dag_for_execution/simple_dag.py [0:0]

• 27 lines of code
• 1 McCabe index (conditional complexity)

def create_cluster():
    emr = boto3.client('emr', region_name=<FILL_IN_REGION, e.g. 'us-west-2'>)
    cluster = emr.run_job_flow(
        Name='Demo-Cluster',
        ReleaseLabel='emr-6.2.0',
        Applications=[{'Name': 'Spark'}, {'Name': 'Livy'}, {'Name': 'JupyterEnterpriseGateway'}],
        VisibleToAllUsers=True,
        Instances={
            'InstanceGroups': [
                {
                    'Name': "Master nodes",
                    'Market': 'ON_DEMAND',
                    'InstanceRole': 'MASTER',
                    'InstanceType': 'm5.xlarge',
                    'InstanceCount': 1,
                }
            ],
            'KeepJobFlowAliveWhenNoSteps': True,
            'TerminationProtected': False,
            'Ec2SubnetId': '<FILL_IN_SUBNET_ID, e.g subnet-123456>',
        },
        JobFlowRole='EMR_EC2_DefaultRole',
        ServiceRole='EMR_DefaultRole'
    )
    cluster_id = cluster['JobFlowId']
    print("Created an cluster: " + cluster_id)
    return cluster_id