Esempio n. 1
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    def test_should_throw_exception_when_circular_dependency_is_found(self):
        # given
        original_job = mock.Mock()
        job1, job2, job3, job4 = [
            WorkflowJob(original_job, i) for i in range(4)
        ]

        # job1 --- job2
        #   |        |
        #    \       |
        #     \      |
        #      \     |
        #       \    |
        #        \   |
        #         \  |
        #         job3

        job_graph = {job1: (job2, ), job2: (job3, ), job3: (job1, )}

        # expected
        with self.assertRaises(InvalidJobGraph):
            Definition(job_graph)

        # given

        # job1        job4
        #  |          | |
        #  |          | |
        #  |          | |
        # job2 ------ job3

        job_graph = {
            job1: (job2, ),
            job2: (job3, ),
            job3: (job4, ),
            job4: (job3, )
        }

        # expected
        with self.assertRaises(InvalidJobGraph):
            Definition(job_graph)
Esempio n. 2
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    def test_should_run_jobs_in_order_accordingly_to_graph_schema(self):
        # given
        original_job = mock.Mock()
        job1, job2, job3, job4, job5, job6, job7, job8, job9 = [
            WorkflowJob(original_job, i) for i in range(9)
        ]
        job_graph = OrderedDict([(job1, (job5, job6)), (job2, (job6, )),
                                 (job3, (job6, )), (job4, (job7, )),
                                 (job6, (job8, )), (job7, (job8, )),
                                 (job5, (job9, ))])

        #  job1     job2  job3  job4
        #    |  \    |    /      |
        #    |   \   |   /       |
        #    |    \  |  /        |
        #    |     \ | /         |
        #  job5    job6        job7
        #    |        \         /
        #    |         \       /
        #    |          \     /
        #    |           \   /
        #    |            \ /
        #   job9         job8

        definition = Definition(job_graph)
        workflow = Workflow(workflow_id='test_workflow',
                            definition=definition,
                            schedule_interval='@hourly',
                            runtime_as_datetime=True)

        # expected
        self.assertEqual(
            list(workflow.build_sequential_order()),
            [job1, job5, job9, job2, job3, job6, job4, job7, job8])

        # given
        job_graph = OrderedDict([(job1, (job5, job6, job7)), (job2, (job6, )),
                                 (job3, (job6, )), (job4, (job7, )),
                                 (job6, (job8, )), (job7, (job8, )),
                                 (job5, (job9, )), (job6, (job9, ))])

        #  job1     job2  job3  job4
        #    |  \    |    /      |
        #    |   \   |   /       |
        #    |    \  |  /        |
        #    |     \ | /         |
        #  job5    job6        job7
        #    |      / \         /
        #    |     /   \       /
        #    |    /     \     /
        #    |   /       \   /
        #    |  /         \ /
        #   job9         job8

        definition = Definition(job_graph)
        workflow = Workflow(workflow_id='test_workflow',
                            definition=definition,
                            schedule_interval='@hourly',
                            runtime_as_datetime=True)

        # expected
        self.assertEqual(
            workflow.build_sequential_order(),
            [job1, job5, job2, job3, job6, job9, job4, job7, job8])
Esempio n. 3
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from bigflow.workflow import Workflow
from bigflow.workflow import Definition
from .sequential_workflow import Job

job1, job2, job3, job4 = Job('1'), Job('2'), Job('3'), Job('4')

graph_workflow = Workflow(
    workflow_id='graph_workflow',
    definition=Definition({
        job1: [job2, job3],
        job2: [job4],
        job3: [job4],
    }),
)

if __name__ == '__main__':
    graph_workflow.run()
Esempio n. 4
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    def test_should_generate_DAG_file_from_workflow_with_hourly_scheduling(
            self, get_timezone_offset_seconds_mock):
        # given
        workdir = os.path.dirname(__file__)
        get_timezone_offset_seconds_mock.return_value = 2 * 3600
        docker_repository = 'eu.gcr.io/my_docker_repository_project/my-project'

        # given
        job1 = Job(id='job1',
                   component=mock.Mock(),
                   retry_count=10,
                   retry_pause_sec=20)
        job2 = Job(id='job2',
                   component=mock.Mock(),
                   retry_count=100,
                   retry_pause_sec=200)
        job3 = Job(id='job3',
                   component=mock.Mock(),
                   retry_count=100,
                   retry_pause_sec=200)
        w_job1 = WorkflowJob(job1, 1)
        w_job2 = WorkflowJob(job2, 2)
        w_job3 = WorkflowJob(job3, 3)
        graph = {w_job1: (w_job2, w_job3), w_job2: (w_job3, )}
        workflow = Workflow(workflow_id='my_workflow',
                            definition=Definition(graph),
                            start_time_factory=hourly_start_time,
                            schedule_interval='@hourly')

        # when
        dag_file_path = generate_dag_file(workdir, docker_repository, workflow,
                                          '2020-07-02 10:00:00', '0.3.0', 'ca')

        # then
        self.assertEqual(
            dag_file_path,
            workdir + '/.dags/my_workflow__v0_3_0__2020_07_02_10_00_00_dag.py')

        dag_file_content = Path(dag_file_path).read_text()
        expected_dag_content = '''
import datetime
from airflow import DAG
from airflow.contrib.operators import kubernetes_pod_operator

default_args = {
            'owner': 'airflow',
            'depends_on_past': True,
            'start_date': datetime.datetime(2020, 7, 2, 8, 0),
            'email_on_failure': False,
            'email_on_retry': False,
            'execution_timeout': datetime.timedelta(seconds=10800),
}

dag = DAG(
    'my_workflow__v0_3_0__2020_07_02_10_00_00',
    default_args=default_args,
    max_active_runs=1,
    schedule_interval='@hourly'
)


tjob1 = kubernetes_pod_operator.KubernetesPodOperator(
    task_id='job1',
    name='job1',
    cmds=['bf'],
    arguments=['run', '--job', 'my_workflow.job1', '--runtime', '{{ execution_date.strftime("%Y-%m-%d %H:%M:%S") }}', '--project-package', 'ca', '--config', '{{var.value.env}}'],
    namespace='default',
    image='eu.gcr.io/my_docker_repository_project/my-project:0.3.0',
    is_delete_operator_pod=True,
    retries=10,
    retry_delay=datetime.timedelta(seconds=20),
    dag=dag,
    execution_timeout=datetime.timedelta(seconds=10800))


tjob2 = kubernetes_pod_operator.KubernetesPodOperator(
    task_id='job2',
    name='job2',
    cmds=['bf'],
    arguments=['run', '--job', 'my_workflow.job2', '--runtime', '{{ execution_date.strftime("%Y-%m-%d %H:%M:%S") }}', '--project-package', 'ca', '--config', '{{var.value.env}}'],
    namespace='default',
    image='eu.gcr.io/my_docker_repository_project/my-project:0.3.0',
    is_delete_operator_pod=True,
    retries=100,
    retry_delay=datetime.timedelta(seconds=200),
    dag=dag,
    execution_timeout=datetime.timedelta(seconds=10800))

tjob2.set_upstream(tjob1)

tjob3 = kubernetes_pod_operator.KubernetesPodOperator(
    task_id='job3',
    name='job3',
    cmds=['bf'],
    arguments=['run', '--job', 'my_workflow.job3', '--runtime', '{{ execution_date.strftime("%Y-%m-%d %H:%M:%S") }}', '--project-package', 'ca', '--config', '{{var.value.env}}'],
    namespace='default',
    image='eu.gcr.io/my_docker_repository_project/my-project:0.3.0',
    is_delete_operator_pod=True,
    retries=100,
    retry_delay=datetime.timedelta(seconds=200),
    dag=dag,
    execution_timeout=datetime.timedelta(seconds=10800))

tjob3.set_upstream(tjob2)
tjob3.set_upstream(tjob1)
'''

        self.assert_files_are_equal(expected_dag_content, dag_file_content)
Esempio n. 5
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    def test_should_generate_DAG_file_from_workflow_with_daily_scheduling(
            self):
        # given
        workdir = os.path.dirname(__file__)
        docker_repository = 'eu.gcr.io/my_docker_repository_project/my-project'

        # given
        job1 = Job(id='job1',
                   component=mock.Mock(),
                   retry_count=10,
                   retry_pause_sec=20)
        w_job1 = WorkflowJob(job1, 1)
        graph = {w_job1: ()}
        workflow = Workflow(workflow_id='my_daily_workflow',
                            definition=Definition(graph),
                            schedule_interval='@daily')

        # when
        dag_file_path = generate_dag_file(workdir, docker_repository, workflow,
                                          '2020-07-01', '0.3.0', 'ca')

        # then
        self.assertEqual(
            dag_file_path, workdir +
            '/.dags/my_daily_workflow__v0_3_0__2020_07_01_00_00_00_dag.py')

        dag_file_content = Path(dag_file_path).read_text()
        expected_dag_content = '''    
from airflow import DAG
from datetime import timedelta
from datetime import datetime
from airflow.contrib.operators import kubernetes_pod_operator

default_args = {
            'owner': 'airflow',
            'depends_on_past': True,
            'start_date': datetime.strptime("2020-07-01", "%Y-%m-%d") - (timedelta(hours=24)),
            'email_on_failure': False,
            'email_on_retry': False,
            'execution_timeout': timedelta(minutes=90)
}

dag = DAG(
    'my_daily_workflow__v0_3_0__2020_07_01_00_00_00',
    default_args=default_args,
    max_active_runs=1,
    schedule_interval='@daily'
)


tjob1 = kubernetes_pod_operator.KubernetesPodOperator(
    task_id='job1',
    name='job1',
    cmds=['bf'],
    arguments=['run', '--job', 'my_daily_workflow.job1', '--runtime', '{{ execution_date.strftime("%Y-%m-%d %H:%M:%S") }}', '--project-package', 'ca', '--config', '{{var.value.env}}'],
    namespace='default',
    image='eu.gcr.io/my_docker_repository_project/my-project:0.3.0',
    is_delete_operator_pod=True,
    retries=10,
    retry_delay= timedelta(seconds=20),
    dag=dag)            

'''
        self.assert_files_are_equal(expected_dag_content, dag_file_content)
Esempio n. 6
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from bigflow.workflow import Workflow
from bigflow.workflow import Definition
from .sequential_workflow import Job

job1, job2, job3, job4 = Job('1'), Job('2'), Job('3'), Job('4')

graph_workflow = Workflow(workflow_id='graph_workflow',
                          definition=Definition({
                              job1: (job2, job3),
                              job2: (job4, ),
                              job3: (job4, )
                          }))

if __name__ == '__main__':
    graph_workflow.run()