def test_executes(self, mock_hook):
mock_instance = mock_hook.return_value
mock_instance.run_pipeline.return_value = TEST_OPERATION
operator = LifeSciencesRunPipelineOperator(
task_id='task-id', body=TEST_BODY, location=TEST_LOCATION, project_id=TEST_PROJECT_ID
)
result = operator.execute(None)
assert result == TEST_OPERATION
def test_executes_without_project_id(self, mock_hook):
mock_instance = mock_hook.return_value
mock_instance.run_pipeline.return_value = TEST_OPERATION
operator = LifeSciencesRunPipelineOperator(
task_id='task-id',
body=TEST_BODY,
location=TEST_LOCATION,
)
result = operator.execute(None)
self.assertEqual(result, TEST_OPERATION)
"machineType": "n1-standard-1",
},
},
}
}
# [END howto_configure_multiple_action_pipeline]
with models.DAG(
"example_gcp_life_sciences",
default_args=dict(start_date=dates.days_ago(1)),
schedule_interval=None,
tags=['example'],
) as dag:
# [START howto_run_pipeline]
simple_life_science_action_pipeline = LifeSciencesRunPipelineOperator(
task_id='simple-action-pipeline',
body=SIMPLE_ACTION_PIEPELINE,
project_id=PROJECT_ID,
location=LOCATION,
)
# [END howto_run_pipeline]
multiple_life_science_action_pipeline = LifeSciencesRunPipelineOperator(
task_id='multi-action-pipeline',
body=MULTI_ACTION_PIPELINE,
project_id=PROJECT_ID,
location=LOCATION)
simple_life_science_action_pipeline >> multiple_life_science_action_pipeline