def set_current_task(workflow_id, task_id):
workflow_model = session.query(WorkflowModel).filter_by(
id=workflow_id).first()
processor = WorkflowProcessor(workflow_model)
task_id = uuid.UUID(task_id)
spiff_task = processor.bpmn_workflow.get_task(task_id)
_verify_user_and_role(processor, spiff_task)
user_uid = g.user.uid
if spiff_task.state != spiff_task.COMPLETED and spiff_task.state != spiff_task.READY:
raise ApiError(
"invalid_state",
"You may not move the token to a task who's state is not "
"currently set to COMPLETE or READY.")
# Only reset the token if the task doesn't already have it.
if spiff_task.state == spiff_task.COMPLETED:
spiff_task.reset_token(
reset_data=True
) # Don't try to copy the existing data back into this task.
processor.save()
WorkflowService.log_task_action(user_uid, processor, spiff_task,
WorkflowService.TASK_ACTION_TOKEN_RESET)
WorkflowService.update_task_assignments(processor)
workflow_api_model = WorkflowService.processor_to_workflow_api(
processor, spiff_task)
return WorkflowApiSchema().dump(workflow_api_model)
def get_workflow_from_spec(spec_id):
workflow_model = WorkflowService.get_workflow_from_spec(spec_id, g.user)
processor = WorkflowProcessor(workflow_model)
processor.do_engine_steps()
processor.save()
WorkflowService.update_task_assignments(processor)
workflow_api_model = WorkflowService.processor_to_workflow_api(processor)
return WorkflowApiSchema().dump(workflow_api_model)
def test_total_tasks_updated(self, mock_docs):
"""Assure that as a users progress is available when getting a list of studies for that user."""
app.config['PB_ENABLED'] = True
docs_response = self.protocol_builder_response('required_docs.json')
mock_docs.return_value = json.loads(docs_response)
user = self.create_user_with_study_and_workflow()
# The load example data script should set us up a user and at least one study, one category, and one workflow.
studies = StudyService.get_studies_for_user(user)
self.assertTrue(len(studies) == 1)
self.assertTrue(len(studies[0].categories) == 1)
self.assertTrue(len(studies[0].categories[0].workflows) == 1)
workflow = next(iter(
studies[0].categories[0].workflows)) # Workflows is a set.
# workflow should not be started, and it should have 0 completed tasks, and 0 total tasks.
self.assertEqual(WorkflowStatus.not_started, workflow.status)
self.assertEqual(0, workflow.total_tasks)
self.assertEqual(0, workflow.completed_tasks)
# Initialize the Workflow with the workflow processor.
workflow_model = db.session.query(WorkflowModel).filter(
WorkflowModel.id == workflow.id).first()
processor = WorkflowProcessor(workflow_model)
# Assure the workflow is now started, and knows the total and completed tasks.
studies = StudyService.get_studies_for_user(user)
workflow = next(iter(
studies[0].categories[0].workflows)) # Workflows is a set.
# self.assertEqual(WorkflowStatus.user_input_required, workflow.status)
self.assertTrue(workflow.total_tasks > 0)
self.assertEqual(0, workflow.completed_tasks)
self.assertIsNotNone(workflow.spec_version)
# Complete a task
task = processor.next_task()
processor.complete_task(task)
processor.save()
# Assure the workflow has moved on to the next task.
studies = StudyService.get_studies_for_user(user)
workflow = next(iter(
studies[0].categories[0].workflows)) # Workflows is a set.
self.assertEqual(1, workflow.completed_tasks)
# Get approvals
approvals = StudyService.get_approvals(studies[0].id)
self.assertGreater(len(approvals), 0)
self.assertIsNotNone(approvals[0]['display_order'])
def get_workflow(workflow_id, do_engine_steps=True):
"""Retrieve workflow based on workflow_id, and return it in the last saved State.
If do_engine_steps is False, return the workflow without running any engine tasks or logging any events. """
workflow_model: WorkflowModel = session.query(WorkflowModel).filter_by(
id=workflow_id).first()
processor = WorkflowProcessor(workflow_model)
if do_engine_steps:
processor.do_engine_steps()
processor.save()
WorkflowService.update_task_assignments(processor)
workflow_api_model = WorkflowService.processor_to_workflow_api(processor)
return WorkflowApiSchema().dump(workflow_api_model)
def test_timer_event(self):
workflow = self.create_workflow('timer_event')
processor = WorkflowProcessor(workflow)
processor.do_engine_steps()
task = processor.next_task()
processor.complete_task(task)
tasks = processor.get_ready_user_tasks()
self.assertEqual(tasks, [])
processor.save()
time.sleep(.3) # our timer is at .25 sec so we have to wait for it
# get done waiting
WorkflowService.do_waiting()
wf = db.session.query(WorkflowModel).filter(
WorkflowModel.id == workflow.id).first()
self.assertTrue(wf.status != WorkflowStatus.waiting)
def test_waiting_event_error(self):
workflow = self.create_workflow('timer_event_error')
processor = WorkflowProcessor(workflow)
processor.do_engine_steps()
processor.save()
time.sleep(.3) # our timer is at .25 sec so we have to wait for it
# get done waiting
wf = db.session.query(WorkflowModel).filter(
WorkflowModel.id == workflow.id).first()
self.assertTrue(wf.status == WorkflowStatus.waiting)
with self.assertLogs('crc', level='ERROR') as cm:
WorkflowService.do_waiting()
self.assertEqual(1, len(cm.output))
self.assertRegex(cm.output[0], f"workflow #%i" % workflow.id)
self.assertRegex(cm.output[0], f"study #%i" % workflow.study_id)
self.assertTrue(wf.status == WorkflowStatus.erroring)
def test_load_irb_from_db(self, mock_study_service):
# This depends on getting a list of investigators back from the protocol builder.
mock_study_service.return_value = self.mock_investigator_response
self.load_example_data()
workflow_spec_model = self.create_workflow("irb_api_personnel")
study = session.query(StudyModel).first()
processor = WorkflowProcessor(workflow_spec_model)
processor.do_engine_steps()
task_list = processor.get_ready_user_tasks()
processor.complete_task(task_list[0])
processor.do_engine_steps()
nav_list = processor.bpmn_workflow.get_flat_nav_list()
processor.save()
# reload after save
processor = WorkflowProcessor(workflow_spec_model)
nav_list2 = processor.bpmn_workflow.get_flat_nav_list()
self.assertEqual(nav_list, nav_list2)
def update_task(workflow_id, task_id, body, terminate_loop=None):
workflow_model = session.query(WorkflowModel).filter_by(
id=workflow_id).first()
if workflow_model is None:
raise ApiError("invalid_workflow_id",
"The given workflow id is not valid.",
status_code=404)
elif workflow_model.study is None:
raise ApiError("invalid_study",
"There is no study associated with the given workflow.",
status_code=404)
processor = WorkflowProcessor(workflow_model)
task_id = uuid.UUID(task_id)
spiff_task = processor.bpmn_workflow.get_task(task_id)
_verify_user_and_role(processor, spiff_task)
if not spiff_task:
raise ApiError("empty_task",
"Processor failed to obtain task.",
status_code=404)
if spiff_task.state != spiff_task.READY:
raise ApiError(
"invalid_state",
"You may not update a task unless it is in the READY state. "
"Consider calling a token reset to make this task Ready.")
if terminate_loop:
spiff_task.terminate_loop()
spiff_task.update_data(body)
processor.complete_task(spiff_task)
processor.do_engine_steps()
processor.save()
# Log the action, and any pending task assignments in the event of lanes in the workflow.
WorkflowService.log_task_action(g.user.uid, processor, spiff_task,
WorkflowService.TASK_ACTION_COMPLETE)
WorkflowService.update_task_assignments(processor)
workflow_api_model = WorkflowService.processor_to_workflow_api(processor)
return WorkflowApiSchema().dump(workflow_api_model)