sartography
/
cr-connect-workflow
mirror of https://github.com/sartography/cr-connect-workflow.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity
cr-connect-workflow/tests/workflow/test_workflow_spec_api.py

120 lines
6.1 KiB
Python
Raw Normal View History

Protocol builder connections
2020-02-20 18:30:04 +00:00
import json
I absolutely must fix our cascade deletes, but I sort of like the horror such chunks of code cause, we really need to protect these endpoints, and assure they never get called under normal circumstances, and raise some thoughtful errors.
2020-05-27 01:18:09 +00:00
from tests.base_test import BaseTest
Protocol builder connections
2020-02-20 18:30:04 +00:00
from crc import session
from crc.models.file import FileModel
Adds test for updating workflow spec
2020-03-16 16:32:39 +00:00
from crc.models.workflow import WorkflowSpecModel, WorkflowSpecModelSchema, WorkflowModel, WorkflowSpecCategoryModel
Protocol builder connections
2020-02-20 18:30:04 +00:00
Added test for new api endpoint to get all standalone workflow_specs. Modified test_add_new_workflow_specification to include new standalone argument
2021-04-26 12:56:21 +00:00
from example_data import ExampleDataLoader
Protocol builder connections
2020-02-20 18:30:04 +00:00
class TestWorkflowSpec(BaseTest):
def test_list_workflow_specifications(self):
self.load_example_data()
spec = session.query(WorkflowSpecModel).first()
rv = self.app.get('/v1.0/workflow-specification',
follow_redirects=True,
It became impossible to use the Swagger ui when we started adding authentication to all of the calls. I discovered Connexion and Swagger have a default way of handing JTW authentication and this cleans up our code quite a bit, moves the securing of endpoints into the API Definition, which is quite nice, and removes a whole library dependency (I never get to do that!) I added a SWAGGER_AUTH_KEY that can be used in non-production environments to allow users to quickly authenticate from the Swagger ui. I also removed all api calls to simple little happy api services, because that is just mean and pointless.
2020-03-24 18:15:21 +00:00
content_type="application/json",headers=self.logged_in_headers())
Protocol builder connections
2020-02-20 18:30:04 +00:00
self.assert_success(rv)
json_data = json.loads(rv.get_data(as_text=True))
specs = WorkflowSpecModelSchema(many=True).load(json_data, session=session)
spec2 = specs[0]
self.assertEqual(spec.id, spec2.id)
self.assertEqual(spec.display_name, spec2.display_name)
self.assertEqual(spec.description, spec2.description)
def test_add_new_workflow_specification(self):
If you name add a file to a workflow that has the exact same name as a Task Spec's ID, and an extension of "md", it wll use that file as the markdown content, and ignore the markdown in the documentation on the task spec. Moving the primary process id from the workflow model to the file model, and assuring it is updated properly. This was causing a bug that would "lose" the workflow.
2020-04-17 17:30:32 +00:00
self.load_example_data()
Protocol builder connections
2020-02-20 18:30:04 +00:00
num_before = session.query(WorkflowSpecModel).count()
Modified test to check for display_order within workflow category.
2021-01-27 16:08:28 +00:00
category_id = session.query(WorkflowSpecCategoryModel).first().id
category_count = session.query(WorkflowSpecModel).filter_by(category_id=category_id).count()
Adds workflow spec category to API
2020-03-16 16:10:32 +00:00
spec = WorkflowSpecModel(id='make_cookies', name='make_cookies', display_name='Cooooookies',
Added test for new api endpoint to get all standalone workflow_specs. Modified test_add_new_workflow_specification to include new standalone argument
2021-04-26 12:56:21 +00:00
description='Om nom nom delicious cookies', category_id=category_id,
standalone=False)
Requires login
2020-03-11 19:27:22 +00:00
rv = self.app.post('/v1.0/workflow-specification',
headers=self.logged_in_headers(),
content_type="application/json",
Protocol builder connections
2020-02-20 18:30:04 +00:00
data=json.dumps(WorkflowSpecModelSchema().dump(spec)))
self.assert_success(rv)
db_spec = session.query(WorkflowSpecModel).filter_by(id='make_cookies').first()
self.assertEqual(spec.display_name, db_spec.display_name)
num_after = session.query(WorkflowSpecModel).count()
self.assertEqual(num_after, num_before + 1)
Modified test to check for display_order within workflow category.
2021-01-27 16:08:28 +00:00
self.assertEqual(category_count, db_spec.display_order)
category_count_after = session.query(WorkflowSpecModel).filter_by(category_id=category_id).count()
self.assertEqual(category_count_after, category_count + 1)
Protocol builder connections
2020-02-20 18:30:04 +00:00
def test_get_workflow_specification(self):
self.load_example_data()
db_spec = session.query(WorkflowSpecModel).first()
Requires login
2020-03-11 19:27:22 +00:00
rv = self.app.get('/v1.0/workflow-specification/%s' % db_spec.id, headers=self.logged_in_headers())
Protocol builder connections
2020-02-20 18:30:04 +00:00
self.assert_success(rv)
json_data = json.loads(rv.get_data(as_text=True))
api_spec = WorkflowSpecModelSchema().load(json_data, session=session)
self.assertEqual(db_spec, api_spec)
Adds test for updating workflow spec
2020-03-16 16:32:39 +00:00
def test_update_workflow_specification(self):
self.load_example_data()
WIP: Adds default workflow spec categories
2020-03-27 19:32:07 +00:00
category_id = 99
category = WorkflowSpecCategoryModel(id=category_id, name='trap', display_name="It's a trap!", display_order=0)
Adds test for updating workflow spec
2020-03-16 16:32:39 +00:00
session.add(category)
session.commit()
db_spec_before: WorkflowSpecModel = session.query(WorkflowSpecModel).first()
spec_id = db_spec_before.id
Created a "StudyService" and moved all complex logic around study manipulation out of the study api, and this service, as things were getting complicated. The Workflow Processor no longer creates the WorkflowModel, the study object handles that, and only passes the model into the workflow processor when it is ready to start the workflow. Created a Study object (seperate from the StudyModel) that can cronstructed on request, and contains a different data structure than we store in the DB. This allows us to return underlying Categories and Workflows in a clean way. Added a new status to workflows called "not_started", meaning we have not yet instantiated a processor or created a BPMN, they have no version yet and no stored data, just the possiblity of being started. The Top Level Workflow or "Master" workflow is now a part of the sample data, and loaded at all times. Removed the ability to "add a workflow to a study" and "remove a workflow from a study", a study contains all possible workflows by definition. Example data no longer creates users or studies, it just creates the specs.
2020-03-30 12:00:16 +00:00
self.assertNotEqual(db_spec_before.category_id, category_id)
Adds test for updating workflow spec
2020-03-16 16:32:39 +00:00
Created a "StudyService" and moved all complex logic around study manipulation out of the study api, and this service, as things were getting complicated. The Workflow Processor no longer creates the WorkflowModel, the study object handles that, and only passes the model into the workflow processor when it is ready to start the workflow. Created a Study object (seperate from the StudyModel) that can cronstructed on request, and contains a different data structure than we store in the DB. This allows us to return underlying Categories and Workflows in a clean way. Added a new status to workflows called "not_started", meaning we have not yet instantiated a processor or created a BPMN, they have no version yet and no stored data, just the possiblity of being started. The Top Level Workflow or "Master" workflow is now a part of the sample data, and loaded at all times. Removed the ability to "add a workflow to a study" and "remove a workflow from a study", a study contains all possible workflows by definition. Example data no longer creates users or studies, it just creates the specs.
2020-03-30 12:00:16 +00:00
db_spec_before.category_id = category_id
Adds test for updating workflow spec
2020-03-16 16:32:39 +00:00
rv = self.app.put('/v1.0/workflow-specification/%s' % spec_id,
content_type="application/json",
headers=self.logged_in_headers(),
data=json.dumps(WorkflowSpecModelSchema().dump(db_spec_before)))
self.assert_success(rv)
json_data = json.loads(rv.get_data(as_text=True))
api_spec = WorkflowSpecModelSchema().load(json_data, session=session)
self.assertEqual(db_spec_before, api_spec)
db_spec_after: WorkflowSpecModel = session.query(WorkflowSpecModel).filter_by(id=spec_id).first()
Created a "StudyService" and moved all complex logic around study manipulation out of the study api, and this service, as things were getting complicated. The Workflow Processor no longer creates the WorkflowModel, the study object handles that, and only passes the model into the workflow processor when it is ready to start the workflow. Created a Study object (seperate from the StudyModel) that can cronstructed on request, and contains a different data structure than we store in the DB. This allows us to return underlying Categories and Workflows in a clean way. Added a new status to workflows called "not_started", meaning we have not yet instantiated a processor or created a BPMN, they have no version yet and no stored data, just the possiblity of being started. The Top Level Workflow or "Master" workflow is now a part of the sample data, and loaded at all times. Removed the ability to "add a workflow to a study" and "remove a workflow from a study", a study contains all possible workflows by definition. Example data no longer creates users or studies, it just creates the specs.
2020-03-30 12:00:16 +00:00
self.assertIsNotNone(db_spec_after.category_id)
self.assertIsNotNone(db_spec_after.category)
self.assertEqual(db_spec_after.category.display_name, category.display_name)
self.assertEqual(db_spec_after.category.display_order, category.display_order)
Adds test for updating workflow spec
2020-03-16 16:32:39 +00:00
Protocol builder connections
2020-02-20 18:30:04 +00:00
def test_delete_workflow_specification(self):
self.load_example_data()
spec_id = 'random_fact'
Standardizing the script tasks that can be executed on the server, adding tons of error messages for when things go wrong. All scripts must exist in side of the crc/scripts directory. Adding a new script that script tasks can use to add in data about the study. Moving all the test workflow specifications out of the main load. fixing a pile of tests so they can find workflow specs that are now moved into the test directory.
2020-03-03 18:50:22 +00:00
self.load_test_spec(spec_id)
Protocol builder connections
2020-02-20 18:30:04 +00:00
num_specs_before = session.query(WorkflowSpecModel).filter_by(id=spec_id).count()
self.assertEqual(num_specs_before, 1)
num_files_before = session.query(FileModel).filter_by(workflow_spec_id=spec_id).count()
num_workflows_before = session.query(WorkflowModel).filter_by(workflow_spec_id=spec_id).count()
self.assertGreater(num_files_before + num_workflows_before, 0)
Requires login
2020-03-11 19:27:22 +00:00
rv = self.app.delete('/v1.0/workflow-specification/' + spec_id, headers=self.logged_in_headers())
Protocol builder connections
2020-02-20 18:30:04 +00:00
self.assert_success(rv)
num_specs_after = session.query(WorkflowSpecModel).filter_by(id=spec_id).count()
self.assertEqual(0, num_specs_after)
# Make sure that all items in the database with the workflow spec ID are deleted as well.
num_files_after = session.query(FileModel).filter_by(workflow_spec_id=spec_id).count()
num_workflows_after = session.query(WorkflowModel).filter_by(workflow_spec_id=spec_id).count()
self.assertEqual(num_files_after + num_workflows_after, 0)
Removed all self-referential calls in the study_api. One api endpoint should never call another api endpoint. Moved the logic for updating a study to the study Model, rather than checking and setting dictionary values which will become very hard to maintain. The protocol builder service now returns real models, not dictionaries, forcing proper validation and fail-fast behavior. Changed the name of the "status" spec, to "top_level_workflow" and removing any connection a workflow or study has with this specification. It is only unused to determine status in real time, and is not reused or tracked. Modified the required documents script to return a dictionary and not an array, making it easier to speak to specific values in the BPMN and DMN. Working on new ways to test the top_level_workflow in the context of updates, this is still a work in progress. Making use of several modifications to the Spiff library that enables more complex expressions in DMN models. This is evident in the new DMN models for the top_level_workflow
2020-03-26 16:51:53 +00:00
Added test for new api endpoint to get all standalone workflow_specs. Modified test_add_new_workflow_specification to include new standalone argument
2021-04-26 12:56:21 +00:00
def test_get_standalone_workflow_specs(self):
self.load_example_data()
category = session.query(WorkflowSpecCategoryModel).first()
ExampleDataLoader().create_spec('hello_world', 'Hello World', category_id=category.id,
standalone=True, from_tests=True)
rv = self.app.get('/v1.0/workflow-specification/standalone', headers=self.logged_in_headers())
self.assertEqual(1, len(rv.json))
ExampleDataLoader().create_spec('email_script', 'Email Script', category_id=category.id,
standalone=True, from_tests=True)
rv = self.app.get('/v1.0/workflow-specification/standalone', headers=self.logged_in_headers())
self.assertEqual(2, len(rv.json))