We now cache the LDAP records - so we look in our own database for the record before calling out to ldap for the details when given a straight up computing id like dhf8r.
Added "date_approved" to the approval model.
And moved the approver and primary investigator into real associated models to make it easier to dump.
Fixed a problem with the validation that was causing it to throw incorrect errors on valid workflows. Getting it to behave a little more like the front end behaves, and respecting the read-only fields. But it was mainly to do with always returning all the data with each form submission.
Fixing a bug where the validation of forms did not correctly process auto-complete fields.
Fixing a bug where the approvals script and the update study script could not process dot notation correctly.
Moved populate_random_data into the WorkflowService where it makes more sense.
Using the LDAP service for checking user details in development mode - even if you are using the back door.
Added a new Flask fucntion load-example-rrt-data that loads the rrt workflow, and not the CRC wrokflows.
Modified the "load-example-data" in the tests to use some test data, rather than loading up all the workflows[
in CRC each time, with a parameter to load crc data if that is required - which is enabled for just a handful of tests.
(Tests run in 1/4 the time now)
Because this changes the endpoint for all existing document details, I've modified all the test and static bpmn files to use the new format.
Shorting up the SponsorsList.xls file makes for slightly faster tests. seems senseless to load 5000 everytime we reset the data.
Tried to test all of this carefully in the test_study_details_documents.py test.
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.
Added a validate_workflow_specification endpoint that allows you to check if the workflow will execute from beginning to end using random data.
Minor fixes to existing bpmns to allow them to pass.
All scripts must include a "do_task_validate_only" that restricts external calls and database modifications, but performs as much logic as possible.
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.
Dan Funk
Aaron Louie