2. Disabling the token timeout for now, to see if this corrects the issues Alex is having with lost work.
3. Raising more thoughtful error messages for unknown lookup options.
4. Providing better validation of default values and injecting the correct value for defaults related to enum lists of all types.
5. Bumping Spiffworkflow library which contains some better error messages and checks.
Still having issues where we try to eval an empty definition, not quite sure why there is a difference from what we had before. I may need to revert some of it and determine what is going on.
This is the first waypoint on a larger effort to make all of the 'special scripts' that currently require a shebang to be just another python function.
* The Task.title returned to the front end will now attempt to process the "display_name" property for dot-notation syntax, making it possible to use this for multi-instance tasks,
but will work in all cases where we want he title to change based on values in the data model.
* Fixing a bug the test_study_api where it wasn't updated when we made recent changes to the different states of a study.
*
Improving the study_info script documentation to provide detailed examples of values returned based on arguments.
Making the tests a little more targetted and less subject to breaking through better mocks.
Allow all tests to pass even when ther protocol builder mock isn't running locally.
Removing the duplication of reference files in tests and static, as this seems silly to me at the moment.
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.
Required Documents is becoming complicated, so making this it's own script task, removing it from study_info.py
The file_service is now very aware of this irb_documents file, so it will always need to exist. We seed this file
during setup, but it can be overwritten by the configurator.
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.
Kelly McDonald
Dan Funk
Aaron Louie