1. Avoid ever re-generating the list of scripts that can be used in a script task. Terribly expensive as we call eval constantly, and it never ever changes once the app starts. (see script.py changes, and comments)
2. Cache the DocumentStatus list in the flask session, so we calculate it at most once per API Call. It's at least .25 seconds per call. (see study_sevice)
3. We called UserFileService.get_files_for_study (which runs a db query EVERY time) for every possible document type. Now we run the query once (study service line 321)
4. When returning a workflow, we looped through every single task in that workflow's navigation, and called the expensive spiff_task_to_api_task just to figure out it's proper display name. We run a much faster and more efficient method to calculate the display name naow (see workflow_service on lie 680, and 799)
5. A hellton of @timeit and sincetime() calls, that I want to leave in, to help debug any slowness on production.
Adding a DocumentService to clean up the FileService, and get Documents well seperated, as it seems likely be pulled out or seperated in the future, there is now a Documents api file as well, for the same reason.
Some other minor changes are just fixing white space to assure our code is linting correctly.
I removed _create_study_workflow_approvals from the base test, as we don't use approvals like this anymore.
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.
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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.
