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.
I've also made it so that it falls back if we accidentally forget to add a shebang to a study as this would be a breaking change.
With the fallback feature, it should work with unmodified bpmn documents.
* TaskEvents now contain the data for each event as it was when the task was completed.
* When loading a task for the front end, if the task was completed previously, we take that data, and overwrite it with the lastest data, allowing users to see previously entered values.
* Pulling in the Admin branch, as there are changes in that branch that are critical to seeing what is happening when we do this thing.
* Moved code for converting a workflow to an API ready data stricture into the Workflow service where it belongs, and out of the API.
* Hard resets just convert to using the latest spec, they don't try to keep the data from the last task. There is a better way.
* Moving to a previous task does not attept to keep the data from the last completed task.
* Added a function that will fix all the existing RRT data by adding critical data into the TaskEvent model. This can be called with from the flask command line tool.
I noticed the validation sometimes looks ahead for files, so looking at all the tasks now, not just the ready tasks for the lookup field.
Ran into an issue with validation where a workflow model was required, so I create one and delete it. Another refactor for another day.
Another speed improvement - data in the FileDataModel is deferred, and not queried until it is specifically used, as the new data structures need to use this model frequently.
Added a File class, that we wrap around the FileModel so the api endpoints don't change, but File no longer holds refences to versions or dates of the file_data model, we
figure this out based on a clean database structure.
The ApprovalFile is directly related to the file_data_model - so no chance that a reviewer would review the incorrect version of a file.py
Noticed that our FileType enum called "bpmn" "bpmm", hope this doesn't screw someone up.
Workflows are directly related to the data_models that create the workflow spec it needs. So the files should always be there. There are no more hashes, and thus no more hash errors where it can't find the files to rebuild the workflow.py
Not much to report here, other than I broke every single test in the system at one point. So I'm super concerned about this, and will be testing it a lot before creating the pull request.
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.
No Previous Task, No Last Task, No Task List. Just the current task, and the Navigation.
Use the token endpoint to set the current task, even if it is a "READY" task in the api.
Previous Task can be set by identifying the prior task in the Navigation (I'm hoping)
Prefering camel case to snake case on all new apis. Maybe clean the rest up later.
I noticed we were saving the workflow every time we loaded it up, rather than only when we were making changes to it. Refactored this to be a little more careful.
Centralized the saving of the workflow into one location in the processor, so we can make sure we update all the details about that workflow every time we save.
The workflow service has a method that will log any task action taken in a consistent way.
The stats models were removed from the API completely. Will wait for a use case for dealing with this later.
Because the name field is now used to expose workflow/sub-process information on tasks, we can't use it to store the workflow_version, so that is now just stored on the database model. Which is much cleaner and removes a duplication.
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.
Found a problem where the documentation for elements was being processed BEFORE data was loaded from a script. There still may be some issues here.
Ran into an issue with circular dependencies - handling it with a new workflow_service, and pulling computational logic out of the api_models - it was the right thing to do.
Adding id and spec_version to the workflow metadata.
Refactoring the processing of the master_spec so that it doesn't polute the workflow database.
Adding tests to assure that the status and counts are updated on the workflow model as users make progress.
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.
Aaron Louie
Dan Funk
Kelly McDonald
Carlos Lopez