Criteria :
task.multi_instance_type == 'looping'
to terminate, use the standard endpoint for submitting form data with a query variable of terminate_loop=true
Will likely need two buttons:
"Submit and quit"
"Submit and add another"
or something similar
Also, when returning error messages, attempt to include the task data for the task that caused the error.
Also, when attempting to delete any file, respond with an API error explaining the issue, and log the details.
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.
From an API point of view you can do the following (and only the following)
/files?workflow_spec_id=x
* You can find all files associated with a workflow_spec_id, and add a file with a workflow_spec_id
/files?workflow_id=x
* You can find all files associated with a workflow_id, and add a file that is directly associated with the workflow
/files?workflow_id=x&form_field_key=y
* You can find all files associated with a form element on a running workflow, and add a new file.
Note: you can add multiple files to the same form_field_key, IF they have different file names. If the same name, the original file is archived,
and the new file takes its place.
The study endpoints always return a list of the file metadata associated with the study. Removed /studies-files, but there is an
endpoint called
/studies/all - that returns all the studies in the system, and does include their files.
On a deeper level:
The File model no longer contains:
- study_id,
- task_id,
- form_field_key
Instead, if the file is associated with workflow - then that is the one way it is connected to the study, and we use this relationship to find files for a study.
A file is never associated with a task_id, as these change when the workflow is reloaded.
The form_field_key must match the irb_doc_code, so when requesting files for a form field, we just look up the irb_doc_code.
Refactored calls into a new lookup_service to keep things tidy.
New keys for all enum/auto-complete fields:
PROP_OPTIONS_FILE = "spreadsheet.name"
PROP_OPTIONS_VALUE_COLUMN = "spreadsheet.value.column"
PROP_OPTIONS_LABEL_COL = "spreadsheet.label.column"
PROP_LDAP_LOOKUP = "ldap.lookup"
FIELD_TYPE_AUTO_COMPLETE = "autocomplete"
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.
running all extension/properties through the Jinja template processor so you can have custom display names using data, very helpful for building multi-instance displays.
Properties was returned as an array of key/value pairs, which is just mean. Switched this to a dictionary.
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.
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.
INCOMPLETE = 'Incomplete in Protocol Builder',
ACTIVE = 'Active / Ready to roll',
HOLD = 'On Hold',
OPEN = 'Open - this study is in progress',
ABANDONED = 'Abandoned, it got deleted in Protocol Builder'
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.
some ugly fixes in the file_service for improving panda output from spreadsheet processing that I need to revist.
now that the spiff-workflow handles multi-instance, we can't have random multi-instance tasks around.
Improved tests around study deletion.
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.
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
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.
Split the API specific models out from the workflow models to help me keep this straight.
Added tests to help me understand the errors thrown the and resolution path when a workflow specification changes in the midst of a running workflow.
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
Carlos Lopez
Dan Funk
Aaron Louie