264 lines
12 KiB
Python
264 lines
12 KiB
Python
import string
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from datetime import datetime
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import random
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import jinja2
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from SpiffWorkflow import Task as SpiffTask, WorkflowException
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from SpiffWorkflow.bpmn.specs.ManualTask import ManualTask
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from SpiffWorkflow.bpmn.specs.ScriptTask import ScriptTask
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from SpiffWorkflow.bpmn.specs.UserTask import UserTask
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from SpiffWorkflow.bpmn.workflow import BpmnWorkflow
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from SpiffWorkflow.dmn.specs.BusinessRuleTask import BusinessRuleTask
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from SpiffWorkflow.specs import CancelTask, StartTask
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from flask import g
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from jinja2 import Template
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from crc import db, app
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from crc.api.common import ApiError
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from crc.models.api_models import Task, MultiInstanceType
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from crc.models.file import LookupDataModel
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from crc.models.stats import TaskEventModel
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from crc.services.file_service import FileService
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from crc.services.lookup_service import LookupService
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from crc.services.workflow_processor import WorkflowProcessor, CustomBpmnScriptEngine
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class WorkflowService(object):
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TASK_ACTION_COMPLETE = "Complete"
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TASK_ACTION_TOKEN_RESET = "Backwards Move"
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TASK_ACTION_HARD_RESET = "Restart (Hard)"
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TASK_ACTION_SOFT_RESET = "Restart (Soft)"
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"""Provides tools for processing workflows and tasks. This
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should at some point, be the only way to work with Workflows, and
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the workflow Processor should be hidden behind this service.
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This will help maintain a structure that avoids circular dependencies.
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But for now, this contains tools for converting spiff-workflow models into our
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own API models with additional information and capabilities."""
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@classmethod
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def test_spec(cls, spec_id):
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"""Runs a spec through it's paces to see if it results in any errors. Not fool-proof, but a good
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sanity check."""
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version = WorkflowProcessor.get_latest_version_string(spec_id)
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spec = WorkflowProcessor.get_spec(spec_id, version)
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bpmn_workflow = BpmnWorkflow(spec, script_engine=CustomBpmnScriptEngine())
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bpmn_workflow.data[WorkflowProcessor.STUDY_ID_KEY] = 1
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bpmn_workflow.data[WorkflowProcessor.WORKFLOW_ID_KEY] = spec_id
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bpmn_workflow.data[WorkflowProcessor.VALIDATION_PROCESS_KEY] = True
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while not bpmn_workflow.is_completed():
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try:
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bpmn_workflow.do_engine_steps()
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tasks = bpmn_workflow.get_tasks(SpiffTask.READY)
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for task in tasks:
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task_api = WorkflowService.spiff_task_to_api_task(
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task,
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add_docs_and_forms=True) # Assure we try to process the documenation, and raise those errors.
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WorkflowService.populate_form_with_random_data(task, task_api)
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task.complete()
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except WorkflowException as we:
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raise ApiError.from_task_spec("workflow_execution_exception", str(we),
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we.sender)
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@staticmethod
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def populate_form_with_random_data(task, task_api):
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"""populates a task with random data - useful for testing a spec."""
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if not hasattr(task.task_spec, 'form'): return
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form_data = {}
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for field in task_api.form.fields:
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if field.type == "enum":
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if len(field.options) > 0:
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form_data[field.id] = random.choice(field.options)
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else:
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raise ApiError.from_task("invalid_enum", "You specified an enumeration field (%s),"
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" with no options" % field.id,
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task)
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if field.type == "autocomplete":
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lookup_model = LookupService.get_lookup_table(task, field)
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if not lookup_model:
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raise ApiError.from_task("invalid_autocomplete", "The settings for this auto complete field "
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"(%s) are incorrect: " % field.id)
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data = db.session.query(LookupDataModel).filter(LookupDataModel.lookup_file_model == lookup_model).limit(10).all()
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options = []
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for d in data:
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options.append({"id": d.value, "name": d.label})
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form_data[field.id] = random.choice(options)
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elif field.type == "long":
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form_data[field.id] = random.randint(1, 1000)
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elif field.type == 'boolean':
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form_data[field.id] = random.choice([True, False])
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elif field.type == 'file':
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form_data[field.id] = random.randint(1, 100)
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elif field.type == 'files':
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form_data[field.id] = random.randrange(1, 100)
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else:
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form_data[field.id] = WorkflowService._random_string()
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if task.data is None:
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task.data = {}
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task.data.update(form_data)
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@staticmethod
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def _random_string(string_length=10):
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"""Generate a random string of fixed length """
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letters = string.ascii_lowercase
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return ''.join(random.choice(letters) for i in range(string_length))
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@staticmethod
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def spiff_task_to_api_task(spiff_task, add_docs_and_forms=False):
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task_type = spiff_task.task_spec.__class__.__name__
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if isinstance(spiff_task.task_spec, UserTask):
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task_type = "UserTask"
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elif isinstance(spiff_task.task_spec, ManualTask):
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task_type = "ManualTask"
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elif isinstance(spiff_task.task_spec, BusinessRuleTask):
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task_type = "BusinessRuleTask"
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elif isinstance(spiff_task.task_spec, CancelTask):
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task_type = "CancelTask"
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elif isinstance(spiff_task.task_spec, ScriptTask):
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task_type = "ScriptTask"
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elif isinstance(spiff_task.task_spec, StartTask):
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task_type = "StartTask"
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else:
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task_type = "NoneTask"
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info = spiff_task.task_info()
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if info["is_looping"]:
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mi_type = MultiInstanceType.looping
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elif info["is_sequential_mi"]:
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mi_type = MultiInstanceType.sequential
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elif info["is_parallel_mi"]:
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mi_type = MultiInstanceType.parallel
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else:
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mi_type = MultiInstanceType.none
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props = {}
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if hasattr(spiff_task.task_spec, 'extensions'):
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for id, val in spiff_task.task_spec.extensions.items():
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props[id] = val
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task = Task(spiff_task.id,
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spiff_task.task_spec.name,
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spiff_task.task_spec.description,
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task_type,
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spiff_task.get_state_name(),
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None,
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"",
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{},
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mi_type,
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info["mi_count"],
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info["mi_index"],
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process_name=spiff_task.task_spec._wf_spec.description,
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properties=props
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)
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# Only process the form and documentation if requested.
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# The task should be in a completed or a ready state, and should
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# not be a previously completed MI Task.
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if add_docs_and_forms:
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task.data = spiff_task.data
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if hasattr(spiff_task.task_spec, "form"):
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task.form = spiff_task.task_spec.form
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for field in task.form.fields:
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WorkflowService.process_options(spiff_task, field)
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task.documentation = WorkflowService._process_documentation(spiff_task)
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# All ready tasks should have a valid name, and this can be computed for
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# some tasks, particularly multi-instance tasks that all have the same spec
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# but need different labels.
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if spiff_task.state == SpiffTask.READY:
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task.properties = WorkflowService._process_properties(spiff_task, props)
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# Replace the title with the display name if it is set in the task properties,
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# otherwise strip off the first word of the task, as that should be following
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# a BPMN standard, and should not be included in the display.
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if task.properties and "display_name" in task.properties:
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task.title = task.properties['display_name']
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elif task.title and ' ' in task.title:
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task.title = task.title.partition(' ')[2]
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return task
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@staticmethod
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def _process_properties(spiff_task, props):
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"""Runs all the property values through the Jinja2 processor to inject data."""
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for k, v in props.items():
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try:
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template = Template(v)
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props[k] = template.render(**spiff_task.data)
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except jinja2.exceptions.TemplateError as ue:
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app.logger.error("Failed to process task property %s " % str(ue))
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return props
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@staticmethod
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def _process_documentation(spiff_task):
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"""Runs the given documentation string through the Jinja2 processor to inject data
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create loops, etc... - If a markdown file exists with the same name as the task id,
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it will use that file instead of the documentation. """
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documentation = spiff_task.task_spec.documentation if hasattr(spiff_task.task_spec, "documentation") else ""
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try:
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doc_file_name = spiff_task.task_spec.name + ".md"
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data_model = FileService.get_workflow_file_data(spiff_task.workflow, doc_file_name)
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raw_doc = data_model.data.decode("utf-8")
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except ApiError:
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raw_doc = documentation
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if not raw_doc:
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return ""
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try:
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template = Template(raw_doc)
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return template.render(**spiff_task.data)
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except jinja2.exceptions.TemplateError as ue:
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# return "Error processing template. %s" % ue.message
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raise ApiError(code="template_error", message="Error processing template for task %s: %s" %
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(spiff_task.task_spec.name, str(ue)), status_code=500)
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# TODO: Catch additional errors and report back.
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@staticmethod
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def process_options(spiff_task, field):
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lookup_model = LookupService.get_lookup_table(spiff_task, field)
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# If this is an auto-complete field, do not populate options, a lookup will happen later.
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if field.type == Task.FIELD_TYPE_AUTO_COMPLETE:
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pass
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else:
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data = db.session.query(LookupDataModel).filter(LookupDataModel.lookup_file_model == lookup_model).all()
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if not hasattr(field, 'options'):
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field.options = []
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for d in data:
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field.options.append({"id": d.value, "name": d.label})
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@staticmethod
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def log_task_action(processor, spiff_task, action):
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task = WorkflowService.spiff_task_to_api_task(spiff_task)
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workflow_model = processor.workflow_model
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task_event = TaskEventModel(
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study_id=workflow_model.study_id,
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user_uid=g.user.uid,
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workflow_id=workflow_model.id,
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workflow_spec_id=workflow_model.workflow_spec_id,
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spec_version=workflow_model.spec_version,
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action=action,
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task_id=task.id,
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task_name=task.name,
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task_title=task.title,
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task_type=str(task.type),
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task_state=task.state,
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mi_type=task.multi_instance_type.value, # Some tasks have a repeat behavior.
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mi_count=task.multi_instance_count, # This is the number of times the task could repeat.
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mi_index=task.multi_instance_index, # And the index of the currently repeating task.
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process_name=task.process_name,
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date=datetime.now(),
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)
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db.session.add(task_event)
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db.session.commit()
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