import string from datetime import datetime import random import jinja2 from SpiffWorkflow import Task as SpiffTask, WorkflowException from SpiffWorkflow.bpmn.specs.ManualTask import ManualTask from SpiffWorkflow.bpmn.specs.ScriptTask import ScriptTask from SpiffWorkflow.bpmn.specs.UserTask import UserTask from SpiffWorkflow.dmn.specs.BusinessRuleTask import BusinessRuleTask from SpiffWorkflow.specs import CancelTask, StartTask from flask import g from jinja2 import Template from crc import db, app from crc.api.common import ApiError from crc.models.api_models import Task, MultiInstanceType from crc.models.file import LookupDataModel from crc.models.stats import TaskEventModel from crc.models.study import StudyModel from crc.models.user import UserModel from crc.models.workflow import WorkflowModel, WorkflowStatus from crc.services.file_service import FileService from crc.services.lookup_service import LookupService from crc.services.study_service import StudyService from crc.services.workflow_processor import WorkflowProcessor, CustomBpmnScriptEngine class WorkflowService(object): TASK_ACTION_COMPLETE = "Complete" TASK_ACTION_TOKEN_RESET = "Backwards Move" TASK_ACTION_HARD_RESET = "Restart (Hard)" TASK_ACTION_SOFT_RESET = "Restart (Soft)" """Provides tools for processing workflows and tasks. This should at some point, be the only way to work with Workflows, and the workflow Processor should be hidden behind this service. This will help maintain a structure that avoids circular dependencies. But for now, this contains tools for converting spiff-workflow models into our own API models with additional information and capabilities and handles the testing of a workflow specification by completing it with random selections, attempting to mimic a front end as much as possible. """ @staticmethod def make_test_workflow(spec_id): user = db.session.query(UserModel).filter_by(uid="test").first() if not user: db.session.add(UserModel(uid="test")) study = db.session.query(StudyModel).filter_by(user_uid="test").first() if not study: db.session.add(StudyModel(user_uid="test", title="test")) db.session.commit() workflow_model = WorkflowModel(status=WorkflowStatus.not_started, workflow_spec_id=spec_id, last_updated=datetime.now(), study=study) return workflow_model @staticmethod def delete_test_data(): for study in db.session.query(StudyModel).filter(StudyModel.user_uid=="test"): StudyService.delete_study(study.id) db.session.commit() user = db.session.query(UserModel).filter_by(uid="test").first() if user: db.session.delete(user) @staticmethod def test_spec(spec_id, required_only=False): """Runs a spec through it's paces to see if it results in any errors. Not fool-proof, but a good sanity check. Returns the final data output form the last task if successful. required_only can be set to true, in which case this will run the spec, only completing the required fields, rather than everything. """ workflow_model = WorkflowService.make_test_workflow(spec_id) try: processor = WorkflowProcessor(workflow_model, validate_only=True) except WorkflowException as we: WorkflowService.delete_test_data() raise ApiError.from_workflow_exception("workflow_execution_exception", str(we), we) while not processor.bpmn_workflow.is_completed(): try: processor.bpmn_workflow.do_engine_steps() tasks = processor.bpmn_workflow.get_tasks(SpiffTask.READY) for task in tasks: task_api = WorkflowService.spiff_task_to_api_task( task, add_docs_and_forms=True) # Assure we try to process the documenation, and raise those errors. WorkflowService.populate_form_with_random_data(task, task_api, required_only) task.complete() except WorkflowException as we: WorkflowService.delete_test_data() raise ApiError.from_workflow_exception("workflow_execution_exception", str(we), we) WorkflowService.delete_test_data() return processor.bpmn_workflow.last_task.data @staticmethod def populate_form_with_random_data(task, task_api, required_only): """populates a task with random data - useful for testing a spec.""" if not hasattr(task.task_spec, 'form'): return form_data = {} for field in task_api.form.fields: if required_only and (not field.has_validation(Task.VALIDATION_REQUIRED) or field.get_validation(Task.VALIDATION_REQUIRED).lower().strip() != "true"): continue # Don't include any fields that aren't specifically marked as required. if field.has_property(Task.PROP_OPTIONS_REPEAT): group = field.get_property(Task.PROP_OPTIONS_REPEAT) if group not in form_data: form_data[group] = [{},{},{}] for i in range(3): form_data[group][i][field.id] = WorkflowService.get_random_data_for_field(field, task) else: form_data[field.id] = WorkflowService.get_random_data_for_field(field, task) if task.data is None: task.data = {} task.data.update(form_data) @staticmethod def get_random_data_for_field(field, task): if field.type == "enum": if len(field.options) > 0: random_choice = random.choice(field.options) if isinstance(random_choice, dict): return random.choice(field.options)['id'] else: # fixme: why it is sometimes an EnumFormFieldOption, and other times not? return random_choice.id ## Assume it is an EnumFormFieldOption else: raise ApiError.from_task("invalid_enum", "You specified an enumeration field (%s)," " with no options" % field.id, task) elif field.type == "autocomplete": lookup_model = LookupService.get_lookup_model(task, field) if field.has_property(Task.PROP_LDAP_LOOKUP): # All ldap records get the same person. return { "label": "dhf8r", "value": "Dan Funk", "data": { "uid": "dhf8r", "display_name": "Dan Funk", "given_name": "Dan", "email_address": "dhf8r@virginia.edu", "department": "Depertment of Psychocosmographictology", "affiliation": "Rousabout", "sponsor_type": "Staff"} } elif lookup_model: data = db.session.query(LookupDataModel).filter( LookupDataModel.lookup_file_model == lookup_model).limit(10).all() options = [] for d in data: options.append({"id": d.value, "name": d.label}) return random.choice(options) else: raise ApiError.from_task("invalid_autocomplete", "The settings for this auto complete field " "are incorrect: %s " % field.id, task) elif field.type == "long": return random.randint(1, 1000) elif field.type == 'boolean': return random.choice([True, False]) elif field.type == 'file': # fixme: produce some something sensible for files. return random.randint(1, 100) # fixme: produce some something sensible for files. elif field.type == 'files': return random.randrange(1, 100) else: return WorkflowService._random_string() def __get_options(self): pass @staticmethod def _random_string(string_length=10): """Generate a random string of fixed length """ letters = string.ascii_lowercase return ''.join(random.choice(letters) for i in range(string_length)) @staticmethod def spiff_task_to_api_task(spiff_task, add_docs_and_forms=False): task_type = spiff_task.task_spec.__class__.__name__ if isinstance(spiff_task.task_spec, UserTask): task_type = "UserTask" elif isinstance(spiff_task.task_spec, ManualTask): task_type = "ManualTask" elif isinstance(spiff_task.task_spec, BusinessRuleTask): task_type = "BusinessRuleTask" elif isinstance(spiff_task.task_spec, CancelTask): task_type = "CancelTask" elif isinstance(spiff_task.task_spec, ScriptTask): task_type = "ScriptTask" elif isinstance(spiff_task.task_spec, StartTask): task_type = "StartTask" else: task_type = "NoneTask" info = spiff_task.task_info() if info["is_looping"]: mi_type = MultiInstanceType.looping elif info["is_sequential_mi"]: mi_type = MultiInstanceType.sequential elif info["is_parallel_mi"]: mi_type = MultiInstanceType.parallel else: mi_type = MultiInstanceType.none props = {} if hasattr(spiff_task.task_spec, 'extensions'): for id, val in spiff_task.task_spec.extensions.items(): props[id] = val task = Task(spiff_task.id, spiff_task.task_spec.name, spiff_task.task_spec.description, task_type, spiff_task.get_state_name(), None, "", {}, mi_type, info["mi_count"], info["mi_index"], process_name=spiff_task.task_spec._wf_spec.description, properties=props ) # Only process the form and documentation if requested. # The task should be in a completed or a ready state, and should # not be a previously completed MI Task. if add_docs_and_forms: task.data = spiff_task.data if hasattr(spiff_task.task_spec, "form"): task.form = spiff_task.task_spec.form for field in task.form.fields: WorkflowService.process_options(spiff_task, field) task.documentation = WorkflowService._process_documentation(spiff_task) # All ready tasks should have a valid name, and this can be computed for # some tasks, particularly multi-instance tasks that all have the same spec # but need different labels. if spiff_task.state == SpiffTask.READY: task.properties = WorkflowService._process_properties(spiff_task, props) # Replace the title with the display name if it is set in the task properties, # otherwise strip off the first word of the task, as that should be following # a BPMN standard, and should not be included in the display. if task.properties and "display_name" in task.properties: task.title = task.properties['display_name'] elif task.title and ' ' in task.title: task.title = task.title.partition(' ')[2] return task @staticmethod def _process_properties(spiff_task, props): """Runs all the property values through the Jinja2 processor to inject data.""" for k, v in props.items(): try: template = Template(v) props[k] = template.render(**spiff_task.data) except jinja2.exceptions.TemplateError as ue: app.logger.error("Failed to process task property %s " % str(ue)) return props @staticmethod def _process_documentation(spiff_task): """Runs the given documentation string through the Jinja2 processor to inject data create loops, etc... - If a markdown file exists with the same name as the task id, it will use that file instead of the documentation. """ documentation = spiff_task.task_spec.documentation if hasattr(spiff_task.task_spec, "documentation") else "" try: doc_file_name = spiff_task.task_spec.name + ".md" data_model = FileService.get_workflow_file_data(spiff_task.workflow, doc_file_name) raw_doc = data_model.data.decode("utf-8") except ApiError: raw_doc = documentation if not raw_doc: return "" try: template = Template(raw_doc) return template.render(**spiff_task.data) except jinja2.exceptions.TemplateError as ue: raise ApiError(code="template_error", message="Error processing template for task %s: %s" % (spiff_task.task_spec.name, str(ue)), status_code=500) except TypeError as te: raise ApiError(code="template_error", message="Error processing template for task %s: %s" % (spiff_task.task_spec.name, str(te)), status_code=500) # TODO: Catch additional errors and report back. @staticmethod def process_options(spiff_task, field): # If this is an auto-complete field, do not populate options, a lookup will happen later. if field.type == Task.FIELD_TYPE_AUTO_COMPLETE: pass elif field.has_property(Task.PROP_OPTIONS_FILE): lookup_model = LookupService.get_lookup_model(spiff_task, field) data = db.session.query(LookupDataModel).filter(LookupDataModel.lookup_file_model == lookup_model).all() if not hasattr(field, 'options'): field.options = [] for d in data: field.options.append({"id": d.value, "name": d.label}) @staticmethod def log_task_action(processor, spiff_task, action): task = WorkflowService.spiff_task_to_api_task(spiff_task) workflow_model = processor.workflow_model task_event = TaskEventModel( study_id=workflow_model.study_id, user_uid=g.user.uid, workflow_id=workflow_model.id, workflow_spec_id=workflow_model.workflow_spec_id, spec_version=processor.get_version_string(), action=action, task_id=task.id, task_name=task.name, task_title=task.title, task_type=str(task.type), task_state=task.state, mi_type=task.multi_instance_type.value, # Some tasks have a repeat behavior. mi_count=task.multi_instance_count, # This is the number of times the task could repeat. mi_index=task.multi_instance_index, # And the index of the currently repeating task. process_name=task.process_name, date=datetime.now(), ) db.session.add(task_event) db.session.commit()