486 lines
22 KiB
Python
486 lines
22 KiB
Python
import re
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from SpiffWorkflow.serializer.exceptions import MissingSpecError
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from lxml import etree
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import shlex
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from datetime import datetime
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from typing import List
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from SpiffWorkflow import Task as SpiffTask, WorkflowException
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from SpiffWorkflow.bpmn.BpmnScriptEngine import BpmnScriptEngine
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from SpiffWorkflow.bpmn.parser.ValidationException import ValidationException
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from SpiffWorkflow.bpmn.serializer.BpmnSerializer import BpmnSerializer
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from SpiffWorkflow.bpmn.specs.EndEvent import EndEvent
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from SpiffWorkflow.bpmn.workflow import BpmnWorkflow
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from SpiffWorkflow.camunda.parser.CamundaParser import CamundaParser
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from SpiffWorkflow.dmn.parser.BpmnDmnParser import BpmnDmnParser
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from SpiffWorkflow.exceptions import WorkflowTaskExecException
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from SpiffWorkflow.specs import WorkflowSpec
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import crc
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from crc import session, app
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from crc.api.common import ApiError
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from crc.models.file import FileDataModel, FileModel, FileType
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from crc.models.task_event import TaskEventModel
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from crc.models.user import UserModelSchema
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from crc.models.workflow import WorkflowStatus, WorkflowModel, WorkflowSpecDependencyFile
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from crc.scripts.script import Script
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from crc.services.file_service import FileService
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from crc import app
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from crc.services.user_service import UserService
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class CustomBpmnScriptEngine(BpmnScriptEngine):
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"""This is a custom script processor that can be easily injected into Spiff Workflow.
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It will execute python code read in from the bpmn. It will also make any scripts in the
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scripts directory available for execution. """
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def evaluate(self, task, expression):
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"""
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Evaluate the given expression, within the context of the given task and
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return the result.
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"""
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return self.evaluate_expression(task, expression)
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def execute(self, task: SpiffTask, script, data):
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study_id = task.workflow.data[WorkflowProcessor.STUDY_ID_KEY]
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if WorkflowProcessor.WORKFLOW_ID_KEY in task.workflow.data:
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workflow_id = task.workflow.data[WorkflowProcessor.WORKFLOW_ID_KEY]
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else:
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workflow_id = None
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try:
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if task.workflow.data[WorkflowProcessor.VALIDATION_PROCESS_KEY]:
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augmentMethods = Script.generate_augmented_validate_list(task, study_id, workflow_id)
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else:
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augmentMethods = Script.generate_augmented_list(task, study_id, workflow_id)
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super().execute(task, script, data, externalMethods=augmentMethods)
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except SyntaxError as e:
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raise ApiError('syntax_error',
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f'Something is wrong with your python script '
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f'please correct the following:'
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f' {script}, {e.msg}')
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except NameError as e:
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raise ApiError('name_error',
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f'something you are referencing does not exist:'
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f' {script}, {e}')
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# else:
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# self.run_predefined_script(task, script[2:], data) # strip off the first two characters.
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# def run_predefined_script(self, task: SpiffTask, script, data):
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# commands = shlex.split(script)
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# path_and_command = commands[0].rsplit(".", 1)
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# if len(path_and_command) == 1:
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# module_name = "crc.scripts." + self.camel_to_snake(path_and_command[0])
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# class_name = path_and_command[0]
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# else:
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# module_name = "crc.scripts." + path_and_command[0] + "." + self.camel_to_snake(path_and_command[1])
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# class_name = path_and_command[1]
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# try:
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# mod = __import__(module_name, fromlist=[class_name])
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# klass = getattr(mod, class_name)
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# study_id = task.workflow.data[WorkflowProcessor.STUDY_ID_KEY]
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# if WorkflowProcessor.WORKFLOW_ID_KEY in task.workflow.data:
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# workflow_id = task.workflow.data[WorkflowProcessor.WORKFLOW_ID_KEY]
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# else:
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# workflow_id = None
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#
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# if not isinstance(klass(), Script):
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# raise ApiError.from_task("invalid_script",
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# "This is an internal error. The script '%s:%s' you called " %
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# (module_name, class_name) +
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# "does not properly implement the CRC Script class.",
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# task=task)
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# if task.workflow.data[WorkflowProcessor.VALIDATION_PROCESS_KEY]:
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# """If this is running a validation, and not a normal process, then we want to
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# mimic running the script, but not make any external calls or database changes."""
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# klass().do_task_validate_only(task, study_id, workflow_id, *commands[1:])
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# else:
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# klass().do_task(task, study_id, workflow_id, *commands[1:])
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# except ModuleNotFoundError:
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# raise ApiError.from_task("invalid_script",
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# "Unable to locate Script: '%s:%s'" % (module_name, class_name),
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# task=task)
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def evaluate_expression(self, task, expression):
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"""
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Evaluate the given expression, within the context of the given task and
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return the result.
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"""
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study_id = task.workflow.data[WorkflowProcessor.STUDY_ID_KEY]
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if WorkflowProcessor.WORKFLOW_ID_KEY in task.workflow.data:
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workflow_id = task.workflow.data[WorkflowProcessor.WORKFLOW_ID_KEY]
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else:
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workflow_id = None
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try:
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if task.workflow.data[WorkflowProcessor.VALIDATION_PROCESS_KEY]:
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augmentMethods = Script.generate_augmented_validate_list(task, study_id, workflow_id)
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else:
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augmentMethods = Script.generate_augmented_list(task, study_id, workflow_id)
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exp, valid = self.validateExpression(expression)
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return self._eval(exp, externalMethods=augmentMethods, **task.data)
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except Exception as e:
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raise WorkflowTaskExecException(task,
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"Error evaluating expression "
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"'%s', %s" % (expression, str(e)))
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@staticmethod
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def camel_to_snake(camel):
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camel = camel.strip()
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return re.sub(r'(?<!^)(?=[A-Z])', '_', camel).lower()
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class MyCustomParser(BpmnDmnParser):
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"""
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A BPMN and DMN parser that can also parse Camunda forms.
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"""
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OVERRIDE_PARSER_CLASSES = BpmnDmnParser.OVERRIDE_PARSER_CLASSES
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OVERRIDE_PARSER_CLASSES.update(CamundaParser.OVERRIDE_PARSER_CLASSES)
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class WorkflowProcessor(object):
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_script_engine = CustomBpmnScriptEngine()
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_serializer = BpmnSerializer()
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WORKFLOW_ID_KEY = "workflow_id"
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STUDY_ID_KEY = "study_id"
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VALIDATION_PROCESS_KEY = "validate_only"
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def __init__(self, workflow_model: WorkflowModel, validate_only=False):
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"""Create a Workflow Processor based on the serialized information available in the workflow model."""
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self.workflow_model = workflow_model
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if workflow_model.bpmn_workflow_json is None: # The workflow was never started.
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self.spec_data_files = FileService.get_spec_data_files(
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workflow_spec_id=workflow_model.workflow_spec_id)
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spec = self.get_spec(self.spec_data_files, workflow_model.workflow_spec_id)
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else:
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self.spec_data_files = FileService.get_spec_data_files(
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workflow_spec_id=workflow_model.workflow_spec_id,
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workflow_id=workflow_model.id)
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spec = None
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self.workflow_spec_id = workflow_model.workflow_spec_id
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try:
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self.bpmn_workflow = self.__get_bpmn_workflow(workflow_model, spec, validate_only)
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self.bpmn_workflow.script_engine = self._script_engine
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if UserService.has_user():
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current_user = UserService.current_user(allow_admin_impersonate=True)
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current_user_data = UserModelSchema().dump(current_user)
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tasks = self.bpmn_workflow.get_tasks(SpiffTask.READY)
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for task in tasks:
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task.data['current_user'] = current_user_data
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if self.WORKFLOW_ID_KEY not in self.bpmn_workflow.data:
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if not workflow_model.id:
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session.add(workflow_model)
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session.commit()
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# If the model is new, and has no id, save it, write it into the workflow model
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# and save it again. In this way, the workflow process is always aware of the
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# database model to which it is associated, and scripts running within the model
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# can then load data as needed.
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self.bpmn_workflow.data[WorkflowProcessor.WORKFLOW_ID_KEY] = workflow_model.id
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workflow_model.bpmn_workflow_json = WorkflowProcessor._serializer.serialize_workflow(
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self.bpmn_workflow, include_spec=True)
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self.save()
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except MissingSpecError as ke:
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raise ApiError(code="unexpected_workflow_structure",
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message="Failed to deserialize workflow"
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" '%s' version %s, due to a mis-placed or missing task '%s'" %
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(self.workflow_spec_id, self.get_version_string(), str(ke)))
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# set whether this is the latest spec file.
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if self.spec_data_files == FileService.get_spec_data_files(workflow_spec_id=workflow_model.workflow_spec_id):
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self.is_latest_spec = True
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else:
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self.is_latest_spec = False
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def reset(self, workflow_model, clear_data=False):
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print('WorkflowProcessor: reset: ')
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self.cancel_notify()
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workflow_model.bpmn_workflow_json = None
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if clear_data:
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# Clear form_data from task_events
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task_events = session.query(TaskEventModel). \
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filter(TaskEventModel.workflow_id == workflow_model.id).all()
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for task_event in task_events:
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task_event.form_data = {}
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session.add(task_event)
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session.commit()
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return self.__init__(workflow_model)
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def __get_bpmn_workflow(self, workflow_model: WorkflowModel, spec: WorkflowSpec, validate_only=False):
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if workflow_model.bpmn_workflow_json:
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bpmn_workflow = self._serializer.deserialize_workflow(workflow_model.bpmn_workflow_json,
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workflow_spec=spec)
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else:
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bpmn_workflow = BpmnWorkflow(spec, script_engine=self._script_engine)
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bpmn_workflow.data[WorkflowProcessor.STUDY_ID_KEY] = workflow_model.study_id
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bpmn_workflow.data[WorkflowProcessor.VALIDATION_PROCESS_KEY] = validate_only
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# try:
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# bpmn_workflow.do_engine_steps()
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# except WorkflowException as we:
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# raise ApiError.from_task_spec("error_loading_workflow", str(we), we.sender)
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return bpmn_workflow
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def save(self):
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"""Saves the current state of this processor to the database """
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self.workflow_model.bpmn_workflow_json = self.serialize()
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complete_states = [SpiffTask.CANCELLED, SpiffTask.COMPLETED]
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tasks = list(self.get_all_user_tasks())
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self.workflow_model.status = self.get_status()
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self.workflow_model.total_tasks = len(tasks)
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self.workflow_model.completed_tasks = sum(1 for t in tasks if t.state in complete_states)
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self.workflow_model.last_updated = datetime.now()
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self.update_dependencies(self.spec_data_files)
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session.add(self.workflow_model)
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session.commit()
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def get_version_string(self):
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# this could potentially become expensive to load all the data in the data models.
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# in which case we might consider using a deferred loader for the actual data, but
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# trying not to pre-optimize.
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file_data_models = FileService.get_spec_data_files(self.workflow_model.workflow_spec_id,
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self.workflow_model.id)
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return WorkflowProcessor.__get_version_string_for_data_models(file_data_models)
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@staticmethod
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def get_latest_version_string_for_spec(spec_id):
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file_data_models = FileService.get_spec_data_files(spec_id)
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return WorkflowProcessor.__get_version_string_for_data_models(file_data_models)
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@staticmethod
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def __get_version_string_for_data_models(file_data_models):
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"""Version is in the format v[VERSION] (FILE_ID_LIST)
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For example, a single bpmn file with only one version would be
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v1 (12) Where 12 is the id of the file data model that is used to create the
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specification. If multiple files exist, they are added on in
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dot notation to both the version number and the file list. So
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a Spec that includes a BPMN, DMN, an a Word file all on the first
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version would be v1.1.1 (12.45.21)"""
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major_version = 0 # The version of the primary file.
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minor_version = [] # The versions of the minor files if any.
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file_ids = []
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for file_data in file_data_models:
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file_ids.append(file_data.id)
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if file_data.file_model.primary:
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major_version = file_data.version
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else:
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minor_version.append(file_data.version)
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minor_version.insert(0, major_version) # Add major version to beginning.
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version = ".".join(str(x) for x in minor_version)
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files = ".".join(str(x) for x in file_ids)
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full_version = "v%s (%s)" % (version, files)
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return full_version
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def update_dependencies(self, spec_data_files):
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existing_dependencies = FileService.get_spec_data_files(
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workflow_spec_id=self.workflow_model.workflow_spec_id,
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workflow_id=self.workflow_model.id)
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# Don't save the dependencies if they haven't changed.
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if existing_dependencies == spec_data_files:
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return
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# Remove all existing dependencies, and replace them.
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self.workflow_model.dependencies = []
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for file_data in spec_data_files:
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self.workflow_model.dependencies.append(WorkflowSpecDependencyFile(file_data_id=file_data.id))
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@staticmethod
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def run_master_spec(spec_model, study):
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"""Executes a BPMN specification for the given study, without recording any information to the database
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Useful for running the master specification, which should not persist. """
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spec_data_files = FileService.get_spec_data_files(spec_model.id)
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spec = WorkflowProcessor.get_spec(spec_data_files, spec_model.id)
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try:
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bpmn_workflow = BpmnWorkflow(spec, script_engine=WorkflowProcessor._script_engine)
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bpmn_workflow.data[WorkflowProcessor.STUDY_ID_KEY] = study.id
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bpmn_workflow.data[WorkflowProcessor.VALIDATION_PROCESS_KEY] = False
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bpmn_workflow.do_engine_steps()
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except WorkflowException as we:
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raise ApiError.from_task_spec("error_running_master_spec", str(we), we.sender)
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if not bpmn_workflow.is_completed():
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raise ApiError("master_spec_not_automatic",
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"The master spec should only contain fully automated tasks, it failed to complete.")
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return bpmn_workflow.last_task.data
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@staticmethod
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def get_parser():
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parser = MyCustomParser()
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return parser
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@staticmethod
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def get_spec(file_data_models: List[FileDataModel], workflow_spec_id):
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"""Returns a SpiffWorkflow specification for the given workflow spec,
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using the files provided. The Workflow_spec_id is only used to generate
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better error messages."""
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parser = WorkflowProcessor.get_parser()
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process_id = None
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for file_data in file_data_models:
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if file_data.file_model.type == FileType.bpmn:
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bpmn: etree.Element = etree.fromstring(file_data.data)
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if file_data.file_model.primary:
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process_id = FileService.get_process_id(bpmn)
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parser.add_bpmn_xml(bpmn, filename=file_data.file_model.name)
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elif file_data.file_model.type == FileType.dmn:
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dmn: etree.Element = etree.fromstring(file_data.data)
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parser.add_dmn_xml(dmn, filename=file_data.file_model.name)
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if process_id is None:
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raise (ApiError(code="no_primary_bpmn_error",
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message="There is no primary BPMN model defined for workflow %s" % workflow_spec_id))
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try:
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spec = parser.get_spec(process_id)
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except ValidationException as ve:
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raise ApiError(code="workflow_validation_error",
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message="Failed to parse Workflow Specification '%s'" % workflow_spec_id +
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"Error is %s" % str(ve),
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file_name=ve.filename,
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task_id=ve.id,
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tag=ve.tag)
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return spec
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@staticmethod
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def status_of(bpmn_workflow):
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if bpmn_workflow.is_completed():
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return WorkflowStatus.complete
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user_tasks = bpmn_workflow.get_ready_user_tasks()
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if len(user_tasks) > 0:
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return WorkflowStatus.user_input_required
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else:
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return WorkflowStatus.waiting
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# def hard_reset(self):
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# """Recreate this workflow. This will be useful when a workflow specification changes.
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# """
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# self.spec_data_files = FileService.get_spec_data_files(workflow_spec_id=self.workflow_spec_id)
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# new_spec = WorkflowProcessor.get_spec(self.spec_data_files, self.workflow_spec_id)
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# new_bpmn_workflow = BpmnWorkflow(new_spec, script_engine=self._script_engine)
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# new_bpmn_workflow.data = self.bpmn_workflow.data
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# try:
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# new_bpmn_workflow.do_engine_steps()
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# except WorkflowException as we:
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# raise ApiError.from_task_spec("hard_reset_engine_steps_error", str(we), we.sender)
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# self.bpmn_workflow = new_bpmn_workflow
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def get_status(self):
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return self.status_of(self.bpmn_workflow)
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def do_engine_steps(self):
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try:
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self.bpmn_workflow.do_engine_steps()
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except WorkflowTaskExecException as we:
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raise ApiError.from_task("task_error", str(we), we.task)
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def cancel_notify(self):
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try:
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self.bpmn_workflow.cancel_notify()
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except WorkflowTaskExecException as we:
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raise ApiError.from_task("task_error", str(we), we.task)
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def serialize(self):
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return self._serializer.serialize_workflow(self.bpmn_workflow,include_spec=True)
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def next_user_tasks(self):
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return self.bpmn_workflow.get_ready_user_tasks()
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def next_task(self):
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"""Returns the next task that should be completed
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even if there are parallel tasks and multiple options are
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available.
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If the workflow is complete
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it will return the final end task.
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"""
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# If the whole blessed mess is done, return the end_event task in the tree
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if self.bpmn_workflow.is_completed():
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for task in SpiffTask.Iterator(self.bpmn_workflow.task_tree, SpiffTask.ANY_MASK):
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if isinstance(task.task_spec, EndEvent):
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return task
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# If there are ready tasks to complete, return the next ready task, but return the one
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# in the active parallel path if possible.
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ready_tasks = self.bpmn_workflow.get_tasks(SpiffTask.READY)
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if len(ready_tasks) > 0:
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for task in ready_tasks:
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if task.parent == self.bpmn_workflow.last_task:
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return task
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return ready_tasks[0]
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# If there are no ready tasks, but the thing isn't complete yet, find the first non-complete task
|
|
# and return that
|
|
next_task = None
|
|
for task in SpiffTask.Iterator(self.bpmn_workflow.task_tree, SpiffTask.NOT_FINISHED_MASK):
|
|
next_task = task
|
|
return next_task
|
|
|
|
def previous_task(self):
|
|
return None
|
|
|
|
def complete_task(self, task):
|
|
self.bpmn_workflow.complete_task_from_id(task.id)
|
|
|
|
def get_data(self):
|
|
return self.bpmn_workflow.data
|
|
|
|
def get_workflow_id(self):
|
|
return self.workflow_model.id
|
|
|
|
def get_study_id(self):
|
|
return self.bpmn_workflow.data[self.STUDY_ID_KEY]
|
|
|
|
def get_ready_user_tasks(self):
|
|
return self.bpmn_workflow.get_ready_user_tasks()
|
|
|
|
def get_current_user_tasks(self):
|
|
"""Return a list of all user tasks that are READY or
|
|
COMPLETE and are parallel to the READY Task."""
|
|
ready_tasks = self.bpmn_workflow.get_ready_user_tasks()
|
|
additional_tasks = []
|
|
if len(ready_tasks) > 0:
|
|
for child in ready_tasks[0].parent.children:
|
|
if child.state == SpiffTask.COMPLETED:
|
|
additional_tasks.append(child)
|
|
return ready_tasks + additional_tasks
|
|
|
|
def get_all_user_tasks(self):
|
|
all_tasks = self.bpmn_workflow.get_tasks(SpiffTask.ANY_MASK)
|
|
return [t for t in all_tasks if not self.bpmn_workflow._is_engine_task(t.task_spec)]
|
|
|
|
def get_all_completed_tasks(self):
|
|
all_tasks = self.bpmn_workflow.get_tasks(SpiffTask.ANY_MASK)
|
|
return [t for t in all_tasks
|
|
if not self.bpmn_workflow._is_engine_task(t.task_spec) and t.state in [t.COMPLETED, t.CANCELLED]]
|
|
|
|
def get_nav_item(self, task):
|
|
for nav_item in self.bpmn_workflow.get_nav_list():
|
|
if nav_item['task_id'] == task.id:
|
|
return nav_item
|
|
|
|
def find_spec_and_field_by_field_id(self, field_id):
|
|
"""Tracks down a form field by name in the workflow spec,
|
|
only looks at ready tasks. Returns a tuple of the task, and form"""
|
|
for spec in self.bpmn_workflow.spec.task_specs.values():
|
|
if hasattr(spec, "form"):
|
|
for field in spec.form.fields:
|
|
if field.id == field_id:
|
|
return spec, field
|
|
raise ApiError("invalid_field",
|
|
"Unable to find a task in the workflow with a lookup field called: %s" % field_id)
|