Question

我无法理解如何使用SpiffWorkflow工作流引擎。什么意味着准确地创建任务，我该怎么做？

此外，我找不到使用SpiffWorkflow的任何示例。谁使用这个引擎？我如何找到用法示例？

Answer 1

我找到了一个例子here.

import sys, os
sys.path.insert(0, os.path.join(os.path.dirname(__file__),  '../../lib'))

from SpiffWorkflow.specs import *
from SpiffWorkflow import Task, Workflow
from SpiffWorkflow.storage import XmlSerializer

def on_entered_cb(workflow, task, taken_path):
    #print "entered:",task.get_name()
    return True

def on_ready_cb(workflow, task, taken_path):
    #print "ready:",task.get_name()
    return True

def on_reached_cb(workflow, task, taken_path):
    #print "reached:",task.get_name()
    return True

def on_complete_cb(workflow, task, taken_path):
    # Record the path.
    print "complete:",task.get_name()
    #print task.get_description()
    indent = '  ' * (task._get_depth() - 1)
    taken_path.append('%s%s' % (indent, task.get_name()))
    return True

class QuestionError(Exception):

    def __init__(self, value):
        self.value = value

    def __str__(self):
        return repr(self.value)

class QuestionWorkflow(object):
    def __init__(self):
        self.serializer = XmlSerializer()

    def set_up(self,filename):
        # Test patterns that are defined in XML format.
        xml = open(filename).read()
        self.wf_spec = WorkflowSpec.deserialize(XmlSerializer(), xml, filename = filename)
        self.taken_path = self.track_workflow(self.wf_spec)
        self.workflow   = Workflow(self.wf_spec)


    def run(self, UserSelection, restart=False):

        if restart:
            self.workflow = Workflow(self.wf_spec)

        workflow = self.workflow
        condition_keys = []
        if UserSelection is None:
            UserSelection = {}

        task_data_dict = UserSelection.copy()

        while not workflow.is_completed():
            tasks = workflow.get_tasks(Task.READY)

            for t in tasks:
                print "Ready:", t.task_spec.name
                if  hasattr(t.task_spec, "cond_task_specs"):
                    for cond, name in t.task_spec.cond_task_specs:
                        for cond_unit in cond.args:
                            if hasattr(cond_unit, "name"):
                                condition_keys.append(cond_unit.name)


            flag_keys_in_user_select = True
            for cond_key in condition_keys:
                if not task_data_dict.has_key(cond_key):
                    print cond_key
                    flag_keys_in_user_select = False
                    break

            if not flag_keys_in_user_select:
                # some tast's condition's key not in input userselect dict
                return
            for t in tasks:
                t.set_data(**task_data_dict)

            workflow.complete_next()

        if not workflow.is_completed():
            raise QuestionError('invalid feature[%s]' % filename)

    def print_trace(self):
        path = '\n'.join(self.taken_path) + '\n'
        info = ""
        info += 'the workflowrun path:\n'
        info += '%s\n' % path
        print info


    def track_task(self, task_spec, taken_path):

        #reached event call back
        if task_spec.reached_event.is_connected(on_reached_cb):
            task_spec.reached_event.disconnect(on_reached_cb)
        task_spec.reached_event.connect(on_reached_cb, taken_path)

        #completed event call back
        if task_spec.completed_event.is_connected(on_complete_cb):
            task_spec.completed_event.disconnect(on_complete_cb)
        task_spec.completed_event.connect(on_complete_cb, taken_path)

        #enter event call back
        if task_spec.entered_event.is_connected(on_entered_cb):
            task_spec.entered_event.disconnect(on_entered_cb)
        task_spec.entered_event.connect(on_entered_cb, taken_path)

        #ready event call back
        if task_spec.ready_event.is_connected(on_ready_cb):
            task_spec.ready_event.disconnect(on_ready_cb)
        task_spec.ready_event.connect(on_ready_cb, taken_path)



    def track_workflow(self, wf_spec, taken_path = None):
        if taken_path is None:
            taken_path = []
        for name in wf_spec.task_specs:
            #print "track_workflow:",name
            self.track_task(wf_spec.task_specs[name], taken_path)
        return taken_path

if __name__ == '__main__':
    qw = QuestionWorkflow()
    qw.set_up("./case.xml")
    print "==========1st question=========="
    user_selct = {'man':'1'}
    qw.run(user_selct)
    print "==========2nd question=========="
    user_selct = {'man':'1', 'house': '2'}
    qw.run(user_selct)
    print "==========3rd question=========="
    user_selct = {'man':'1', 'house': '2', 'why': 'because you are a hero'}
    qw.run(user_selct)

    '''
    print "==========4th question========="
    user_selct = {'man':'1', 'house': '2', 'role':'5'}
    qw.run(user_selct)
    '''

    print "==========fix some question=========="
    user_selct = {'man':'1', 'house': '1', 'role':'5'}
    qw.run(user_selct,True)

    print

Answer 2

或许看看这个文件会有所帮助

https://github.com/knipknap/SpiffWorkflow/blob/master/SpiffWorkflow/specs/WorkflowSpec.py

和这些文档 https://github.com/knipknap/SpiffWorkflow/wiki

Answer 3

我们开发了具有改进功能的Zengine扩展版SpiffWorkFlow。您可以找到它here，并且可以看到here以查找用法示例。

简而言之;

Zengine基于BPMN工作流的框架，具有Tornado，Rabbit AMQP，高级权限，可扩展的脚手架功能等。

建立在以下主要组件之上;

SpiffWorkflow：具有BPMN 2.0支持的强大工作流引擎。 Tornado：Tornado是一个Python Web框架和异步网络库。 Pyoko：Riak KV商店的Django esque ORM。 RabbitMQ：使用传奇的Erlang lang编写的快速，超清晰的AMQP服务器。

如何使用SpiffWorkflow创建任务？

3 个答案: