7fe6bf0d6b
In order to make it simpler (and less code) just prefer to use object types that already exist instead of trying to make dictionaries also behave like objects. For those that really need this kind of functionality: https://pypi.python.org/pypi/attrdict Change-Id: Ib7ddfa517f0500082fafac2c3e53fd6a158a6ddf
187 lines
6.7 KiB
Python
187 lines
6.7 KiB
Python
# -*- coding: utf-8 -*-
|
|
|
|
# Copyright (C) 2013 Yahoo! Inc. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License"); you may
|
|
# not use this file except in compliance with the License. You may obtain
|
|
# a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
|
|
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
|
|
# License for the specific language governing permissions and limitations
|
|
# under the License.
|
|
|
|
import json
|
|
import logging
|
|
import os
|
|
import sys
|
|
import time
|
|
|
|
logging.basicConfig(level=logging.ERROR)
|
|
|
|
top_dir = os.path.abspath(os.path.join(os.path.dirname(__file__),
|
|
os.pardir,
|
|
os.pardir))
|
|
sys.path.insert(0, top_dir)
|
|
|
|
|
|
from taskflow import engines
|
|
from taskflow.listeners import printing
|
|
from taskflow.openstack.common import uuidutils
|
|
from taskflow.patterns import graph_flow as gf
|
|
from taskflow.patterns import linear_flow as lf
|
|
from taskflow import task
|
|
from taskflow.utils import misc
|
|
|
|
# INTRO: This example walks through a miniature workflow which simulates a
|
|
# the reception of a API request, creation of a database entry, driver
|
|
# activation (which invokes a 'fake' webservice) and final completion.
|
|
#
|
|
# This example also shows how a function/object (in this class the url sending)
|
|
# that occurs during driver activation can update the progress of a task
|
|
# without being aware of the internals of how to do this by associating a
|
|
# callback that the url sending can update as the sending progresses from 0.0%
|
|
# complete to 100% complete.
|
|
|
|
|
|
class DB(object):
|
|
def query(self, sql):
|
|
print("Querying with: %s" % (sql))
|
|
|
|
|
|
class UrlCaller(object):
|
|
def __init__(self):
|
|
self._send_time = 0.5
|
|
self._chunks = 25
|
|
|
|
def send(self, url, data, status_cb=None):
|
|
sleep_time = float(self._send_time) / self._chunks
|
|
for i in range(0, len(data)):
|
|
time.sleep(sleep_time)
|
|
# As we send the data, each chunk we 'fake' send will progress
|
|
# the sending progress that much further to 100%.
|
|
if status_cb:
|
|
status_cb(float(i) / len(data))
|
|
|
|
|
|
# Since engines save the output of tasks to a optional persistent storage
|
|
# backend resources have to be dealt with in a slightly different manner since
|
|
# resources are transient and can *not* be persisted (or serialized). For tasks
|
|
# that require access to a set of resources it is a common pattern to provide
|
|
# a object (in this case this object) on construction of those tasks via the
|
|
# task constructor.
|
|
class ResourceFetcher(object):
|
|
def __init__(self):
|
|
self._db_handle = None
|
|
self._url_handle = None
|
|
|
|
@property
|
|
def db_handle(self):
|
|
if self._db_handle is None:
|
|
self._db_handle = DB()
|
|
return self._db_handle
|
|
|
|
@property
|
|
def url_handle(self):
|
|
if self._url_handle is None:
|
|
self._url_handle = UrlCaller()
|
|
return self._url_handle
|
|
|
|
|
|
class ExtractInputRequest(task.Task):
|
|
def __init__(self, resources):
|
|
super(ExtractInputRequest, self).__init__(provides="parsed_request")
|
|
self._resources = resources
|
|
|
|
def execute(self, request):
|
|
return {
|
|
'user': request.user,
|
|
'user_id': misc.as_int(request.id),
|
|
'request_id': uuidutils.generate_uuid(),
|
|
}
|
|
|
|
|
|
class MakeDBEntry(task.Task):
|
|
def __init__(self, resources):
|
|
super(MakeDBEntry, self).__init__()
|
|
self._resources = resources
|
|
|
|
def execute(self, parsed_request):
|
|
db_handle = self._resources.db_handle
|
|
db_handle.query("INSERT %s INTO mydb" % (parsed_request))
|
|
|
|
def revert(self, result, parsed_request):
|
|
db_handle = self._resources.db_handle
|
|
db_handle.query("DELETE %s FROM mydb IF EXISTS" % (parsed_request))
|
|
|
|
|
|
class ActivateDriver(task.Task):
|
|
def __init__(self, resources):
|
|
super(ActivateDriver, self).__init__(provides='sent_to')
|
|
self._resources = resources
|
|
self._url = "http://blahblah.com"
|
|
|
|
def execute(self, parsed_request):
|
|
print("Sending billing data to %s" % (self._url))
|
|
url_sender = self._resources.url_handle
|
|
# Note that here we attach our update_progress function (which is a
|
|
# function that the engine also 'binds' to) to the progress function
|
|
# that the url sending helper class uses. This allows the task progress
|
|
# to be tied to the url sending progress, which is very useful for
|
|
# downstream systems to be aware of what a task is doing at any time.
|
|
url_sender.send(self._url, json.dumps(parsed_request),
|
|
status_cb=self.update_progress)
|
|
return self._url
|
|
|
|
def update_progress(self, progress, **kwargs):
|
|
# Override the parent method to also print out the status.
|
|
super(ActivateDriver, self).update_progress(progress, **kwargs)
|
|
print("%s is %0.2f%% done" % (self.name, progress * 100))
|
|
|
|
|
|
class DeclareSuccess(task.Task):
|
|
def execute(self, sent_to):
|
|
print("Done!")
|
|
print("All data processed and sent to %s" % (sent_to))
|
|
|
|
|
|
class DummyUser(object):
|
|
def __init__(self, user, id):
|
|
self.user = user
|
|
self.id = id
|
|
|
|
|
|
# Resources (db handles and similar) of course can *not* be persisted so we
|
|
# need to make sure that we pass this resource fetcher to the tasks constructor
|
|
# so that the tasks have access to any needed resources (the resources are
|
|
# lazily loaded so that they are only created when they are used).
|
|
resources = ResourceFetcher()
|
|
flow = lf.Flow("initialize-me")
|
|
|
|
# 1. First we extract the api request into a usable format.
|
|
# 2. Then we go ahead and make a database entry for our request.
|
|
flow.add(ExtractInputRequest(resources), MakeDBEntry(resources))
|
|
|
|
# 3. Then we activate our payment method and finally declare success.
|
|
sub_flow = gf.Flow("after-initialize")
|
|
sub_flow.add(ActivateDriver(resources), DeclareSuccess())
|
|
flow.add(sub_flow)
|
|
|
|
# Initially populate the storage with the following request object,
|
|
# prepopulating this allows the tasks that dependent on the 'request' variable
|
|
# to start processing (in this case this is the ExtractInputRequest task).
|
|
store = {
|
|
'request': DummyUser(user="bob", id="1.35"),
|
|
}
|
|
eng = engines.load(flow, engine='serial', store=store)
|
|
|
|
# This context manager automatically adds (and automatically removes) a
|
|
# helpful set of state transition notification printing helper utilities
|
|
# that show you exactly what transitions the engine is going through
|
|
# while running the various billing related tasks.
|
|
with printing.PrintingListener(eng):
|
|
eng.run()
|