d433a5323f
To avoid having one set of options coming from `engine_conf` and another set of options coming from `kwargs` and another set coming from `engine_conf` if it is a URI just start to shift toward `engine_conf` being deprecated and `engine` being a string type only (or a URI with additional query parameters) and having any additional **kwargs that are provided just get merged into the final engine options. This adds a new helper function that handles all these various options and adds in a keyword argument `engine` that will be shifted to in a future version (in that future version we can also then remove the `engine_conf` and just stick to a smaller set of option mechanisms). It also adjusts all examples to use this new and more easier to understand format and adjusts tests, conductor interface to use this new more easily understandable style of getting an engine. Change-Id: Ic7617057338e0c63775cf38a24643cff6e454950
92 lines
2.8 KiB
Python
92 lines
2.8 KiB
Python
# -*- coding: utf-8 -*-
|
|
|
|
# Copyright (C) 2012-2013 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 logging
|
|
import os
|
|
import sys
|
|
|
|
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)
|
|
|
|
import taskflow.engines
|
|
from taskflow.patterns import graph_flow as gf
|
|
from taskflow.patterns import linear_flow as lf
|
|
from taskflow import task
|
|
|
|
|
|
# In this example there are complex *inferred* dependencies between tasks that
|
|
# are used to perform a simple set of linear equations.
|
|
#
|
|
# As you will see below the tasks just define what they require as input
|
|
# and produce as output (named values). Then the user doesn't care about
|
|
# ordering the tasks (in this case the tasks calculate pieces of the overall
|
|
# equation).
|
|
#
|
|
# As you will notice a graph flow resolves dependencies automatically using the
|
|
# tasks symbol requirements and provided symbol values and no orderin
|
|
# dependency has to be manually created.
|
|
#
|
|
# Also notice that flows of any types can be nested into a graph flow; showing
|
|
# that subflow dependencies (and associated ordering) will be inferred too.
|
|
|
|
|
|
class Adder(task.Task):
|
|
|
|
def execute(self, x, y):
|
|
return x + y
|
|
|
|
|
|
flow = gf.Flow('root').add(
|
|
lf.Flow('nested_linear').add(
|
|
# x2 = y3+y4 = 12
|
|
Adder("add2", provides='x2', rebind=['y3', 'y4']),
|
|
# x1 = y1+y2 = 4
|
|
Adder("add1", provides='x1', rebind=['y1', 'y2'])
|
|
),
|
|
# x5 = x1+x3 = 20
|
|
Adder("add5", provides='x5', rebind=['x1', 'x3']),
|
|
# x3 = x1+x2 = 16
|
|
Adder("add3", provides='x3', rebind=['x1', 'x2']),
|
|
# x4 = x2+y5 = 21
|
|
Adder("add4", provides='x4', rebind=['x2', 'y5']),
|
|
# x6 = x5+x4 = 41
|
|
Adder("add6", provides='x6', rebind=['x5', 'x4']),
|
|
# x7 = x6+x6 = 82
|
|
Adder("add7", provides='x7', rebind=['x6', 'x6']))
|
|
|
|
# Provide the initial variable inputs using a storage dictionary.
|
|
store = {
|
|
"y1": 1,
|
|
"y2": 3,
|
|
"y3": 5,
|
|
"y4": 7,
|
|
"y5": 9,
|
|
}
|
|
|
|
result = taskflow.engines.run(
|
|
flow, engine='serial', store=store)
|
|
|
|
print("Single threaded engine result %s" % result)
|
|
|
|
result = taskflow.engines.run(
|
|
flow, engine='parallel', store=store)
|
|
|
|
print("Multi threaded engine result %s" % result)
|