Files
deb-python-taskflow/taskflow/patterns/graph_flow.py
2013-05-21 16:53:12 -07:00

111 lines
4.2 KiB
Python

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (C) 2012 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 collections
import logging
from networkx import exception as g_exc
from networkx.algorithms import dag
from networkx.classes import digraph
from taskflow import exceptions as exc
from taskflow.patterns import ordered_flow
LOG = logging.getLogger(__name__)
class Flow(ordered_flow.Flow):
"""A flow which will analyze the attached tasks input requirements and
determine who provides said input and order the task so that said providing
task will be ran before."""
def __init__(self, name, tolerant=False, parents=None):
super(Flow, self).__init__(name, tolerant, parents)
self._graph = digraph.DiGraph()
self._connected = False
def add(self, task):
# Do something with the task, either store it for later
# or add it to the graph right now...
#
# Only insert the node to start, connect all the edges
# together later after all nodes have been added.
self._graph.add_node(task)
self._connected = False
def _fetch_task_inputs(self, task):
inputs = {}
for n in task.requires():
for (them, there_result) in self.results:
if (not self._graph.has_edge(them, task) or
not n in them.provides() or not there_result):
continue
if n in there_result:
# NOTE(harlowja): later results overwrite
# prior results for the same keys, which is
# typically desired.
inputs[n] = there_result[n]
return inputs
def order(self):
self.connect()
try:
return dag.topological_sort(self._graph)
except g_exc.NetworkXUnfeasible:
raise exc.InvalidStateException("Unable to correctly determine "
"the path through the provided "
"flow which will satisfy the "
"tasks needed inputs and outputs.")
def connect(self):
"""Connects the nodes & edges of the graph together."""
if self._connected or len(self._graph) == 0:
return
# Figure out the provider of items and the requirers of items.
provides_what = collections.defaultdict(list)
requires_what = collections.defaultdict(list)
for t in self._graph.nodes_iter():
for r in t.requires():
requires_what[r].append(t)
for p in t.provides():
provides_what[p].append(t)
# Link providers to consumers of items.
for (want_what, who_wants) in requires_what.iteritems():
who_provided = 0
for p in provides_what[want_what]:
# P produces for N so thats why we link P->N and not N->P
for n in who_wants:
if p is n:
# No self-referencing allowed.
continue
why = {
want_what: True,
}
self._graph.add_edge(p, n, why)
who_provided += 1
if not who_provided:
who_wants = ", ".join([str(a) for a in who_wants])
raise exc.InvalidStateException("%s requires input %s "
"but no other task produces "
"said output." % (who_wants,
want_what))
self._connected = True