a8b83e1e2c
Ensure that we connect from some input to some node that provides said input (not itself).
110 lines
4.0 KiB
Python
110 lines
4.0 KiB
Python
# -*- coding: utf-8 -*-
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# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright (C) 2012 Yahoo! Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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from collections import defaultdict
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import logging
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from networkx import exception as g_exc
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from networkx.algorithms import dag
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from networkx.classes import digraph
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from taskflow import exceptions as exc
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from taskflow.patterns import ordered_flow
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LOG = logging.getLogger(__name__)
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class Flow(ordered_flow.Flow):
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"""A flow which will analyze the attached tasks input requirements and
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determine who provides said input and order the task so that said providing
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task will be ran before."""
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def __init__(self, name, tolerant=False, parents=None):
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super(Flow, self).__init__(name, tolerant, parents)
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self._graph = digraph.DiGraph()
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self._connected = False
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def add(self, task):
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# Do something with the task, either store it for later
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# or add it to the graph right now...
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#
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# Only insert the node to start, connect all the edges
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# together later after all nodes have been added.
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self._graph.add_node(task)
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self._connected = False
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def _fetch_task_inputs(self, task):
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task_needs = task.requires()
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if not task_needs:
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return None
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inputs = {}
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for (_who, there_result) in self.results:
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for n in task_needs:
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if there_result and n in there_result:
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inputs[n] = there_result[n]
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return inputs
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def run(self, context, *args, **kwargs):
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self.connect()
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return super(Flow, self).run(context, *args, **kwargs)
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def order(self):
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self.connect()
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try:
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return dag.topological_sort(self._graph)
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except g_exc.NetworkXUnfeasible:
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raise exc.InvalidStateException("Unable to correctly determine "
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"the path through the provided "
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"flow which will satisfy the "
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"tasks needed inputs and outputs.")
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def connect(self):
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"""Connects the nodes & edges of the graph together."""
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if self._connected or len(self._graph) == 0:
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return
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provides_what = defaultdict(list)
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requires_what = defaultdict(list)
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for t in self._graph.nodes_iter():
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for r in t.requires():
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requires_what[r].append(t)
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for p in t.provides():
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provides_what[p].append(t)
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for (want_what, who_wants) in requires_what.items():
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who_provided = 0
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for p in provides_what.get(want_what, []):
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# P produces for N so thats why we link P->N and not N->P
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for n in who_wants:
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if p is n:
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# No self-referencing allowed.
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continue
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why = {
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want_what: True,
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}
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self._graph.add_edge(p, n, why)
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who_provided += 1
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if not who_provided:
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raise exc.InvalidStateException("Task/s %s requires input %s "
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"but no other task produces "
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"said output." % (who_wants,
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want_what))
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self._connected = True
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