b4f592c524
Incases where a item is produced by 2+ tasks we should allow the task that depends on that item to get the 2+ items produced as a list of items. We can also disallow this type of production via a new boolean option.
131 lines
5.0 KiB
Python
131 lines
5.0 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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import collections
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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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allow_same_inputs=True):
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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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self._allow_same_inputs = allow_same_inputs
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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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inputs = collections.defaultdict(list)
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for n in task.requires():
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for (them, there_result) in self.results:
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if (not self._graph.has_edge(them, task) or
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not n in them.provides()):
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continue
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if there_result and n in there_result:
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inputs[n].append(there_result[n])
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else:
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inputs[n].append(None)
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def collapse_functor(k_v):
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(k, v) = k_v
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if len(v) == 1:
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v = v[0]
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return (k, v)
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return dict(map(collapse_functor, inputs.iteritems()))
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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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# Figure out the provider of items and the requirers of items.
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provides_what = collections.defaultdict(list)
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requires_what = collections.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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def get_providers(node, want_what):
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providers = []
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for (producer, me) in self._graph.in_edges_iter(node):
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providing_what = self._graph.get_edge_data(producer, me)
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if want_what in providing_what:
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providers.append(producer)
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return providers
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# Link providers to consumers of items.
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for (want_what, who_wants) in requires_what.iteritems():
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who_provided = 0
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for p in provides_what[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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if (len(get_providers(n, want_what)) and not
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self._allow_same_inputs):
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msg = "Multiple providers of %s not allowed."
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raise exc.InvalidStateException(msg % (want_what))
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self._graph.add_edge(p, n, attr_dict={
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want_what: True,
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})
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who_provided += 1
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if not who_provided:
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who_wants = ", ".join([str(a) for a in who_wants])
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raise exc.InvalidStateException("%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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