Files
deb-python-taskflow/taskflow/patterns/graph_flow.py
Joshua Harlow bdf1bf18dc Don't forget to return self
To retain the functionality where we can chain
function calls to add, link we need to return the
object we are acting on (instead of none).

Change-Id: Iadf0f9d3a21b6d079c1edd29063196180f5222ed
2013-12-06 19:52:52 -08:00

227 lines
7.5 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 networkx as nx
from networkx.algorithms import traversal
from taskflow import exceptions as exc
from taskflow import flow
from taskflow.utils import graph_utils
class Flow(flow.Flow):
"""Graph flow pattern
Contained *flows/tasks* will be executed according to their dependencies
which will be resolved by using the *flows/tasks* provides and requires
mappings or by following manually created dependency links.
From dependencies directed graph is build. If it has edge A -> B, this
means B depends on A.
Note: Cyclic dependencies are not allowed.
"""
def __init__(self, name):
super(Flow, self).__init__(name)
self._graph = nx.freeze(nx.DiGraph())
def _validate(self, graph=None):
if graph is None:
graph = self._graph
# Ensure that there is a valid topological ordering.
if not nx.is_directed_acyclic_graph(graph):
raise exc.DependencyFailure("No path through the items in the"
" graph produces an ordering that"
" will allow for correct dependency"
" resolution")
def link(self, u, v):
"""Link existing node u as a runtime dependency of existing node v."""
if not self._graph.has_node(u):
raise ValueError('Item %s not found to link from' % (u))
if not self._graph.has_node(v):
raise ValueError('Item %s not found to link to' % (v))
self._swap(self._link(u, v, manual=True))
return self
def _link(self, u, v, graph=None, reason=None, manual=False):
mutable_graph = True
if graph is None:
graph = self._graph
mutable_graph = False
# NOTE(harlowja): Add an edge to a temporary copy and only if that
# copy is valid then do we swap with the underlying graph.
attrs = graph_utils.get_edge_attrs(graph, u, v)
if not attrs:
attrs = {}
if manual:
attrs['manual'] = True
if reason is not None:
if 'reasons' not in attrs:
attrs['reasons'] = set()
attrs['reasons'].add(reason)
if not mutable_graph:
graph = nx.DiGraph(graph)
graph.add_edge(u, v, **attrs)
return graph
def _swap(self, replacement_graph):
"""Validates the replacement graph and then swaps the underlying graph
with a frozen version of the replacement graph (this maintains the
invariant that the underlying graph is immutable).
"""
self._validate(replacement_graph)
self._graph = nx.freeze(replacement_graph)
def add(self, *items):
"""Adds a given task/tasks/flow/flows to this flow."""
items = [i for i in items if not self._graph.has_node(i)]
if not items:
return self
requirements = collections.defaultdict(list)
provided = {}
def update_requirements(node):
for value in node.requires:
requirements[value].append(node)
for node in self:
update_requirements(node)
for value in node.provides:
provided[value] = node
# NOTE(harlowja): Add items and edges to a temporary copy of the
# underlying graph and only if that is successful added to do we then
# swap with the underlying graph.
tmp_graph = nx.DiGraph(self._graph)
for item in items:
tmp_graph.add_node(item)
update_requirements(item)
for value in item.provides:
if value in provided:
raise exc.DependencyFailure(
"%(item)s provides %(value)s but is already being"
" provided by %(flow)s and duplicate producers"
" are disallowed"
% dict(item=item.name,
flow=provided[value].name,
value=value))
provided[value] = item
for value in item.requires:
if value in provided:
self._link(provided[value], item,
graph=tmp_graph, reason=value)
for value in item.provides:
if value in requirements:
for node in requirements[value]:
self._link(item, node,
graph=tmp_graph, reason=value)
self._swap(tmp_graph)
return self
def __len__(self):
return self.graph.number_of_nodes()
def __iter__(self):
for n in self.graph.nodes_iter():
yield n
@property
def provides(self):
provides = set()
for subflow in self:
provides.update(subflow.provides)
return provides
@property
def requires(self):
requires = set()
for subflow in self:
requires.update(subflow.requires)
return requires - self.provides
@property
def graph(self):
return self._graph
class TargetedFlow(Flow):
"""Graph flow with a target.
Adds possibility to execute a flow up to certain graph node
(task or subflow).
"""
def __init__(self, *args, **kwargs):
super(TargetedFlow, self).__init__(*args, **kwargs)
self._subgraph = None
self._target = None
def set_target(self, target_item):
"""Set target for the flow.
Any items (tasks or subflows) not needed for the target
item will not be executed.
"""
if not self._graph.has_node(target_item):
raise ValueError('Item %s not found' % target_item)
self._target = target_item
self._subgraph = None
def reset_target(self):
"""Reset target for the flow.
All items of the flow will be executed.
"""
self._target = None
self._subgraph = None
def add(self, *items):
"""Adds a given task/tasks/flow/flows to this flow."""
super(TargetedFlow, self).add(*items)
# reset cached subgraph, in case it was affected
self._subgraph = None
return self
def link(self, u, v):
"""Link existing node u as a runtime dependency of existing node v."""
super(TargetedFlow, self).link(u, v)
# reset cached subgraph, in case it was affected
self._subgraph = None
return self
@property
def graph(self):
if self._subgraph is not None:
return self._subgraph
if self._target is None:
return self._graph
nodes = [self._target]
nodes.extend(dst for _src, dst in
traversal.dfs_edges(self._graph.reverse(), self._target))
self._subgraph = nx.freeze(self._graph.subgraph(nodes))
return self._subgraph