# -*- coding: utf-8 -*- # 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 six from taskflow import exceptions as exc from taskflow import flow from taskflow.types import graph as gr def _unsatisfied_requires(node, graph, *additional_provided): requires = set(node.requires) if not requires: return requires for provided in additional_provided: # This is using the difference() method vs the - # operator since the latter doesn't work with frozen # or regular sets (when used in combination with ordered # sets). # # If this is not done the following happens... # # TypeError: unsupported operand type(s) # for -: 'set' and 'OrderedSet' requires = requires.difference(provided) if not requires: return requires for pred in graph.bfs_predecessors_iter(node): requires = requires.difference(pred.provides) if not requires: return requires return requires 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, retry=None): super(Flow, self).__init__(name, retry) self._graph = gr.DiGraph() self._graph.freeze() #: Extracts the unsatisified symbol requirements of a single node. _unsatisfied_requires = staticmethod(_unsatisfied_requires) def link(self, u, v, decider=None): """Link existing node u as a runtime dependency of existing node v.""" if not self._graph.has_node(u): raise ValueError("Node '%s' not found to link from" % (u)) if not self._graph.has_node(v): raise ValueError("Node '%s' not found to link to" % (v)) if decider is not None: if not six.callable(decider): raise ValueError("Decider boolean callback must be callable") self._swap(self._link(u, v, manual=True, decider=decider)) return self def _link(self, u, v, graph=None, reason=None, manual=False, decider=None): 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.get_edge_data(u, v) if not attrs: attrs = {} if decider is not None: attrs[flow.LINK_DECIDER] = decider if manual: attrs[flow.LINK_MANUAL] = True if reason is not None: if flow.LINK_REASONS not in attrs: attrs[flow.LINK_REASONS] = set() attrs[flow.LINK_REASONS].add(reason) if not mutable_graph: graph = gr.DiGraph(graph) graph.add_edge(u, v, **attrs) return graph def _swap(self, graph): """Validates the replacement graph and then swaps the underlying graph. After swapping occurs the underlying graph will be frozen so that the immutability invariant is maintained (we may be able to relax this constraint in the future since our exposed public api does not allow direct access to the underlying graph). """ if not graph.is_directed_acyclic(): raise exc.DependencyFailure("No path through the node(s) in the" " graph produces an ordering that" " will allow for logical" " edge traversal") self._graph = graph.freeze() def add(self, *nodes, **kwargs): """Adds a given task/tasks/flow/flows to this flow. :param nodes: node(s) to add to the flow :param kwargs: keyword arguments, the two keyword arguments currently processed are: * ``resolve_requires`` a boolean that when true (the default) implies that when node(s) are added their symbol requirements will be matched to existing node(s) and links will be automatically made to those providers. If multiple possible providers exist then a AmbiguousDependency exception will be raised. * ``resolve_existing``, a boolean that when true (the default) implies that on addition of a new node that existing node(s) will have their requirements scanned for symbols that this newly added node can provide. If a match is found a link is automatically created from the newly added node to the requiree. """ # Let's try to avoid doing any work if we can; since the below code # after this filter can create more temporary graphs that aren't needed # if the nodes already exist... nodes = [i for i in nodes if not self._graph.has_node(i)] if not nodes: return self # This syntax will *hopefully* be better in future versions of python. # # See: http://legacy.python.org/dev/peps/pep-3102/ (python 3.0+) resolve_requires = bool(kwargs.get('resolve_requires', True)) resolve_existing = bool(kwargs.get('resolve_existing', True)) # Figure out what the existing nodes *still* require and what they # provide so we can do this lookup later when inferring. required = collections.defaultdict(list) provided = collections.defaultdict(list) retry_provides = set() if self._retry is not None: for value in self._retry.requires: required[value].append(self._retry) for value in self._retry.provides: retry_provides.add(value) provided[value].append(self._retry) for node in self._graph.nodes_iter(): for value in self._unsatisfied_requires(node, self._graph, retry_provides): required[value].append(node) for value in node.provides: provided[value].append(node) # NOTE(harlowja): Add node(s) and edge(s) 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 = gr.DiGraph(self._graph) for node in nodes: tmp_graph.add_node(node) # Try to find a valid provider. if resolve_requires: for value in self._unsatisfied_requires(node, tmp_graph, retry_provides): if value in provided: providers = provided[value] if len(providers) > 1: provider_names = [n.name for n in providers] raise exc.AmbiguousDependency( "Resolution error detected when" " adding '%(node)s', multiple" " providers %(providers)s found for" " required symbol '%(value)s'" % dict(node=node.name, providers=sorted(provider_names), value=value)) else: self._link(providers[0], node, graph=tmp_graph, reason=value) else: required[value].append(node) for value in node.provides: provided[value].append(node) # See if what we provide fulfills any existing requiree. if resolve_existing: for value in node.provides: if value in required: for requiree in list(required[value]): if requiree is not node: self._link(node, requiree, graph=tmp_graph, reason=value) required[value].remove(requiree) self._swap(tmp_graph) return self def _get_subgraph(self): """Get the active subgraph of _graph. Descendants may override this to make only part of self._graph visible. """ return self._graph def __len__(self): return self._get_subgraph().number_of_nodes() def __iter__(self): for n in self._get_subgraph().topological_sort(): yield n def iter_links(self): for (u, v, e_data) in self._get_subgraph().edges_iter(data=True): yield (u, v, e_data) @property def requires(self): requires = set() retry_provides = set() if self._retry is not None: requires.update(self._retry.requires) retry_provides.update(self._retry.provides) g = self._get_subgraph() for node in g.nodes_iter(): requires.update(self._unsatisfied_requires(node, g, retry_provides)) return frozenset(requires) 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_node): """Set target for the flow. Any node(s) (tasks or subflows) not needed for the target node will not be executed. """ if not self._graph.has_node(target_node): raise ValueError("Node '%s' not found" % target_node) self._target = target_node self._subgraph = None def reset_target(self): """Reset target for the flow. All node(s) of the flow will be executed. """ self._target = None self._subgraph = None def add(self, *nodes): """Adds a given task/tasks/flow/flows to this flow.""" super(TargetedFlow, self).add(*nodes) # reset cached subgraph, in case it was affected self._subgraph = None return self def link(self, u, v, decider=None): """Link existing node u as a runtime dependency of existing node v.""" super(TargetedFlow, self).link(u, v, decider=decider) # reset cached subgraph, in case it was affected self._subgraph = None return self def _get_subgraph(self): if self._subgraph is not None: return self._subgraph if self._target is None: return self._graph nodes = [self._target] nodes.extend(self._graph.bfs_predecessors_iter(self._target)) self._subgraph = self._graph.subgraph(nodes) self._subgraph.freeze() return self._subgraph