5ca61f956e
Most of the utility graph functions we have can be connected to a directed graph class that itself derives (and adds on to) the networkx base class. Doing this allows for functionality that isn't exposed in networkx to be exposed in our subclass (which is a useful pattern to have). It also makes it possible (if ever needed) to replace the networkx usage in taskflow with something else if this ever becomes a major request. Change-Id: I0a825d5637236d7b5dbdbda0d426adb0183d5ba3
123 lines
4.6 KiB
Python
123 lines
4.6 KiB
Python
# -*- coding: utf-8 -*-
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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 networkx as nx
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import six
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class DiGraph(nx.DiGraph):
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"""A directed graph subclass with useful utility functions."""
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def __init__(self, data=None, name=''):
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super(DiGraph, self).__init__(name=name, data=data)
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self.frozen = False
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def freeze(self):
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"""Freezes the graph so that no more mutations can occur."""
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if not self.frozen:
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nx.freeze(self)
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return self
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def get_edge_data(self, u, v, default=None):
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"""Returns a *copy* of the attribute dictionary associated with edges
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between (u, v).
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NOTE(harlowja): this differs from the networkx get_edge_data() as that
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function does not return a copy (but returns a reference to the actual
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edge data).
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"""
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try:
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return dict(self.adj[u][v])
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except KeyError:
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return default
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def topological_sort(self):
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"""Return a list of nodes in this graph in topological sort order."""
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return nx.topological_sort(self)
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def pformat(self):
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"""Pretty formats your graph into a string representation that includes
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details about your graph, including; name, type, frozeness, node count,
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nodes, edge count, edges, graph density and graph cycles (if any).
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"""
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lines = []
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lines.append("Name: %s" % self.name)
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lines.append("Type: %s" % type(self).__name__)
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lines.append("Frozen: %s" % nx.is_frozen(self))
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lines.append("Nodes: %s" % self.number_of_nodes())
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for n in self.nodes_iter():
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lines.append(" - %s" % n)
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lines.append("Edges: %s" % self.number_of_edges())
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for (u, v, e_data) in self.edges_iter(data=True):
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if e_data:
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lines.append(" %s -> %s (%s)" % (u, v, e_data))
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else:
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lines.append(" %s -> %s" % (u, v))
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lines.append("Density: %0.3f" % nx.density(self))
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cycles = list(nx.cycles.recursive_simple_cycles(self))
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lines.append("Cycles: %s" % len(cycles))
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for cycle in cycles:
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buf = six.StringIO()
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buf.write("%s" % (cycle[0]))
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for i in range(1, len(cycle)):
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buf.write(" --> %s" % (cycle[i]))
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buf.write(" --> %s" % (cycle[0]))
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lines.append(" %s" % buf.getvalue())
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return "\n".join(lines)
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def export_to_dot(self):
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"""Exports the graph to a dot format (requires pydot library)."""
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return nx.to_pydot(self).to_string()
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def is_directed_acyclic(self):
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"""Returns if this graph is a DAG or not."""
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return nx.is_directed_acyclic_graph(self)
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def no_successors_iter(self):
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"""Returns an iterator for all nodes with no successors."""
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for n in self.nodes_iter():
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if not len(self.successors(n)):
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yield n
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def no_predecessors_iter(self):
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"""Returns an iterator for all nodes with no predecessors."""
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for n in self.nodes_iter():
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if not len(self.predecessors(n)):
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yield n
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def merge_graphs(graphs, allow_overlaps=False):
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"""Merges a bunch of graphs into a single graph."""
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if not graphs:
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return None
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graph = graphs[0]
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for g in graphs[1:]:
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# This should ensure that the nodes to be merged do not already exist
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# in the graph that is to be merged into. This could be problematic if
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# there are duplicates.
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if not allow_overlaps:
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# Attempt to induce a subgraph using the to be merged graphs nodes
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# and see if any graph results.
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overlaps = graph.subgraph(g.nodes_iter())
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if len(overlaps):
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raise ValueError("Can not merge graph %s into %s since there "
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"are %s overlapping nodes" (g, graph,
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len(overlaps)))
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# Keep the target graphs name.
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name = graph.name
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graph = nx.algorithms.compose(graph, g)
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graph.name = name
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return graph
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