/usr/lib/python2.7/dist-packages/taskflow/types/graph.py is in python-taskflow 2.3.0-2.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 | # -*- 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 os
import networkx as nx
from networkx.drawing import nx_pydot
import six
def _common_format(g, edge_notation):
lines = []
lines.append("Name: %s" % g.name)
lines.append("Type: %s" % type(g).__name__)
lines.append("Frozen: %s" % nx.is_frozen(g))
lines.append("Density: %0.3f" % nx.density(g))
lines.append("Nodes: %s" % g.number_of_nodes())
for n, n_data in g.nodes_iter(data=True):
if n_data:
lines.append(" - %s (%s)" % (n, n_data))
else:
lines.append(" - %s" % n)
lines.append("Edges: %s" % g.number_of_edges())
for (u, v, e_data) in g.edges_iter(data=True):
if e_data:
lines.append(" %s %s %s (%s)" % (u, edge_notation, v, e_data))
else:
lines.append(" %s %s %s" % (u, edge_notation, v))
return lines
class Graph(nx.Graph):
"""A graph subclass with useful utility functions."""
def __init__(self, data=None, name=''):
super(Graph, self).__init__(name=name, data=data)
self.frozen = False
def freeze(self):
"""Freezes the graph so that no more mutations can occur."""
if not self.frozen:
nx.freeze(self)
return self
def export_to_dot(self):
"""Exports the graph to a dot format (requires pydot library)."""
return nx_pydot.to_pydot(self).to_string()
def pformat(self):
"""Pretty formats your graph into a string."""
return os.linesep.join(_common_format(self, "<->"))
class DiGraph(nx.DiGraph):
"""A directed graph subclass with useful utility functions."""
def __init__(self, data=None, name=''):
super(DiGraph, self).__init__(name=name, data=data)
self.frozen = False
def freeze(self):
"""Freezes the graph so that no more mutations can occur."""
if not self.frozen:
nx.freeze(self)
return self
def get_edge_data(self, u, v, default=None):
"""Returns a *copy* of the edge attribute dictionary between (u, v).
NOTE(harlowja): this differs from the networkx get_edge_data() as that
function does not return a copy (but returns a reference to the actual
edge data).
"""
try:
return dict(self.adj[u][v])
except KeyError:
return default
def topological_sort(self):
"""Return a list of nodes in this graph in topological sort order."""
return nx.topological_sort(self)
def pformat(self):
"""Pretty formats your graph into a string.
This pretty formatted string representation includes many useful
details about your graph, including; name, type, frozeness, node count,
nodes, edge count, edges, graph density and graph cycles (if any).
"""
lines = _common_format(self, "->")
cycles = list(nx.cycles.recursive_simple_cycles(self))
lines.append("Cycles: %s" % len(cycles))
for cycle in cycles:
buf = six.StringIO()
buf.write("%s" % (cycle[0]))
for i in range(1, len(cycle)):
buf.write(" --> %s" % (cycle[i]))
buf.write(" --> %s" % (cycle[0]))
lines.append(" %s" % buf.getvalue())
return os.linesep.join(lines)
def export_to_dot(self):
"""Exports the graph to a dot format (requires pydot library)."""
return nx_pydot.to_pydot(self).to_string()
def is_directed_acyclic(self):
"""Returns if this graph is a DAG or not."""
return nx.is_directed_acyclic_graph(self)
def no_successors_iter(self):
"""Returns an iterator for all nodes with no successors."""
for n in self.nodes_iter():
if not len(self.successors(n)):
yield n
def no_predecessors_iter(self):
"""Returns an iterator for all nodes with no predecessors."""
for n in self.nodes_iter():
if not len(self.predecessors(n)):
yield n
def bfs_predecessors_iter(self, n):
"""Iterates breadth first over *all* predecessors of a given node.
This will go through the nodes predecessors, then the predecessor nodes
predecessors and so on until no more predecessors are found.
NOTE(harlowja): predecessor cycles (if they exist) will not be iterated
over more than once (this prevents infinite iteration).
"""
visited = set([n])
queue = collections.deque(self.predecessors_iter(n))
while queue:
pred = queue.popleft()
if pred not in visited:
yield pred
visited.add(pred)
for pred_pred in self.predecessors_iter(pred):
if pred_pred not in visited:
queue.append(pred_pred)
class OrderedDiGraph(DiGraph):
"""A directed graph subclass with useful utility functions.
This derivative retains node, edge, insertion and iteration
ordering (so that the iteration order matches the insertion
order).
"""
node_dict_factory = collections.OrderedDict
adjlist_dict_factory = collections.OrderedDict
edge_attr_dict_factory = collections.OrderedDict
class OrderedGraph(Graph):
"""A graph subclass with useful utility functions.
This derivative retains node, edge, insertion and iteration
ordering (so that the iteration order matches the insertion
order).
"""
node_dict_factory = collections.OrderedDict
adjlist_dict_factory = collections.OrderedDict
edge_attr_dict_factory = collections.OrderedDict
def merge_graphs(graph, *graphs, **kwargs):
"""Merges a bunch of graphs into a new graph.
If no additional graphs are provided the first graph is
returned unmodified otherwise the merged graph is returned.
"""
tmp_graph = graph
allow_overlaps = kwargs.get('allow_overlaps', False)
overlap_detector = kwargs.get('overlap_detector')
if overlap_detector is not None and not six.callable(overlap_detector):
raise ValueError("Overlap detection callback expected to be callable")
elif overlap_detector is None:
overlap_detector = (lambda to_graph, from_graph:
len(to_graph.subgraph(from_graph.nodes_iter())))
for g in graphs:
# This should ensure that the nodes to be merged do not already exist
# in the graph that is to be merged into. This could be problematic if
# there are duplicates.
if not allow_overlaps:
# Attempt to induce a subgraph using the to be merged graphs nodes
# and see if any graph results.
overlaps = overlap_detector(graph, g)
if overlaps:
raise ValueError("Can not merge graph %s into %s since there "
"are %s overlapping nodes (and we do not "
"support merging nodes)" % (g, graph,
overlaps))
graph = nx.algorithms.compose(graph, g)
# Keep the first graphs name.
if graphs:
graph.name = tmp_graph.name
return graph
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