#!/usr/bin/python # tsort.py # Topological sorting. # # Copyright (C) 2010 Red Hat, Inc. # # This copyrighted material is made available to anyone wishing to use, # modify, copy, or redistribute it subject to the terms and conditions of # the GNU General Public License v.2, or (at your option) any later version. # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY expressed or implied, including the implied warranties of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General # Public License for more details. You should have received a copy of the # GNU General Public License along with this program; if not, write to the # Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301, USA. Any Red Hat trademarks that are incorporated in the # source code or documentation are not subject to the GNU General Public # License and may only be used or replicated with the express permission of # Red Hat, Inc. # # Red Hat Author(s): Dave Lehman # class CyclicGraphError(Exception): pass def tsort(graph): order = [] # sorted list of items if not graph or not graph['items']: return order # determine which nodes have no incoming edges roots = [n for n in graph['items'] if graph['incoming'][n] == 0] if not roots: raise CyclicGraphError("no root nodes") visited = [] # list of nodes visited, for cycle detection while roots: # remove a root, add it to the order root = roots.pop() if root in visited: raise CyclicGraphError("graph contains cycles") visited.append(root) i = graph['items'].index(root) order.append(root) # remove each edge from the root to another node for (parent, child) in [e for e in graph['edges'] if e[0] == root]: graph['incoming'][child] -= 1 graph['edges'].remove((parent, child)) # if destination node is now a root, add it to roots if graph['incoming'][child] == 0: roots.append(child) if len(graph['items']) != len(visited): raise CyclicGraphError("graph contains cycles") return order def create_graph(items, edges): """ Create a graph based on a list of items and a list of edges. Arguments: items - an iterable containing (hashable) items to sort edges - an iterable containing (parent, child) edge pair tuples Return Value: The return value is a dictionary representing the directed graph. It has three keys: items is the same as the input argument of the same name edges is the same as the input argument of the same name incoming is a dict of incoming edge count hashed by item """ graph = {'items': [], # the items to sort 'edges': [], # partial order info: (parent, child) pairs 'incoming': {}} # incoming edge count for each item graph['items'] = items graph['edges'] = edges for item in items: graph['incoming'][item] = 0 for (parent, child) in edges: graph['incoming'][child] += 1 return graph if __name__ == "__main__": items = [5, 2, 3, 4, 1] edges = [(1, 2), (2, 4), (4, 5), (3, 2)] print items print edges graph = create_graph(items, edges) print tsort(graph)