# Source code for gpi.topsort

```
#!/usr/bin/env python
# Copyright (C) 2014 Dignity Health
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# NO CLINICAL USE. THE SOFTWARE IS NOT INTENDED FOR COMMERCIAL PURPOSES
# AND SHOULD BE USED ONLY FOR NON-COMMERCIAL RESEARCH PURPOSES. THE
# SOFTWARE MAY NOT IN ANY EVENT BE USED FOR ANY CLINICAL OR DIAGNOSTIC
# PURPOSES. YOU ACKNOWLEDGE AND AGREE THAT THE SOFTWARE IS NOT INTENDED FOR
# USE IN ANY HIGH RISK OR STRICT LIABILITY ACTIVITY, INCLUDING BUT NOT
# LIMITED TO LIFE SUPPORT OR EMERGENCY MEDICAL OPERATIONS OR USES. LICENSOR
# MAKES NO WARRANTY AND HAS NO LIABILITY ARISING FROM ANY USE OF THE
# SOFTWARE IN ANY HIGH RISK OR STRICT LIABILITY ACTIVITIES.
#
# The code in this file was modifed/derived from the topsort.py with the
# following license:
#
# Permission is hereby granted to copy, modify and use the above source
# code for any purpose as long as the following comment line is included
# with it:
#
# Original topological sort code written by Ofer Faigon
# (www.bitformation.com) and used with permission
[docs]def topological_sort(items, partial_order):
"""Perform topological sort.
items is a list of items to be sorted.
partial_order is a list of pairs. If pair (a,b) is in it, it means
that item a should appear before item b.
Returns a list of the items in one of the possible orders, or None
if partial_order contains a loop.
"""
def add_node(graph, node):
"""Add a node to the graph if not already exists."""
if node not in graph:
graph[node] = [0] # 0 = number of arcs coming into this node.
def add_arc(graph, fromnode, tonode):
"""Add an arc to a graph. Can create multiple arcs.
The end nodes must already exist."""
graph[fromnode].append(tonode)
# Update the count of incoming arcs in tonode.
graph[tonode][0] = graph[tonode][0] + 1
# step 1 - create a directed graph with an arc a->b for each input
# pair (a,b).
# The graph is represented by a dictionary. The dictionary contains
# a pair item:list for each node in the graph. /item/ is the value
# of the node. /list/'s 1st item is the count of incoming arcs, and
# the rest are the destinations of the outgoing arcs. For example:
# {'a':[0,'b','c'], 'b':[1], 'c':[1]}
# represents the graph: c <-- a --> b
# The graph may contain loops and multiple arcs.
# Note that our representation does not contain reference loops to
# cause GC problems even when the represented graph contains loops,
# because we keep the node names rather than references to the nodes.
graph = {}
for v in items:
add_node(graph, v)
for a,b in partial_order:
add_arc(graph, a, b)
# Step 2 - find all roots (nodes with zero incoming arcs).
roots = [node for (node,nodeinfo) in list(graph.items()) if nodeinfo[0] == 0]
# step 3 - repeatedly emit a root and remove it from the graph. Removing
# a node may convert some of the node's direct children into roots.
# Whenever that happens, we append the new roots to the list of
# current roots.
sorted = []
while len(roots) != 0:
# If len(roots) is always 1 when we get here, it means that
# the input describes a complete ordering and there is only
# one possible output.
# When len(roots) > 1, we can choose any root to send to the
# output; this freedom represents the multiple complete orderings
# that satisfy the input restrictions. We arbitrarily take one of
# the roots using pop(). Note that for the algorithm to be efficient,
# this operation must be done in O(1) time.
root = roots.pop()
sorted.append(root)
for child in graph[root][1:]:
graph[child][0] = graph[child][0] - 1
if graph[child][0] == 0:
roots.append(child)
del graph[root]
if len(list(graph.items())) != 0:
# There is a loop in the input.
return None
return sorted
[docs]def topsort(connection_list):
"""NRZ:
The connection list is a list of pairs indicating flow direction through node ordering.
-we only care about nodes with connections
-so only itemize those nodes
"""
# remove redundant connections
c = set(connection_list)
# list connected nodes
l = set([ i for i,j in c ] + [ j for i,j in c ])
return topological_sort(l,c)
if __name__ == '__main__':
print("test topsort")
print((topological_sort([1,2,3], [(1,2),(1,3),(3,2)]))) # --> [1,3,2]
print((topological_sort([1,2], [(2,1),(2,1)]))) # --> [2,1]
print((topological_sort([1,2], [(1,2),(2,1)]))) # --> None
print((topological_sort([0,1,2], [(0,1),(1,2),(2,1)]))) # --> None
# hashable type
x = type
y = int
z = float
print((topological_sort([x,y,z], [(x,y),(x,z),(z,y)]))) # --> [1,3,2]
print((topsort( [(x,y),(x,z),(z,y)] )))
print("cyclic and acylic graphs")
print((topsort( [(1,2),(1,3),(3,2),(5,6),(5,7),(7,6),(7,5)] )))
print("multiple graphs")
print((topsort( [(1,2),(1,3),(3,2),(5,6),(5,7),(7,6)] )))
```