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def max_distance(node, ancestors, distances):
"""Calculate the max distance to an ancestor.
Return None if not all possible ancestors have known distances"""
best = None
if node in distances:
best = distances[node]
for ancestor in ancestors[node]:
# An ancestor which is not listed in ancestors will never be in
# distances, so we pretend it never existed.
if ancestor not in ancestors:
continue
if ancestor not in distances:
return None
if best is None or distances[ancestor] > best:
best = distances[ancestor] + 1
return best
def farthest_nodes(graph, ancestors, start):
"""Produce a list of nodes, sorted by distance from a start node.
This is an algorithm devised by Aaron Bentley, because applying Dijkstra
backwards seemed too complicated.
For each node, we walk its descendants. If all the descendant's ancestors
have a max-distance-to-start, (excluding ones that can never reach start),
we calculate their max-distance-to-start, and schedule their descendants.
So when a node's last parent acquires a distance, it will acquire a
distance on the next iteration.
Once we know the max distances for all nodes, we can return a list sorted
by distance, farthest first.
"""
distances = {start: 0}
lines = set([start])
while len(lines) > 0:
new_lines = set()
for line in lines:
assert line not in graph[line], "%s refers to itself" % line
for descendant in graph[line]:
distance = max_distance(descendant, ancestors, distances)
if distance is None:
continue
distances[descendant] = distance
new_lines.add(descendant)
lines = new_lines
def by_distance(n):
return distances[n],n
node_list = distances.keys()
node_list.sort(key=by_distance, reverse=True)
return node_list
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