from collections import defaultdict | |
from heapq import * | |
def dijkstra(edges, f, t): | |
g = defaultdict(list) | |
for l,r,c in edges: | |
g[l].append((c,r)) | |
q, seen, mins = [(0,f,())], set(), {f: 0} | |
while q: | |
(cost,v1,path) = heappop(q) | |
if v1 not in seen: | |
seen.add(v1) | |
path = (v1, path) | |
if v1 == t: return (cost, path) | |
for c, v2 in g.get(v1, ()): | |
if v2 in seen: continue | |
prev = mins.get(v2, None) | |
next = cost + c | |
if prev is None or next < prev: | |
mins[v2] = next | |
heappush(q, (next, v2, path)) | |
return float("inf"), None | |
if __name__ == "__main__": | |
edges = [ | |
("A", "B", 7), | |
("A", "D", 5), | |
("B", "C", 8), | |
("B", "D", 9), | |
("B", "E", 7), | |
("C", "E", 5), | |
("D", "E", 15), | |
("D", "F", 6), | |
("E", "F", 8), | |
("E", "G", 9), | |
("F", "G", 11) | |
] | |
print "=== Dijkstra ===" | |
print edges | |
print "A -> E:" | |
print dijkstra(edges, "A", "E") | |
print "F -> G:" | |
print dijkstra(edges, "F", "G") |
Unless I am missing something here, this is a BFS with a min-heap, not a Dijkstra's algorithm.
@JixinSiND Dijkstra's algorithm is essentially a weighted version of BFS.
Just leaving a comment to let the author know that his code has been inappropriately taken and re-used as material for teaching at a University master in London. The authorship has been modified to report the lecturer's one instead.
https://www.dcs.bbk.ac.uk/~ale/pwd/2019-20/pwd-8/src/pwd-ex-dijkstra+heap.py
@alelom Thanks a lot for letting me know, such a kind of you! This is not the first time this code was copy-pasted into lecture materials and/or projects codebases. Honestly, if it helped students to learn - I would be glad and proud. I care less about authorship or any sort of attribution. On the one hand, I wouldn't want to encourage disrespectful actions, on the other hand, I don't have reliable way to prevent this from happening. So, choosing between spread of knowledge or nurturing morality, I would always vote for the former. Thanks again for letting me know!
I just care for what is right. If I were the lecturer, I'd quote the real author and the source – an action that does not diminish the teaching potential, and encourages sharing of good code lawfully.
Thank you so much for this gift, very clean and clever solution
If anyone just wonders how to easily receive as output only the value of the solution remove the cost from the return at line 15:
if v1 == t: return cost
instead of
if v1 == t: return (cost, path)
Nice and clean
Thank you very much for this beautiful algorithm.
pretty sure this is not Dijkstra; you're doing heappush(q, (next, v2, path))
at the very end, but in True dijkstra it would need a call to "decrease_key", which in python is heap._siftdown
@xdavidliu I was confused by this until I saw https://stackoverflow.com/a/31123108. I think Dijkstra's algorithm is a higher level concept, so either implementation is valid.
Hi, I think I made a bit cleaner (subjectively :)) implementation in Python that uses RBTree as a priority queue with tests there
https://github.com/ehborisov/algorithms/blob/master/8.Graphs/dijkstra.py