"
> To do this I need to consider the out edges from each node in sorted order by 
> weight. The problem is that making a list of the edges and sorting them each 
> time I visit a node is slow on my large graph.
> I could explicitly store the sorted list of edges at each node but this would 
> use too much extra space on my large graph.
How large is your graph? Pre-sorting the edge indices for every node takes only 
a few seconds even on a graph with one million edges on my machine:

inclist = g.get_inclist()
weights = g.es["weight"]
for row in inclist:
    row.sort(key=weights.__getitem__, reverse=True)

If you cannot afford storing the whole pre-sorted list at once but you visit 
some nodes more frequently than others, you could probably try caching the 
pre-sorted lists in a memory-limited least-recently-used cache. This way you 
could keep your memory usage under control while not having to recalculate the 
list every time you visit a node if the list is still in the cache.
"

Thank you for the reply.

I can afford the time to presort the edge indices for every node once as you 
suggest. I just wanted to avoid using the space to store all the edges twice. 
Once in the normal igraph graph and once in a sorted list labeling each vertex. 
 It seems that you are effectively representing the same graph twice if you do 
that. Maybe there is no way round this however.

Marshall

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