Handling Infinite Loop in Dijkstra's Algorithm Implementation in Python with NetworkX
I've been researching this but I'm working with an scenario with my Dijkstra's algorithm implementation using the NetworkX library in Python... I noticed that under certain conditions, my algorithm enters an infinite loop, especially when there are negative weight edges in the graph. I've set up my graph as follows: ```python import networkx as nx g = nx.DiGraph() g.add_weighted_edges_from([(1, 2, 4), (1, 3, 1), (3, 2, -2), (2, 4, 2)]) ``` When I run the Dijkstra algorithm: ```python shortest_paths = nx.single_source_dijkstra_path(g, 1) ``` I expected it to return the shortest path from node 1 to all other nodes, but instead, it seems to hang indefinitely when there are negative weights involved. I have done some research and found that Dijkstra’s algorithm is not suitable for graphs with negative weights, but I wasn't sure how to handle this in my implementation. I tried adding a check for negative weights before executing the algorithm: ```python if any(weight < 0 for u, v, weight in g.edges(data='weight')): print('Graph contains negative weight edges. Dijkstra is not applicable.') else: shortest_paths = nx.single_source_dijkstra_path(g, 1) ``` However, even with this check, my program seems to still hang when I try to run it with various graphs, particularly if the structure is more complex. Could anyone guide to understand why this might be happening or suggest a workaround? I'm using NetworkX version 2.6.3 and Python 3.9.5. Any insights would be greatly appreciated! Thanks for your help in advance! I'm using Python 3.11 in this project. Is this even possible? Any ideas what could be causing this?