Python: How to find if a path exists between 2 nodes in a graph?

Question

I am using networkx package of Python.

Answer 1

Use

shortest_path(G, source, target)

or one of the Shortest Path methods. Stay clear of the methods which return paths between all nodes however if you merely have two specific nodes to test for connectivity.

Answer 2

• dijkstra_path(G, source, target)

  Returns the shortest path from source to target in a weighted graph G.

Answer 3

>>> import networkx as nx
>>> G=nx.empty_graph()
>>> G.add_edge(1,2)
>>> G.add_edge(2,3)
>>> G.add_edge(4,5)
>>> nx.path.bidirectional_dijkstra(G,1,2)
(1, [1, 2])
>>> nx.path.bidirectional_dijkstra(G,1,3)
(2, [1, 2, 3])
>>> nx.path.bidirectional_dijkstra(G,1,4)
False
>>> nx.path.bidirectional_dijkstra(G,1,5)
False
>>> 

You can also use the result as a boolean value

>>> if nx.path.bidirectional_dijkstra(G,1,2): print "path exists"
... 
path exists
>>> if nx.path.bidirectional_dijkstra(G,1,4): print "path exists"
... 
>>> 

Answer 4

To check whether there is a path between two nodes in a graph -

>>> import networkx as nx
>>> G=nx.Graph()
>>> G.add_edge(1,2)
>>> G.add_edge(2,3)
>>> nx.has_path(G,1,3)
True
>>> G.add_edge(4,5)
>>> nx.has_path(G,1,5)
False

For more information, please refer has_path — NetworkX 1.7 documentation

Answer 5

Using a disjoint set data structure:

Create a singleton set for every vertex in the graph, then union the sets containing each of the pair of vertices for every edge in the graph.

Finally, you know a path exists between two vertices if they are in the same set.

See the wikipedia page on the disjoint set data structure.

This is much more efficient than using a path finding algorithm.