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    <p>You can find the relevant docs here :)</p> <p><a href="http://networkx.github.io/documentation/latest/reference/generated/networkx.algorithms.simple_paths.all_simple_paths.html#networkx.algorithms.simple_paths.all_simple_paths" rel="nofollow">Simple Paths in NetworkX</a></p> <p>essentially it's just a tree search of some sort</p> <p>you can use the <a href="http://networkx.github.io/documentation/latest/reference/generated/networkx.classes.function.nodes.html#networkx.classes.function.nodes" rel="nofollow">list of nodes</a> and do this</p> <pre><code>list_of_nodes = nodes(my_graph) for mysource in list_of_nodes: for mytarget in list_of_nodes: if source != target: print all_simple_paths(my_graph,source=mysource,target=mytarget, cutoff=4) </code></pre> <p>If you want all the shortest paths of length 4 you can use <a href="http://networkx.github.io/documentation/latest/reference/generated/networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path.html#networkx.algorithms.shortest_paths.unweighted.all_pairs_shortest_path" rel="nofollow">``all_pairs_shortest_path_```</a></p> <pre><code>paths = all_pairs_shortest_path(my_graph,cutoff=4) for k,v in paths: if len(paths[k][v]) == 4: print paths[k][v] </code></pre> <p>There is no real command built in to generate all the simple paths of a certain length as the only way to find that is to generate a tree from every node, e.g. doing a modified version of my for loop above since that uses a modified depth-first search.</p> <hr> <blockquote> <p>"A path with no repeated vertices is called a simple path" - <a href="http://en.wikipedia.org/wiki/Path_%28graph_theory%29" rel="nofollow">Wikipedia</a></p> </blockquote> <p>If you would like a <a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1084515" rel="nofollow">paper citation</a>. The only way to check for simple paths is to check from each node. If you have a graph with 90000 elements; there is no other way to check if two connect :/. The 'target' is really not consequential as it's just another cutoff, though if you have a large number of nodes it can make a difference so you're right there :).</p> <pre><code> " def _all_simple_paths_graph(G, source, target, cutoff=None): if cutoff &lt; 1: return visited = [source] stack = [iter(G[source])] while stack: children = stack[-1] child = next(children, None) if child is None: stack.pop() visited.pop() elif len(visited) &lt; cutoff: if child == target: yield visited + [target] elif child not in visited: visited.append(child) stack.append(iter(G[child])) else: #len(visited) == cutoff: if child == target or target in children: yield visited + [target] stack.pop() visited.pop()" </code></pre> <p>code above from <a href="http://networkx.github.io/documentation/latest/reference/algorithms.html" rel="nofollow">networkx docs</a></p> <p>to modify it in order to generate the DFS without the 'target' cutoff you can use:</p> <pre><code> def _all_simple_paths_graph(G, source, target, cutoff=None): if cutoff &lt; 1: return visited = [source] stack = [iter(G[source])] while stack: children = stack[-1] child = next(children, None) if child is None: stack.pop() visited.pop() elif len(visited) &lt; cutoff: #if child == target: # yield visited + [target] #elif child not in visited: if child not in visited: visited.append(child) stack.append(iter(G[child])) #else: #len(visited) == cutoff: #if child == target or target in children: # yield visited + [target] #stack.pop() #visited.pop() </code></pre> <hr> <p>Hope that works for you :)</p>
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    1. POSub graph isomorphism
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    1. USEiyrioü von Kauyf
    1. USEiyrioü von Kauyf
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    1. COThat says "Generate all simple paths in the graph G from source to target." which is not what I am looking for. I don't have a source node in my problem.
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    2. COit's a directed graph, you can set the source to any node and the target to any other. this is more specific then you need; that's never a problem
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    3. COMy problem is to find all simple paths of length 4. Not all simple paths starting from some particular node.
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