Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

# networkx.algorithms.shortest_paths.weighted.dijkstra_path¶

`dijkstra_path`(G, source, target, weight='weight')[source]

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

Uses Dijkstra’s Method to compute the shortest weighted path between two nodes in a graph.

Parameters
GNetworkX graph
sourcenode

Starting node

targetnode

Ending node

weightstring or function

If this is a string, then edge weights will be accessed via the edge attribute with this key (that is, the weight of the edge joining `u` to `v` will be `G.edges[u, v][weight]`). If no such edge attribute exists, the weight of the edge is assumed to be one.

If this is a function, the weight of an edge is the value returned by the function. The function must accept exactly three positional arguments: the two endpoints of an edge and the dictionary of edge attributes for that edge. The function must return a number.

Returns
pathlist

List of nodes in a shortest path.

Raises
NodeNotFound

If `source` is not in `G`.

NetworkXNoPath

If no path exists between source and target.

Notes

Edge weight attributes must be numerical. Distances are calculated as sums of weighted edges traversed.

The weight function can be used to hide edges by returning None. So `weight = lambda u, v, d: 1 if d['color']=="red" else None` will find the shortest red path.

The weight function can be used to include node weights.

```>>> def func(u, v, d):
...     node_u_wt = G.nodes[u].get("node_weight", 1)
...     node_v_wt = G.nodes[v].get("node_weight", 1)
...     edge_wt = d.get("weight", 1)
...     return node_u_wt / 2 + node_v_wt / 2 + edge_wt
```

In this example we take the average of start and end node weights of an edge and add it to the weight of the edge.

The function `single_source_dijkstra()` computes both path and length-of-path if you need both, use that.

Examples

```>>> G = nx.path_graph(5)
>>> print(nx.dijkstra_path(G, 0, 4))
[0, 1, 2, 3, 4]
```