edges_iter¶

Graph.
edges_iter
(nbunch=None, data=False, default=None)[source]¶ Return an iterator over the edges.
Edges are returned as tuples with optional data in the order (node, neighbor, data).
Parameters:  nbunch (iterable container, optional (default= all nodes)) – A container of nodes. The container will be iterated through once.
 data (string or bool, optional (default=False)) – The edge attribute returned in 3tuple (u,v,ddict[data]). If True, return edge attribute dict in 3tuple (u,v,ddict). If False, return 2tuple (u,v).
 default (value, optional (default=None)) – Value used for edges that dont have the requested attribute. Only relevant if data is not True or False.
Returns: edge_iter – An iterator of (u,v) or (u,v,d) tuples of edges.
Return type: iterator
See also
edges()
 return a list of edges
Notes
Nodes in nbunch that are not in the graph will be (quietly) ignored. For directed graphs this returns the outedges.
Examples
>>> G = nx.Graph() # or MultiGraph, etc >>> G.add_path([0,1,2]) >>> G.add_edge(2,3,weight=5) >>> [e for e in G.edges_iter()] [(0, 1), (1, 2), (2, 3)] >>> list(G.edges_iter(data=True)) # default data is {} (empty dict) [(0, 1, {}), (1, 2, {}), (2, 3, {'weight': 5})] >>> list(G.edges_iter(data='weight', default=1)) [(0, 1, 1), (1, 2, 1), (2, 3, 5)] >>> list(G.edges_iter([0,3])) [(0, 1), (3, 2)] >>> list(G.edges_iter(0)) [(0, 1)]