networkx.Graph.edges¶

Graph.
edges
¶ An EdgeView of the Graph as G.edges or G.edges().
edges(self, nbunch=None, data=False, default=None)
The EdgeView provides setlike operations on the edgetuples as well as edge attribute lookup. When called, it also provides an EdgeDataView object which allows control of access to edge attributes (but does not provide setlike operations). Hence,
G.edges[u, v]['color']
provides the value of the color attribute for edge(u, v)
whilefor (u, v, c) in G.edges.data('color', default='red'):
iterates through all the edges yielding the color attribute with default'red'
if no color attribute exists.Parameters:  nbunch (single node, container, or all nodes (default= all nodes)) – The view will only report edges incident to these nodes.
 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 don’t have the requested attribute. Only relevant if data is not True or False.
Returns: edges – A view of edge attributes, usually it iterates over (u, v) or (u, v, d) tuples of edges, but can also be used for attribute lookup as
edges[u, v]['foo']
.Return type: EdgeView
Notes
Nodes in nbunch that are not in the graph will be (quietly) ignored. For directed graphs this returns the outedges.
Examples
>>> G = nx.path_graph(3) # or MultiGraph, etc >>> G.add_edge(2, 3, weight=5) >>> [e for e in G.edges] [(0, 1), (1, 2), (2, 3)] >>> G.edges.data() # default data is {} (empty dict) EdgeDataView([(0, 1, {}), (1, 2, {}), (2, 3, {'weight': 5})]) >>> G.edges.data('weight', default=1) EdgeDataView([(0, 1, 1), (1, 2, 1), (2, 3, 5)]) >>> G.edges([0, 3]) # only edges incident to these nodes EdgeDataView([(0, 1), (3, 2)]) >>> G.edges(0) # only edges incident to a single node (use G.adj[0]?) EdgeDataView([(0, 1)])