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MultiGraph.add_edge(u, v, key=None, attr_dict=None, **attr)

Add an edge between u and v.

The nodes u and v will be automatically added if they are not already in the graph.

Edge attributes can be specified with keywords or by providing a dictionary with key/value pairs. See examples below.

Parameters :

u,v : nodes

Nodes can be, for example, strings or numbers. Nodes must be hashable (and not None) Python objects.

key : hashable identifier, optional (default=lowest unused integer)

Used to distinguish multiedges between a pair of nodes.

attr_dict : dictionary, optional (default= no attributes)

Dictionary of edge attributes. Key/value pairs will update existing data associated with the edge.

attr : keyword arguments, optional

Edge data (or labels or objects) can be assigned using keyword arguments.

See also

add a collection of edges


To replace/update edge data, use the optional key argument to identify a unique edge. Otherwise a new edge will be created.

NetworkX algorithms designed for weighted graphs cannot use multigraphs directly because it is not clear how to handle multiedge weights. Convert to Graph using edge attribute ‘weight’ to enable weighted graph algorithms.


The following all add the edge e=(1,2) to graph G:

>>> G = nx.Graph()   # or DiGraph, MultiGraph, MultiDiGraph, etc
>>> e = (1,2)
>>> G.add_edge(1, 2)           # explicit two-node form
>>> G.add_edge(*e)             # single edge as tuple of two nodes
>>> G.add_edges_from( [(1,2)] ) # add edges from iterable container

Associate data to edges using keywords:

>>> G.add_edge(1, 2, weight=3)
>>> G.add_edge(1, 2, key=0, weight=4)   # update data for key=0
>>> G.add_edge(1, 3, weight=7, capacity=15, length=342.7)