Glossary

dictionary

A Python dictionary maps keys to values. Also known as “hashes”, or “associative arrays” in other programming languages. See the Python tutorial on dictionaries.

edge

Edges are either two-tuples of nodes (u, v) or three tuples of nodes with an edge attribute dictionary (u, v, dict).

ebunch

An iterable container of edge tuples like a list, iterator, or file.

edge attribute

Edges can have arbitrary Python objects assigned as attributes by using keyword/value pairs when adding an edge assigning to the G.edges[u][v] attribute dictionary for the specified edge u-v.

nbunch

An nbunch is a single node, container of nodes or None (representing all nodes). It can be a list, set, graph, etc. To filter an nbunch so that only nodes actually in G appear, use G.nbunch_iter(nbunch).

If the nbunch is a container or iterable that is not itself a node in the graph, then it will be treated as an iterable of nodes, for instance, when nbunch is a string or a tuple:

>>> import networkx as nx
>>> G = nx.DiGraph()
>>> G.add_edges_from([("b", "c"), ("a", "ab"), ("ab", "c")])
>>> G.edges("ab")
OutEdgeDataView([('ab', 'c')])

Since “ab” is a node in G, it is treated as a single node:

>>> G.edges("bc")
OutEdgeDataView([('b', 'c')])

Since “bc” is not a node in G, it is treated as an iterator:

>>> G.edges(["bc"])
OutEdgeDataView([])

If “bc” is wrapped in a list, the list is the iterable and “bc” is treated as a single node. That is, if the nbunch is an iterable of iterables, the inner iterables will always be treated as nodes:

>>> G.edges("de")
OutEdgeDataView([])

When nbunch is an iterator that is not itself a node and none of its elements are nodes, then the edge view suite of methods return an empty edge view.

node

A node can be any hashable Python object except None.

node attribute

Nodes can have arbitrary Python objects assigned as attributes by using keyword/value pairs when adding a node or assigning to the G.nodes[n] attribute dictionary for the specified node n.