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.. _glossary:
Glossary
========
.. glossary::
dictionary
A Python dictionary maps keys to values. Also known as "hashes",
or "associative arrays" in other programming languages.
See :ref:`the Python tutorial on dictionaries <tut-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`.
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