doc/release/release_2.8.1.rst
Release date: 18 May 2022
Supports Python 3.8, 3.9, and 3.10
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
For more information, please visit our website <https://networkx.org/>_
and our :ref:gallery of examples <examples_gallery>.
Please send comments and questions to the networkx-discuss mailing list <http://groups.google.com/group/networkx-discuss>_.
Minor documentation and bug fixes.
Changed the treatment of directed graphs for has_eulerian_path which
used to allow graphs with isolated nodes, i.e. nodes with zero degree to have
an eulerian path. For undirected graphs, on the other hand, has_eulerian_path
does not allow isolated nodes. For example:
>>> G = nx.DiGraph([(0, 1), (1, 2), (2, 0)])
>>> G.add_node(3)
>>> nx.has_eulerian_path(G)
The above snippet used to produce True whereas the below one used to produce False.
>>> G = nx.Graph([(0, 1), (1, 2), (2, 0)])
>>> G.add_node(3)
>>> nx.has_eulerian_path(G)
The change makes the method consistent for both undirected and directed graph types so
that it does not allow isolated nodes. (Both examples produce False now.)
is_bipartite_node_set now raises an exception when the tested nodes are
not distinct (previously this would not affect the outcome).
This is to avoid surprising behaviour when using node sets in other bipartite
algorithms, for example it yields incorrect results for weighted_projected_graph.
A total of 52 changes have been committed.
nodes property on Graph (#5600)_mat_spect_approx in favor of simpler procedure (#5624)