- Update to 2.5:
* Highlights:
+ Dropped support for Python 3.5.
+ add Pathlib support to work with files.
+ improve performance.
+ Updated docs and tests.
+ Removed code designed to work with Python 2.
* New Functions:
+ lukes_partitioning
+ triadic analysis functions
+ functions for trophic levels analysis
+ d_separated
+ is_regular and other regular graph measures
+ graph_hash using Weisfeiler Lehman methods
+ common_neighbor_centrality (CCPA link prediction)
+ max_weight_clique
+ path_weight and is_path
+ rescale_layout_dict
+ junction_tree
* New generators:
+ paley_graph
+ interval_graph
* New layouts:
+ multipartite_layout
- To see improvements, API changes and deprecations, please visit:
https://networkx.github.io/documentation/stable/release/release_2.5.html
- Dropped patches already included by upstream:
* numpy-38-test.patch
* matplotlib.patch
* networkx-pr4012-use-mpl.patch
OBS-URL: https://build.opensuse.org/request/show/833726
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-networkx?expand=0&rev=26
Highlights:
* Remove deprecated code from 1.x
* Support for Python 3.8
* Switched to pytest for testing
* Last release to support Python 3.5
* Fifteen new fuctions, including onion decomposition and linear prufing
* Three new generators, such as a directed joint degree generator
- Add numpy-38-test.patch, to correct test failure under Python 3.8
- Update URL, upstream changed to tarballs from zipfiles.
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-networkx?expand=0&rev=13
- Update to version 2.3
Highlights:
* Dropped support for Python 2. We are no longer supporting Python 2.7 and we will
start changing code to take advantage of Python 3 features we couldn't before.
* Added some Moral Graph analysis functions.
* Enable matplotlib drawing using curved arrows via connectionstyle parameter.
* Remove ticks and axes labels from matplotlib plots.
* Two new generators of Harary Graphs.
* Added Dual Barabasi-Albert model
* Added VoteRank algorithm
* Added Equitable coloring algorithms
* Added planar layout algorithms
* Les Miserables network example
* Javascript example update
OBS-URL: https://build.opensuse.org/request/show/717962
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-networkx?expand=0&rev=11
- Update to version 2.2:
* Add support for Python 3.7. This is the last release to support
Python 2.
* Uniform random number generator (RNG) handling which defaults
to global RNGs but allows specification of a single RNG for all
random numbers in NX.
* Improved GraphViews to ease subclassing and remove cyclic
references which caused trouble with deepcopy and pickle.
* New Graph method G.update(H)
- Run tests
- Update project url
OBS-URL: https://build.opensuse.org/request/show/662473
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-networkx?expand=0&rev=5
- update to 1.10:
* connected_components, weakly_connected_components, and
strongly_connected_components return now a generator of
sets of nodes. Previously the generator was of lists of
nodes. This PR also refactored the connected_components
and weakly_connected_components implementations making them
faster, especially for large graphs.
* The func_iter functions in Di/Multi/Graphs classes are slated
for removal in NetworkX 2.0 release. func will behave like func_iter
and return an iterator instead of list. These functions are deprecated
in NetworkX 1.10 release.
* A enumerate_all_cliques function is added in the clique package
(networkx.algorithms.clique) for enumerating all cliques
(including nonmaximal ones) of undirected graphs.
* A coloring package (networkx.algorithms.coloring) is created for graph
coloring algorithms. Initially, a greedy_color function is provided
for coloring graphs using various greedy heuristics.
* A new generator edge_dfs, added to networkx.algorithms.traversal, implements
a depth-first traversal of the edges in a graph. This complements
functionality provided by a depth-first traversal of the nodes in
a graph. For multigraphs, it allows the user to know precisely which
edges were followed in a traversal. All NetworkX graph types are
supported. A traversal can also reverse edge orientations or ignore them.
* A find_cycle function is added to the networkx.algorithms.cycles package
to find a cycle in a graph. Edge orientations can be optionally
reversed or ignored.
* Add a random generator for the duplication-divergence model.
* A new networkx.algorithms.dominance package is added for dominance/dominator
algorithms on directed graphs. It contains a immediate_dominators
function for computing immediate dominators/dominator trees and a (forwarded request 330044 from tbechtold)
OBS-URL: https://build.opensuse.org/request/show/330047
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-networkx?expand=0&rev=8
