Name: python3-networkx	Distribution: openSUSE Leap 15.2
Version: 2.4	Vendor: openSUSE
Release: lp152.1.1	Build date: Sat May 30 09:20:07 2020
Group: Development/Languages/Python	Build host: cloud121
Size: 12617447	Source RPM: python-networkx-2.4-lp152.1.1.src.rpm
Packager: https://bugs.opensuse.org
Url: https://networkx.github.io/
Summary: Python package for the study of complex networks

NetworkX (NX) is a Python package for the creation, manipulation, and study of the structure, dynamics,
and functions of complex networks.

Features:
 * Includes standard graph-theoretic and statistical physics functions
 * Exchange of network algorithms between applications, disciplines, and platforms
 * Includes many classic graphs and synthetic networks
 * Nodes and edges can be "anything" (e.g. time-series, text, images, XML records)
 * Exploits existing code from high-quality legacy software in C, C++, Fortran, etc.
 * Unit-tested

Provides

python3-networkx

Requires

License

BSD-3-Clause

Changelog

* Fri Nov 22 2019 steven.kowalik@suse.com
  - Drop incorrectly calculated dependency on python33
  - Switch to using %pytest macro
* Sun Nov 17 2019 Steve Kowalik <steven.kowalik@suse.com>
  - Update to version 2.4
    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.
* Tue Jul 23 2019 Todd R <toddrme2178@gmail.com>
  - 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
* Tue Jan 22 2019 Matej Cepl <mcepl@suse.com>
  - Switch off test_subgraph_centrality_big_graph test, as it leads to
    crashes on i586, gh#networkx/networkx#3304.
* Fri Jan 04 2019 Jan Engelhardt <jengelh@inai.de>
  - Fix incomplete summary. Trim filler wording from description.
* Wed Jan 02 2019 Martin Pluskal <mpluskal@suse.com>
  - 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
* Sun Sep 02 2018 arun@gmx.de
  - specfile:
    * update copyright year
    * removed devel from noarch package
  - update to version 2.1:
    * Highlights
      + Arrows for drawing DiGraph edges are vastly improved! And an
      example to show them.
      + More than 12 new functions for graph generation, manipulation
      and/or new graph algorithms.
      o Add a large clique size heuristic function (#2830)
      o Add rooted product function (#2825)
      o Label Propagation Community Detection (#2821)
      o Minimum cycle basis (#2823)
      o Add Mycielski Operator (#2785)
      o Adds prefix_tree, dag_to_branching, and example. (#2784)
      o Add inverse_line_graph generator from #2241 (#2782)
      o Steiner tree and metric closure. (#2252)
      o Add flow based node and edge disjoint paths. (#2063)
      o Update geometric networks with new models (#2498)
      o Graph edit distance (#2729)
      o Added function for finding a k-edge-augmentation (#2572)
      + G.name is no longer processed by graph operators. It remains as
      a property mechanism to access G.graph['name'] but the user is
      in charge of updating or changing it for copies, subgraphs,
      unions and other graph operations.
* Tue Oct 31 2017 arun@gmx.de
  - specfile:
    * changes from tar.gz to zip
    * updated sed
    * INSTALL doesn't seem to be packaged anymore, deleted "rm" command
  - update to version 2.0:
    * Highlights
      + This release is the result of over two years of work with 1212
      commits and 193 merges by 86 contributors. Highlights include:
      + We have made major changes to the methods in the Multi/Di/Graph
      classes. There is a migration guide for people moving from 1.X
      to 2.0.
      + We updated the documentation system.
    * full release notes at
      https://networkx.github.io/documentation/stable/release/release_2.0.html
* Sun Aug 06 2017 toddrme2178@gmail.com
  - Fix shebangs
* Thu May 11 2017 toddrme2178@gmail.com
  - Implement single-spec version.
  - Fix source URL.
* Wed Aug 17 2016 tbechtold@suse.com
  update to version networkx-1.11
    * Update release and news info for v1.10.1
    * Use utils.testing to handle testing edge and node equality
    * Update news to include 1.10 release highlights
    * Remove spurious line due to typo.
    * Fix algebraicconnectivity float conversion
    * Fix python3 numpy wont read in {}.values to array.
    * update requirements.txt on v1.11 branch
    * update doc/requirements.txt to point Sphinx-origin_stable
    * Update license, readme, and release.py for networkx-1.11
    * adjust tutorial to mention import write_dot
    * Revert some API changes in layout.py due to bugs.
    * Update news and api for v1.11
    * Update authors, copyrights and EOL space
    * Add release date in news
    * Add tests, convert center to np.array, fix domain_size
    * Put graphviz install outside check for python2.7
    * Activate Appveyor-CI
    * Add layout tests and minor docs
    * networkx-1.11rc2 label
    * Remove all the symbolic links from the 'examples/' directory
    * v1.11 Add utils functions to flow variable __all__
    * Fix Sphinx for v1.11
    * Prepare release number and news.rst for v1.11
    * simplify pydot imports, use testing.utils routines
    * Get the month right.
    * update release docs files for v1.11
    * Use pydotplus for all supported python versions
    * Add note about pyggraphviz and pydotplus import changes
    * Modified release.py
    * change copyright year in doc build
    * For v1.11 drop support for python3.2 and add 3.5
    * Update news.rst for v1.11
    * Examples and doc changes
    * Re-add scaling inside fruchterman_reingold
    * Update conf.py to point to make_examples_rst.py
    * Reinstate v1.10 layout except center. Fix bugs
    * Adjust imports in drawing layouts with graphviz
    * Doc tweak on edges for v1.11
* Sun Mar 13 2016 dmueller@suse.com
  - add license/readme
* Wed Sep 09 2015 tbechtold@suse.com
  - 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
      dominance_frontiers function for computing dominance frontiers.
    * The GML reader/parser and writer/generator are rewritten to remove
      the dependence on pyparsing and enable handling of arbitrary graph data.
    * The network simplex method in the networkx.algorithms.flow package is
      rewritten to improve its performance and support multi- and disconnected
      networks. For some cases, the new implementation is two or three orders
      of magnitude faster than the old implementation.
    * Added the Margulis--Gabber--Galil graph to networkx.generators.
    * Added the chordal p-cycle graph, a mildly explicit algebraic construction of
      a family of 3-regular expander graphs. Also, moves both the existing
      expander graph generator function (for the Margulis-Gabber-Galil expander)
      and the new chordal cycle graph function to a new module,
      networkx.generators.expanders.
    * Allow overwriting of base class dict with dict-like: OrderedGraph, ThinGraph,
      LogGraph, etc.
    * Added to_pandas_dataframe and from_pandas_dataframe.
    * Added the Hopcroft--Karp algorithm for finding a maximum cardinality
      matching in bipartite graphs.
    * Expanded data keyword in G.edges and added default keyword.
    * Added support for finding optimum branchings and arborescences.
    * Added a from_pandas_dataframe function that accepts Pandas DataFrames
      and returns a new graph object. At a minimum, the DataFrame must have two
      columns, which define the nodes that make up an edge. However, the function
      can also process an arbitrary number of additional columns as edge
      attributes, such as 'weight'.
    * Expanded layout functions to add flexibility for drawing subsets of nodes
      with distinct layouts and for centering each layout around given coordinates.
    * Added ordered variants of default graph class.
    * Added harmonic centrality to network.algorithms.centrality.
    * The generators.bipartite have been moved to algorithms.bipartite.generators.
      The functions are not imported in the main namespace, so to use it,
      the bipartite package has to be imported.
    * Added Kanevsky's algorithm for finding all minimum-size separating node
      sets in an undirected graph. It is implemented as a generator of node
      cut sets.
    * Added power function for simple graphs
    * Added fast approximation for node connectivity based on White and Newman's
      approximation algorithm for finding node independent paths between two nodes.
    * Added transitive closure and antichains function for directed acyclic graphs
      in algorithms.dag. The antichains function was contributed by Peter Jipsen
      and Franco Saliola and originally developed for the SAGE project.
    * Added generator function for the complete multipartite graph.
    * Added nonisomorphic trees generator.
    * Added a generator function for circulant graphs to the
      networkx.generators.classic module.
    * Added function for computing quotient graphs; also created a new module,
      networkx.algorithms.minors.
    * Added longest_path and longest_path_length for DAG.
    * Added node and edge contraction functions to networkx.algorithms.minors.
    * Added a new modularity matrix module to networkx.linalg, and associated
      spectrum functions to the networkx.linalg.spectrum module.
    * Added function to generate all simple paths starting with the shortest ones
      based on Yen's algorithm for finding k shortest paths at
      algorithms.simple_paths.
    * Added the directed modularity matrix to the
      networkx.linalg.modularity_matrix module.
    * Adds triadic_census function; also creates a new module,
      networkx.algorithms.triads.
    * Adds functions for testing if a graph has weighted or negatively weighted
      edges. Also adds a function for testing if a graph is empty. These are
      is_weighted, is_negatively_weighted, and is_empty.
    * Added Johnson's algorithm; one more algorithm for shortest paths. It solves
      all pairs shortest path problem. This is johnson at
      algorithms.shortest_paths
    * Added Moody and White algorithm for identifying k_components in a graph,
      which is based on Kanevsky's algorithm for finding all minimum-size node
      cut-sets (implemented in all_node_cuts #1391).
    * Added fast approximation for k_components to the
      networkx.approximation package. This is based on White and Newman
      approximation algorithm for finding node independent paths between two
      nodes (see #1405).
    * The legacy ford_fulkerson maximum flow function is removed.
      Use edmonds_karp instead.
    * Support for Python 2.6 is dropped.
* Sat Jul 25 2015 seife+obs@b1-systems.com
  - fix rhel build by conditionalizing "Recommends:" tags
  - do not hardcode /usr/share/doc/packages but use %_docdir
* Wed Apr 29 2015 tbechtold@suse.com
  - Don't BuildRequires python-pygraphviz. It's not needed.
* Thu Oct 30 2014 tbechtold@suse.com
  - update to version 1.9.1:
    * Bugfix release for minor installation and documentation issues
  - Don't BuildRequire/Recommend matplotlib and scipy on SLE11
    and SLE12. Both are not available there.
* Fri Oct 24 2014 toddrme2178@gmail.com
  - Add python-decorator in requires to buildrequires

Files

/usr/lib/python3.6/site-packages/networkx
/usr/lib/python3.6/site-packages/networkx-2.4-py3.6.egg-info
/usr/lib/python3.6/site-packages/networkx-2.4-py3.6.egg-info/PKG-INFO
/usr/lib/python3.6/site-packages/networkx-2.4-py3.6.egg-info/SOURCES.txt
/usr/lib/python3.6/site-packages/networkx-2.4-py3.6.egg-info/dependency_links.txt
/usr/lib/python3.6/site-packages/networkx-2.4-py3.6.egg-info/not-zip-safe
/usr/lib/python3.6/site-packages/networkx-2.4-py3.6.egg-info/requires.txt
/usr/lib/python3.6/site-packages/networkx-2.4-py3.6.egg-info/top_level.txt
/usr/lib/python3.6/site-packages/networkx/__init__.py
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