python-networkx

Edit Package python-networkx

%description
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
* Easy 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.
* Open source (encourages community input)
* Unit-tested

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Source Files
Filename Size Changed
networkx-2.8.8.tar.gz 0001960828 1.87 MB
python-networkx.changes 0000046489 45.4 KB
python-networkx.spec 0000004426 4.32 KB
Revision 34 (latest revision is 37)
Dominique Leuenberger's avatar Dominique Leuenberger (dimstar_suse) accepted request 1056126 from Dirk Mueller's avatar Dirk Mueller (dirkmueller) (revision 34)
- update to 2.8.8:
  * Fix warnings from running tests in randomized order 
  * Update pydata-sphinx-theme 
  * update secutiry link to tidelift 
  * Update numpydoc 
  * Support Python 3.11 
  * Minor updates to expanders generator tests 
  * Add missing asserts to tests 
  * fixes #6036 
  * Improve test coverage expanders line graph generators solved (PR for issue #6034) 
  * Replace .A call with .toarray for sparse array in example. 
  * Improve test coverage for algorithms/richclub.py 
  * Tested boykov_kolmogorov and dinitz with cutoff 
  * Improve test coverage for multigraph class 
  * Improve test coverage for algorithms in dominating_set.py (PR for issue 6032) 
  * Improve test coverage for graph class 
  * added coverage in generators/tree.py 
  * DOC: Specifically branch off main, instead of current branch 
  * Improve test coverage for multidigraph class 
  * Improve test coverage for digraph class 
  * Improve test coverage for algorithms in dispersion.py 
  * Test on Python 3.11 
  * Improve test coverage in algorithms shortest paths unweighted.py 
  * Increased test coverage algorithms/matching.py 
  * Renamed test functions in test_lowest_common_ancestors 
  * Increase covering coverage 
  * Add example for fiedler_vector 
  * Improve test coverage for cycles.py 
  * Added an example in all_pairs_node_connectivity  
  * Amount of nodes and edges have mistakes when reading adjlist file
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