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python-networkx_2.1-1_all.deb

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STEP 2: Install the package

      
sudo apt-get install python-networkx=2.1-1

  


        

      

            
tool to create, manipulate and study complex networks (Python2)


  
Full description:
  tool to create, manipulate and study complex networks (Python2)
 NetworkX is a Python-based package for the creation, manipulation, and
 study of the structure, dynamics, and functions of complex networks.
 .
 The structure of a graph or network is encoded in the edges (connections,
 links, ties, arcs, bonds) between nodes (vertices, sites, actors). If
 unqualified, by graph it's meant a simple undirected graph, i.e. no
 self-loops and no multiple edges are allowed. By a network it's usually
 meant a graph with weights (fields, properties) on nodes and/or edges.
 .
 The potential audience for NetworkX includes: mathematicians, physicists,
 biologists, computer scientists, social scientists.
 .
 This package contains the Python 2 version of NetworkX.



        
          

            
Checksums

            

  
    

      
        MD5
      
      
        72d54ad56f351fdac05bc4aac594f94f
      
    

    

      
        SHA1
      
      
        40c5d67be1885214b429f9962bb1fa077dec6227
      
    

    

      
        SHA256
      
      
        977e8c61c67939f1f7181069ca1d5329316ed88a3bbac144aabe446b1080edb3
      
    

    

      
        SHA512
      
      
        635897b306e1da66a98d96dc499f646f09ae177280581184c20a5841d43dedb267f04e20fff1225c472b9abb82754f14e9a0fdc39f12b5d65b6a5e22e09757c4
      
    

  



          

        




                

                  
Depends

                  
    
                    
  • python3-decorator (>= 4.1.0), python-decorator, python:any (<< 2.8), python:any (>= 2.7.5-5~)
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Suggests

                  
    
                    
  • python-networkx-doc
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Files

  
    
      
  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/tests/test_maxflow_large_graph.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/tests/test_gomory_hu.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/tests/netgen-2.gpickle.bz2
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/tests/gw1.gpickle.bz2
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/tests/gl1.gpickle.bz2
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/shortestaugmentingpath.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/preflowpush.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/networksimplex.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/mincost.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/maxflow.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/gomory_hu.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/edmondskarp.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/dinitz_alg.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/capacityscaling.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/boykovkolmogorov.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/flow/__init__.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/euler.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/efficiency.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/dominating.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/dominance.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/distance_regular.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/distance_measures.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/dag.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/cycles.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/cuts.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/covering.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/core.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/utils.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/tests/test_stoer_wagner.py
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  • /usr/lib/python2.7/dist-packages/networkx/algorithms/connectivity/tests/test_kcutsets.py
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Uploaded

  about 7 years ago




  

    
Package Size

    945 KB
  

    

      
Installed Size

      4.37 MB
    




          
          

  
Downloads

  

    

      
37

    

    
  




          

  
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Homepage

    
      https://networkx.github.io/