# NetworkZ
NetworkZ is a library of graph algorithms in Python. It is an extension of the [NetworkX](https://github.com/networkx/networkx). It contains (by import) everything that is in NetworkX, plus some additional algorithms that were submitted into NetworkX but not merged yet. Currently, NetworkZ contains the following additional algorithms:
* [Rank-maximal matching](networkz/algorithms/bipartite/rank_maximal_matching.py): by Oriya Alperin, Liel Vaknin and Amiel Lejzor.
* [Social-aware coalition formation](networkz/algorithms/approximation/coalition_formation.py) - by Victor Kushnir.
## Installation
```
pip install networkz
```
This installs the latest version of networkx, and the new algorithms added in networkz.
## Usage
### Rank Maximal Matching Algorithm
A rank-maximal matching is a matching that maximizes the number of agents who are matched to their 1st priority; subject to that, it maximizes the number of agents matched to their 2nd priority; and so on.
```
import networkz as nx
G = nx.Graph()
G.add_nodes_from(["agent1", "agent2"], bipartite=0)
G.add_nodes_from(["product1", "product2"], bipartite=1)
G.add_weighted_edges_from([("agent1", "product1", 1), ("agent1", "product2", 1), ("agent2", "product2", 2)])
matching = nx.rank_maximal_matching(G, rank="weight")
print(matching)
```
See [demo website](https://rmm.csariel.xyz/) for more information.
### Social-aware coalition formation
(TODO)
## Contribution
Any additions or bug-fixes to `networkx` should first be submitted there, according to the [NetworkX Contributor Guide](https://github.com/networkx/networkx/blob/main/CONTRIBUTING.rst).
If the pull-request is not handled, you are welcome to submit it here too.
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"description": "# NetworkZ\n\nNetworkZ is a library of graph algorithms in Python. It is an extension of the [NetworkX](https://github.com/networkx/networkx). It contains (by import) everything that is in NetworkX, plus some additional algorithms that were submitted into NetworkX but not merged yet. Currently, NetworkZ contains the following additional algorithms:\n\n* [Rank-maximal matching](networkz/algorithms/bipartite/rank_maximal_matching.py): by Oriya Alperin, Liel Vaknin and Amiel Lejzor.\n* [Social-aware coalition formation](networkz/algorithms/approximation/coalition_formation.py) - by Victor Kushnir.\n\n## Installation\n\n```\npip install networkz\n```\n\nThis installs the latest version of networkx, and the new algorithms added in networkz.\n\n\n## Usage\n\n### Rank Maximal Matching Algorithm\nA rank-maximal matching is a matching that maximizes the number of agents who are matched to their 1st priority; subject to that, it maximizes the number of agents matched to their 2nd priority; and so on.\n\n```\nimport networkz as nx\nG = nx.Graph()\nG.add_nodes_from([\"agent1\", \"agent2\"], bipartite=0)\nG.add_nodes_from([\"product1\", \"product2\"], bipartite=1)\nG.add_weighted_edges_from([(\"agent1\", \"product1\", 1), (\"agent1\", \"product2\", 1), (\"agent2\", \"product2\", 2)])\nmatching = nx.rank_maximal_matching(G, rank=\"weight\")\nprint(matching)\n```\n\nSee [demo website](https://rmm.csariel.xyz/) for more information.\n\n### Social-aware coalition formation\n\n(TODO)\n\n\n## Contribution\n\nAny additions or bug-fixes to `networkx` should first be submitted there, according to the [NetworkX Contributor Guide](https://github.com/networkx/networkx/blob/main/CONTRIBUTING.rst).\n\nIf the pull-request is not handled, you are welcome to submit it here too.\n\n\n\n\n\n",
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