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        "description": "What Is Graphine?\r\n-----------------\r\n\r\nGraphine is a flexible, easy-to-use graph library for Python 3. It was developed\r\nwith four key goals in mind:\r\n\r\n1) No external dependencies- no graphics toolkits, no math libraries, just\r\npure Python.\r\n\r\n2) Python 3 readiness- if you\u2019re looking at moving your application to Python\r\n3, at least you won\u2019t have to port your graph library too.\r\n\r\n3) Flexibility- we aim to support many different graph use cases, from flow\r\nnetworks and planar graphs to tree walking and DAGs.\r\n\r\n4) Ease of use- no graph library, however powerful, is useful if you can\u2019t\r\nfigure it out. We try to make that as painless as possible.\r\n\r\nWho Should Use Graphine\r\n-----------------------\r\n\r\n1) Developers faced with a data set that naturally decomposes into a graph, but\r\nwho are unwilling to reinvent graph theory to properly represent it. We make it\r\neasy to inspect graphs for special properties, add data and structural elements,\r\nand extend graphs for application-specific behavior.\r\n\r\n2) Non-mathematicians who need to process complex data structures but aren\u2019t\r\nfamiliar with the formal methods for doing so in the graph context. Graphine\r\ndoesn\u2019t require a strong mathematical background to use, and is flexible enough\r\nto permit graph problems to be represented in their most natural form.\r\n\r\n3) Students and teachers looking for a clean, easy-to-understand example of\r\nhow graph algorithms are supposed to behave.\r\n\r\n4) Graph theorists looking for a tool to rapidly sketch out a complex problem\r\nwithout the hassle of manual memory management.\r\n\r\nFeatures\r\n--------\r\n\r\nGraphine is designed to be ready-to-use for most graph applications out of the\r\nbox. It supports easy node and edge addition, modification, and removal, and\r\nprovides attribute access to application-defined data. Formally, the graphs\r\nrepresented are bridge multigraphs, capable of representing both directed and\r\nundirected edges, parallel edges, identical nodes and edges, loops, and\r\narbitrary node and edge labels.\r\n\r\nIt also provides a powerful set of graph operations, including a* traversals,\r\nBFS, DFS, shortest path, edge contraction, generators for random walks, and\r\nbinary graph operations like union, intersection, and difference.\r\n\r\nAll of the above is present in the alpha package; experimental support for\r\nloading and storing graphs using GraphML and Dot is also included",
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        "keywords": "Python3 Graph Tree Math",
        "license": "GNU GPLv3",
        "maintainer": "Geremy Condra",
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