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View Code? Open in Web Editor NEWCommon graph algorithms for python, works with arbitrary data structures.
Common graph algorithms for python, works with arbitrary data structures.
Common Graph Algorithms Library Library of graph algorithms which operate directly on python data structures. This library uses a novel API for representing graphs. Graph vertexes can be any hashable python value and the connectivity between vertexes is represented with a callback function. This callback is named the 'adjacent' function. The adjacent function has the following form: def adjacent(vertex): ''' This function returns all vertexes which the given vertex is connected to. ''' return iterable-of-neighboring-vertexes Contents: depth_first_traversal() A lazy depth first traversal depth_first_search() A depth first search iterative_deepening_depth_first_search() Searching infinite graphs a_star() Fast optimal pathfinding topological_sort() Dependency resolution. strongly_connected_components() Determines which areas of the graph can reach which other areas. In the future I would like to implement more algorithms: - Minimum Spanning Tree - Min-cut/Max-flow - Substructure Search Installation note: This package optionally uses numpy. Numpy is used by some unit tests. Numpy is used to calculate A-stars effective branching factor (EBF). If numpy is not available then EBF is not reported. Comments and feedback are welcome Send to David McDougall email: dam1784[at]rit.edu
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