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