Leafy is a python graph library written in cython. This mix gives the speed of writing the library in c with the benefit of python bindings.
Leafy supports two types of graphs: Dense and Sparse. These are represented by the
classes leafy.graph.Graph and leafy.graph.SparseGraph.
To instantiate a graph object we need to know the number of nodes (verticies) in the graph, and if the graph is directed. Graphs defualt to undirected.
>>> from leafy.graph import Graph
>>> from pprint import pprint
>>> g = Graph(4)
>>> g.add_edge(0, 1)
>>> g.add_edge(2, 3)
>>> g.add_edge(2, 1)
>>> pprint(g.matrix)
[[1000001.0, 1.0, 1000001.0, 1000001.0],
[1.0, 1000001.0, 1.0, 1000001.0],
[1000001.0, 1.0, 1000001.0, 1.0],
[1000001.0, 1000001.0, 1.0, 1000001.0]]the same edges can be defined as a directed SparseGraph
>>> from leafy.graph import SparseGraph
>>> g = SparseGraph(4, True)
>>> g.add_edge(0, 1)
>>> g.add_edge(2, 3)
>>> g.add_edge(2, 1)
>>> g.list
[[1], [], [3, 1], []]Leafy can run Depth First Search (DFS) and Breadth First Search (BFS) on a graph and return the graph search properties.
To run a search we need to define the graph to search and the node to start from.
Before you can view the properties we must call .run().
>>> from leafy.search import DFS
>>> graph = small_graph(request.param)
>>> dfs = DFS(graph, 0)
>>> dfs.run()
>>> dfs.simple_path(12)
[0, 1, 2, 11, 12]
>>> dfs.bridges
[(1, 3), (3, 4), (3, 5), (2, 11), (11, 12)]For diagraphs leafy supports DFS which can be imported from leafy.digraph
>>> from leafy.digraph import DFS
>>> dag = small_dag()
>>> dfs = DFS(dag, 0)
>>> dfs.run()
>>> dfs.is_dag
True
>>> dfs.topological_order()
[0, 6, 2, 3, 5, 4, 9, 11, 12, 10, 1]For network shortest path leafy supports single source Dijkstra which can be imported from leafy.shortest_path
>>> from leafy.shortest_path import Dijkstra
>>> dag = small_network()
>>> dij = Dijkstra(dag, 0)
>>> dij.run()
>>> dij.path(3)
[3, 7, 2, 1, 0]