Python的图实现有很多别人已经写好的（比如我下面写的就是参考python-graph），可是不适合一个刚开始的学习的人，我就简化了一下，实现可深度优先和广度优先遍历。
#!/usr/bin/env python
#-*- coding:utf8 -*-
class Graph(object):
def __init__(self, *args, **kwargs):
self.node_neighbors = {}
self.visited = {}
def add_nodes(self, nodelist):
for node in nodelist:
self.add_node(node)
def add_node(self, node):
if not node in self.node_neighbors:
self.node_neighbors[node] = []
def add_edge(self, edge):
u, v = edge
if (v not in self.node_neighbors[u]) and (u not in self.node_neighbors[v]):
self.node_neighbors[u].append(v)
if (u != v):
self.node_neighbors[v].append(u)
def nodes(self):
return self.node_neighbors.keys()
def depth_first_search(self, root=None):
order = []
def dfs(node):
self.visited[node] = True
order.append(node)
for n in self.node_neighbors[node]:
if not n in self.visited:
dfs(n)
if root:
dfs(root)
for node in self.nodes():
if not node in self.visited:
dfs(node)
print order
return order
def breadth_first_search(self, root=None):
queue = []
order = []
def bfs():
while len(queue) > 0:
node = queue.pop(0)
self.visited[node] = True
for n in self.node_neighbors[node]:
if (not n in self.visited) and (not n in queue):
queue.append(n)
order.append(n)
if root:
queue.append(root)
order.append(root)
bfs()
for node in self.nodes():
if not node in self.visited:
queue.append(node)
order.append(node)
bfs()
print order
return order
if __name__ == ‘__main__’:
g = Graph()
g.add_nodes([i+1 for i in range(8)])
g.add_edge((1, 2))
g.add_edge((1, 3))
g.add_edge((2, 4))
g.add_edge((2, 5))
g.add_edge((4, 8))
g.add_edge((5, 8))
g.add_edge((3, 6))
g.add_edge((3, 7))
g.add_edge((6, 7))
print “nodes:”, g.nodes()
order = g.depth_first_search(1)
order = g.breadth_first_search(1)
深度优先、广度优先实现比较简单，其他的有权图的关键路径、最短路径等下次实现
