树的实现采用queue的形式：
树的三种遍历方式（广度优先白能力法）：先序遍历（根左右），中序遍历（左根右）以及后序遍历（左右根）
######################P6.4 数据结构##################
class Node(object):
def __init__(self, item):
self.elem = item
self.lchild = None
self.rchild = None
class Tree(object):
def __init__(self):
self.root = None
"""树添加子节点"""
def add(self, item):
node = Node(item)
if self.root is None:
self.root = node
return
else:
queue = [self.root]
while queue:
cur_node = queue.pop(0)
if cur_node.lchild is None:
cur_node.lchild = node
return
else:
queue.append(cur_node.lchild)
if cur_node.rchild is None:
cur_node.rchild = node
return
else:
queue.append(cur_node.rchild)
def breadth_travel(self):
"""广度遍历，又称层次遍历"""
if self.root is None:
return
queue = [self.root]
while queue:
cur_node = queue.pop(0)
print(cur_node.elem, end=" ")
if cur_node.lchild is not None:
queue.append(cur_node.lchild)
if cur_node.rchild is not None:
queue.append(cur_node.rchild)
######################P6.5 数据结构##################
"""先序遍历：中左右 中序遍历：左中右 后序遍历：左右中"""
def preorder(self, node):
#先序遍历：中左右
if node is None:
return
print(node.elem, end=" ") #打印根节点元素
self.preorder(node.lchild) #处理左子树
self.preorder(node.rchild)
def mideorder(self, node):
#中序遍历：中左右
if node is None:
return
self.mideorder(node.lchild) #处理左子树
print(node.elem, end=" ") # 打印根节点元素
self.mideorder(node.rchild)
def posorder(self, node):
#后序遍历：中左右
if node is None:
return
self.posorder(node.lchild) #处理左子树
self.posorder(node.rchild)
print(node.elem, end=" ") # 打印根节点元素
if __name__ == "__main__":
tree = Tree()
tree.add(0)
tree.add(1)
tree.add(2)
tree.add(3)
tree.add(4)
tree.add(5)
tree.add(6)
tree.add(7)
tree.add(8)
tree.add(9)
tree.breadth_travel()
print(" ")
tree.preorder(tree.root)
print(" ")
tree.mideorder(tree.root)
print(" ")
tree.posorder(tree.root)
print(" ")
运行结果：依次为 原来的顺序 先序遍历 中序遍历 与后续遍历
