PYTHON实现二叉树的层次遍历，先序遍历，中序遍历，后序遍历

介绍：

树是数据结构中非常重要的一种，主要的用途是用来提高查找效率，对于要重复查找的情况效果更佳，如二叉排序树、FP-树。另外可以用来提高编码效率，如哈弗曼树。

代码：

class Node(object):
    """节点类"""
    def __init__(self, elem):
        self.elem = elem
        self.lchild = None
        self.rchild = None


class Tree(object):
    """树类"""
    def __init__(self):
        self.root = None

    def add(self, elem):
        """为树添加节点"""
        node = Node(elem)
        if self.root is None:
            self.root = node
            return
        queue = [self.root]
        '''队列来存储节点'''
        while queue:
            cur_node = queue.pop(0)
            '''层次遍历，找到插入节点的位置'''
            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)

    '''广度遍历'''
    def breadth_travel(self):
        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)
    '''先序遍历'''
    def preorder(self,node):
        if node is None:
            return
        print(node.elem,end=' ')
        self.preorder(node.lchild)
        self.preorder(node.rchild)

    '''中序遍历'''
    def inorder(self,node):
        if node is None:
             return
        self.inorder(node.lchild)
        print(node.elem,end=' ')
        self.inorder(node.rchild)

    '''后序遍历'''
    def postorder(self, node):
        if node is None:
            return
        self.postorder(node.lchild)
        self.postorder(node.rchild)
        print(node.elem,end=' ')

tree = Tree()
for i in range(10):
    tree.add(i)
print("层次遍历：")
tree.breadth_travel()
print()
print("先序遍历：")
tree.preorder(tree.root)
print()
print("中序遍历：")
tree.inorder(tree.root)
print()
print("后序遍历：")
tree.postorder(tree.root)

运行结果：