Python实现二叉树的定义、前序、中序、后序、层次遍历
2021/6/9 22:24:20
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定义二叉树类,实现二叉树的插入、查找和赋值:
#!/usr/bin/python3 # -*- coding: utf-8 -*- class BinaryTree: def __init__(self, root_obj): self.key = root_obj self.leftChild = None self.rightChild = None def insert_left(self, new_node): if self.leftChild is None: self.leftChild = BinaryTree(new_node) else: temp = BinaryTree(new_node) temp.leftChild = self.leftChild self.leftChild = temp def insert_right(self, new_node): if self.rightChild is None: self.rightChild = BinaryTree(new_node) else: temp = BinaryTree(new_node) temp.rightChild = self.rightChild self.rightChild = temp def get_right_node(self): return self.rightChild def get_left_node(self): return self.leftChild def set_root_val(self, obj): self.key = obj def get_root_val(self): return self.key # tree = BinaryTree('root') # print(tree.get_left_node()) # tree.insert_left('left001') # tree.insert_right('right001') # tree.get_left_node().insert_left('left002') # print(tree.get_left_node().get_left_node().get_root_val())
实现二叉树的前序、中序、后序递归与非递归遍历,实现二叉树的层次遍历:
#!/usr/bin/python3 # -*- coding: utf-8 -*- from Tree.BinaryTree import BinaryTree tree = BinaryTree('root') tree.insert_left('left001') tree.insert_right('right001') tree.get_left_node().insert_left('left-left-001') tree.get_left_node().insert_right('left-right-001') tree.get_right_node().insert_left('right-left-001') tree.get_right_node().insert_right('right-right-001') # 前序遍历(递归): 根-左-右 def pre_order_recursive(root_node): if not root_node: return print(root_node.key) pre_order_recursive(root_node.leftChild) pre_order_recursive(root_node.rightChild) # 前序遍历2(递归,带返回值) def pre_order_recursive2(root_node): res = [] def helper(root): if not root: return None res.append(root.key) helper(root.leftChild) helper(root.rightChild) helper(root_node) return res # 前序非递归遍历 def pre_order_non_recursive(root_node): stack = [root_node] while stack: print(root_node.key) if root_node.rightChild: stack.append(root_node.rightChild) if root_node.leftChild: stack.append(root_node.leftChild) root_node = stack.pop() # 前序非递归遍历(带返回值) def pre_order_non_recursive2(root_node): res = [] if not root_node: return res stack = [root_node] while stack: root_node = stack.pop() res.append(root_node.key) if root_node.rightChild: stack.append(root_node.rightChild) if root_node.leftChild: stack.append(root_node.leftChild) return res # 中序遍历(递归):左-根-右 def mid_order_recursive(root_node): if not root_node: return mid_order_recursive(root_node.leftChild) print(root_node.key) mid_order_recursive(root_node.rightChild) # 中序递归遍历,带返回值 def mid_order_recursive2(root_node): res = [] def helper(root): if not root: return helper(root.leftChild) res.append(root.key) helper(root.rightChild) helper(root_node) return res # 中序非递归遍历 def mid_order_non_recursive(root_node): stack = [] pos = root_node while pos or len(stack) > 0: if pos: stack.append(pos) pos = pos.leftChild else: pos = stack.pop() print(pos.key) pos = pos.rightChild # 中序非递归遍历,带返回值 def mid_order_non_recursive2(root_node): res = [] stack = [] pos = root_node while pos or len(stack) > 0: if pos: stack.append(pos) pos = pos.leftChild else: pos = stack.pop() res.append(pos.key) pos = pos.rightChild return res # 后续递归遍历:左-右-根 def post_order_recursive(root_node): if not root_node: return post_order_recursive(root_node.leftChild) post_order_recursive(root_node.rightChild) print(root_node.key) # 后续递归遍历,带返回值 def post_order_recursive2(root_node): res = [] def helper(root): if not root: return helper(root.leftChild) helper(root.rightChild) res.append(root.key) helper(root_node) return res # 后序非递归遍历 # 使用两个栈结构,第一个栈类似前序遍历进栈(注意左右子节点入栈顺序和前序遍历的差别); # 第一个栈是先放根,再放右子树,再放左子树,在入栈的同时,也把每次的根节点放入stack2 ; # 所以第二个栈stack2的入栈顺序是:根-右子树的根-右子树叶节点(先右后左)-左子树的根-左子树叶节点(先右后左); def post_order_non_recursive(root_node): stack = [root_node] stack2 = [] while len(stack) > 0: node = stack.pop() stack2.append(node) if node.leftChild: stack.append(node.leftChild) if node.rightChild: stack.append(node.rightChild) while len(stack2) > 0: print(stack2.pop().key) # 后序非递归遍历,带返回值 def post_order_non_recursive2(root_node): res = [] stack = [root_node] stack2 = [] while len(stack) > 0: node = stack.pop() stack2.append(node) if node.leftChild: stack.append(node.leftChild) if node.rightChild: stack.append(node.rightChild) while len(stack2) > 0: res.append(stack2.pop().key) return res # 层次遍历 def layer_traverse(root_node): if not root_node: return None queue = [root_node] # 因为是先进先出,所以用queue定义变量名更合适 while len(queue) > 0: node = queue.pop(0) print(node.key) if node.leftChild: queue.append(node.leftChild) if node.rightChild: queue.append(node.rightChild) # 层次遍历,带返回值 def layer_traverse2(root_node): res = [] if not root_node: return None queue = [root_node] while len(queue) > 0: node = queue.pop(0) res.append(node.key) if node.leftChild: queue.append(node.leftChild) if node.rightChild: queue.append(node.rightChild) return res print(layer_traverse2(tree))
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