Python implementation of binary tree algorithm example

This article brings you some examples of algorithms for implementing binary trees in Python. It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.

Node definition

class Node(object):
    def __init__(self, left_child, right_child, value):
        self._left_child = left_child
        self._right_child = right_child
        self._value = value

    @property
    def left_child(self):
        return self._left_child

    @property
    def right_child(self):
        return self._right_child

    @left_child.setter
    def left_child(self, value):
        self._left_child = value

    @right_child.setter
    def right_child(self, value):
        self._right_child = value

    @property
    def value(self):
        return self._value

    @value.setter
    def value(self, value):
        self._value = value

Binary tree definition

class Tree(object):
    def __init__(self, value):
        self._root = Node(None, None, value=value)

    @property
    def root(self):
        return self._root

Preorder traversal

Recursive method

'''
先序遍历，递归方式
'''
def preoder(root):
    if not isinstance(root, Node):
        return None
    preorder_res = []
    if root:
        preorder_res.append(root.value)
        preorder_res += preoder(root.left_child)
        preorder_res += preoder(root.right_child)

    return preorder_res

Non-recursive Method

'''
先序遍历，非递归方式
'''
def pre_order_not_recursion(root):
    if not isinstance(root, Node):
        return None

    stack = [root]
    result = []
    while stack:
        node = stack.pop(-1)
        if node:
            result.append(node.value)
            stack.append(node.right_child)
            stack.append(node.left_child)
    return result

In-order traversal

Recursive method

'''
中序遍历，递归方式
'''
def middle_order(root):
    if not isinstance(root, Node):
        return None
    middle_res = []
    if root:
        middle_res += middle_order(root.left_child)
        middle_res.append(root.value)
        middle_res += middle_order(root.right_child)
    return middle_res

Non-recursive method

'''
中序遍历，非递归方式
'''
def middle_order_bot_recursion(root):
    if not isinstance(root, Node):
        return None

    result = []
    stack = [root.right_child, root.value, root.left_child]
    while stack:
        temp = stack.pop(-1)
        if temp:
            if isinstance(temp, Node):
                stack.append(temp.right_child)
                stack.append(temp.value)
                stack.append(temp.left_child)
            else:
                result.append(temp)
    return result

Post-order traversal

Recursive method

'''
后序遍历，递归方式
'''
def post_order(root):
    if not isinstance(root, Node):
        return None
    post_res = []
    if root:
        post_res += post_order(root.left_child)
        post_res += post_order(root.right_child)
        post_res.append(root.value)
    return post_res

Non-recursive method

'''
后序遍历，非递归方式
'''
def post_order_not_recursion(root):
    if not isinstance(root, Node):
        return None

    stack = [root.value, root.right_child, root.left_child]
    result = []

    while stack:
        temp_node = stack.pop(-1)
        if temp_node:
            if isinstance(temp_node, Node):
                stack.append(temp_node.value)
                stack.append(temp_node.right_child)
                stack.append(temp_node.left_child)
            else:
                result.append(temp_node)

    return result

Hierarchical traversal

'''
分层遍历，使用队列实现
'''
def layer_order(root):
    if not isinstance(root, Node):
        return None

    queue = [root.value, root.left_child, root.right_child]
    result = []
    while queue:
        temp = queue.pop(0)
        if temp:
            if isinstance(temp, Node):
                queue.append(temp.value)
                queue.append(temp.left_child)
                queue.append(temp.right_child)
            else:
                result.append(temp)

    return result

Calculate the number of binary tree nodes

'''
计算二叉树结点个数，递归方式
NodeCount(root) = NodeCount(root.left_child) + NodeCount(root.right_child)
'''
def node_count(root):
    if root and not isinstance(root, Node):
        return None

    if root:
        return node_count(root.left_child) + node_count(root.right_child) + 1
    else:
        return 0


'''
计算二叉树结点个数，非递归方式
借用分层遍历计算
'''
def node_count_not_recursion(root):
    if root and not isinstance(root, Node):
        return None

    return len(layer_order(root))

Calculate the depth of the binary tree

'''
计算二叉树深度，递归方式
tree_deep(root) = 1 + max(tree_deep(root.left_child), tree_deep(root.right_child))
'''
def tree_deep(root):
    if root and not isinstance(root, Node):
        return None

    if root:
        return 1 + max(tree_deep(root.left_child), tree_deep(root.right_child))
    else:
        return 0

'''
计算二叉树深度，非递归方法
同理参考分层遍历的思想
'''
def tree_deep_not_recursion(root):
    if root and not isinstance(root, Node):
        return None
    result = 0
    queue = [(root, 1)]
    while queue:
        temp_node, temp_layer = queue.pop(0)
        if temp_node:
            queue.append((temp_node.left_child, temp_layer+1))
            queue.append((temp_node.right_child, temp_layer+1))
            result = temp_layer + 1

    return result-1

Calculate the number of binary tree nodes Number of k-layer nodes

'''
计算二叉树第k层节点个数，递归方式
kth_node_count(root, k) = kth_node_count(root.left_count, k-1) + kth_node_count(root.right_count, k-1)
'''
def kth_node_count(root, k):
    if root and not isinstance(root, Node):
        return None

    if not root or k  k:
                return result
            else:
                queue.append((temp_node.left_child, temp_layer+1))
                queue.append((temp_node.right_child, temp_layer+1))
    return result

Calculate the number of leaf nodes of a binary tree

'''
计算二叉树叶子节点个数，递归方式
关键点是叶子节点的判断标准，左右孩子皆为None
'''
def leaf_count(root):
    if root and not isinstance(root, Node):
        return None

    if not root:
        return 0
    if not root.left_child and not root.right_child:
        return 1

    return leaf_count(root.left_child) + leaf_count(root.right_child)

Judge whether two binary trees are the same

'''
判断两个二叉树是不是相同，递归方式
isSame(root1, root2) = (root1.value == root2.value)
                    and isSame(root1.left, root2.left) 
                    and isSame(root1.right, root2.right)
'''
def is_same_tree(root1, root2):
    if not root1 and not root2:
        return True

    if root1 and root2:
        return (root1.value == root2.value) and \
               is_same_tree(root1.left_child, root2.left_child) and \
               is_same_tree(root1.right_child, root2.right_child)
    else:
        return False

Judge whether they are binary search trees BST

'''
判断是否为二分查找树BST，递归方式
二分查找树的定义搞清楚，二分查找树的中序遍历结果为递增序列
'''
def is_bst_tree(root):
    if root and not isinstance(root, Node):
        return None

    def is_asc(order):
        for i in range(len(order)-1):
            if order[i] > order[i+1]:
                return False
        return True

    return is_asc(middle_order_bot_recursion(root))

Test method

if __name__ == "__main__":
    tree = Tree(1)
    tree1 = Tree(1)
    node6 = Node(None, None, 7)
    node5 = Node(None, None, 6)
    node4 = Node(None, None, 5)
    node3 = Node(None, None, 4)
    node2 = Node(node5, node6, 3)
    node1 = Node(node3, node4, 2)
    tree.root.left_child = node1
    tree.root.right_child = node2
    tree1.root.left_child = node2
    tree1.root.right_child = node2
    print(is_bst_tree(tree.root))

The above is the detailed content of Python implementation of binary tree algorithm example. For more information, please follow other related articles on the PHP Chinese website!