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  • Leetcode总结之Tree

    package Tree;
    
    import java.util.ArrayList;
    import java.util.Arrays;
    import java.util.Collections;
    import java.util.Deque;
    import java.util.LinkedList;
    import java.util.List;
    import java.util.Queue;
    import java.util.Stack;
    class ListNode {
        int val;
        ListNode next;
    
        ListNode(int x) {
            val = x;
        }
    }
    class TreeLinkNode {
        int val;
        TreeLinkNode left, right, next;
    
        TreeLinkNode(int x) {
            val = x;
        }
    }
    class TreeNode {
        public int val;
        public TreeNode left;
        public TreeNode right;
        public TreeNode(int x) {
            val = x;
        }
    }
    public class TreeProblems {
        public static void main(String[] args) {
            // TODO Auto-generated method stub
            TreeLinkNode a1 = new TreeLinkNode(1);
            TreeLinkNode a2 = new TreeLinkNode(2);
            TreeLinkNode a3 = new TreeLinkNode(3);
            TreeLinkNode a4 = new TreeLinkNode(4);
            TreeLinkNode a5 = new TreeLinkNode(5);
            TreeLinkNode a6 = new TreeLinkNode(6);
            TreeLinkNode a7 = new TreeLinkNode(7);
            a1.left = a2;
            a1.right = a3;
            a2.left = a4;
            a2.right = a5;
            a3.left = a6;
            a3.right = a7;
            System.out.println(a5.next.val);
            TreeNode aaa1 = new TreeNode(4);
            TreeNode aaa2 = new TreeNode(1);
            TreeNode aaa3 = new TreeNode(2);
            TreeNode aaa4 = new TreeNode(3);
            aaa1.left = aaa2;
            aaa2.left = aaa3;
            aaa3.left = aaa4;
            /*
             * 9 5 13 1 7 10
             */
            TreeNode aa1 = new TreeNode(5);
            TreeNode aa2 = new TreeNode(4);
            TreeNode aa3 = new TreeNode(8);
            TreeNode aa4 = new TreeNode(11);
            TreeNode aa5 = new TreeNode(13);
            TreeNode aa6 = new TreeNode(4);
            TreeNode aa7 = new TreeNode(7);
            TreeNode aa8 = new TreeNode(2);
            TreeNode aa9 = new TreeNode(1);
            aa1.left = aa2;
            aa1.right = aa3;
            aa2.left = aa4;
            aa3.left = aa5;
            aa3.right = aa6;
            aa4.left = aa7;
            aa4.right = aa8;
            aa6.right = aa9;
        }
    /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
    //树的问题很多都是dfs的问题,首先要学会preorder,inorder,postorder三种dfs算法的两种实现方式。
    /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
        /*
         * 94. Binary Tree Inorder Traversal 
         * 2015.11.21 By Mingyang
         * 跟preorder一样的dfs,不过是每次pop出来的时候记在小本本上,也就是记在list里面 中序遍历迭代解法
         * 用栈先把根节点的所有左孩子都添加到栈内, 然后输出栈顶元素,再处理栈顶元素的右子树
         */
        public List<Integer> inorderTraversal(TreeNode root) {
            List<Integer> list = new ArrayList<Integer>();
            if (root == null)
                return list;
            Stack<TreeNode> stack = new Stack<TreeNode>();
            TreeNode p = root;
            while (!stack.isEmpty() || p != null) {
                if (p != null) {
                    stack.push(p);
                    p = p.left;
                } else {
                    TreeNode t = stack.pop();
                    list.add(t.val);
                    p = t.right;
                }
            }
            return list;
        }
        public List<Integer> inorderTraversal1(TreeNode root) {
            List<Integer> res = new ArrayList<Integer>();
            dfs(root, res);
            return res;
        }
        public void dfs(TreeNode root, List<Integer> res) {
            if (root == null)
                return;
            dfs(root.left, res);
            res.add(root.val);
            dfs(root.right, res);
        }
        /*
         * 144. Binary Tree Preorder Traversal 
         * 2015.11.21 By Mingyang
         * 典型的dfs的做法,每次push进去一个值的时候就记在小本本上,其实也就是记在list里面
         */
        public List<Integer> preorderTraversal(TreeNode root) {
            List<Integer> list = new ArrayList<Integer>();
            if (root == null)
                return list;
            Stack<TreeNode> stack = new Stack<TreeNode>();
            TreeNode p = root;
            while (!stack.isEmpty() || p != null) {
                if (p != null) {
                    stack.push(p);
                    list.add(p.val);
                    p = p.left;
                } else {
                    TreeNode t = stack.pop();
                    p = t.right;
                }
            }
            return list;
        }
        public List<Integer> preorderTraversal1(TreeNode root) {
            List<Integer> res=new ArrayList<Integer>();
            dfs(res,root);
            return res;
        }
        public void dfs(List<Integer> res,TreeNode root){
            if(root==null)
              return;
            res.add(root.val);
            dfs(res,root.left);
            dfs(res,root.right);
        }
        /*
         * 145. Binary Tree Postorder Traversal 
         * 2015.11.21 by Mingyang
         * 左右中,反过来就是中左右,所以就相当于inorder反过来,稍稍改进一下就好
         */
        public List<Integer> postorderTraversal(TreeNode root) {
            List<Integer> list = new ArrayList<Integer>();
            if (root == null)
                return list;
            Stack<TreeNode> stack = new Stack<TreeNode>();
            TreeNode p = root;
            while (!stack.isEmpty() || p != null) {
                if (p != null) {
                    stack.push(p);
                    list.add(p.val);
                    p = p.right;
                } else {
                    TreeNode t = stack.pop();
                    p = t.left;
                }
            }
            Collections.reverse(list);
            return list;
        }
        public List<Integer> postorderTraversal1(TreeNode root) {
            List<Integer> res=new ArrayList<Integer>();
            dfs(root,res);
            return res;
        }
        public void dfs1(TreeNode root,List<Integer> res){
            if(root==null)
             return;
            dfs1(root.left,res);
            dfs1(root.right,res);
            res.add(root.val);
        }
        /*
         * 95. Unique Binary Search Trees II
         * 2015.11.23 By Mingyang
         * 分成两个函数来写,另外一个函数写满起点到终点
         */
        public List<TreeNode> generateTrees(int n) {
            return generateTrees(1, n);
        }
        public List<TreeNode> generateTrees(int start, int end) {
            List<TreeNode> list = new LinkedList<TreeNode>();
            if (start > end) {
                list.add(null);
                return list;
            }
            for (int i = start; i <= end; i++) {
                List<TreeNode> lefts = generateTrees(start, i - 1);//以i作为根节点,左子树由[1,i-1]构成
                List<TreeNode> rights = generateTrees(i + 1, end);//右子树由[i+1, n]构成
                for (TreeNode left : lefts) {//左边和右边分别返回了一个list,每个值就是一个TreeNode,就代表一种可能性
                    for (TreeNode right : rights) {
                        TreeNode node = new TreeNode(i);
                        node.left = left;
                        node.right = right;
                        list.add(node);//存储所有可能行
                    }
                }
            }
            return list;
        }
        /*
         * 145. Binary Tree Postorder Traversal
         * 上面的变体,给你一个preorder的array,看看是不是BST的preorder 
         * 2015.1.24 by Mingyang
         */
        public static boolean canRepresentBST(int pre[], int n) {
            // Create an empty stack
            Stack<Integer> s = new Stack<Integer>();
            // Initialize current root as minimum possible
            // value
            int root = Integer.MIN_VALUE;
            // Traverse given array
            for (int i = 0; i < n; i++) {
                // If we find a node who is on right side
                // and smaller than root, return false
                if (pre[i] < root) {
                    return false;
                }
                // If pre[i] is in right subtree of stack top,
                // Keep removing items smaller than pre[i]
                // and make the last removed item as new
                // root.
                while (!s.empty() && s.peek() < pre[i]) {
                    root = s.peek();
                    s.pop();
                }
                // At this point either stack is empty or
                // pre[i] is smaller than root, push pre[i]
                s.push(pre[i]);
            }
            return true;
        }
        /*
         * 156.Binary Tree Upside Down
         * 2016-3-26 by Mingyang
         * For example:
         *Given a binary tree {1,2,3,4,5},
            1
           / 
          2 3
         / 
        4   5
        *return the root of the binary tree [4,5,2,#,#,3,1].
            4
           / 
          5   2
         / 
        3   1
        *先去处理最左下角的分支,因为他就是未来的root,然后再一层一层的上来
         */
        public TreeNode UpsideDownBinaryTree(TreeNode root) {  
            if (root == null)  
                return null;  
            TreeNode parent = root, left = root.left, right = root.right;  
            if (left != null) {  
                TreeNode ret = UpsideDownBinaryTree(left);  
                left.left = right;  
                left.right = parent;  
                return ret;  
            }  
            return root;  
        } 
        /*
         * 272.Closest Binary Search Tree Value II 
         * 2016-3-27 By Mingyang
         * 二叉搜索树的中序遍历就是顺序输出二叉搜索树,所以我们只要中序遍历二叉搜索树,同时维护一个大小为K的队列,
         * 前K个数直接加入队列,之后每来一个新的数(较大的数),如果该数和目标的差,相比于队头的数离目标的差来说,
         * 更小,则将队头拿出来,将新数加入队列。如果该数的差更大,则直接退出并返回这个队列,因为后面的数更大,差值也只会更大。
         * @return true if result is already found.
         */
        public List<Integer> closestKValues(TreeNode root, double target, int k) {
            LinkedList<Integer> list = new LinkedList<Integer>();
            closestKValuesHelper(list, root, target, k);
            return list;
        }
        private boolean closestKValuesHelper(LinkedList<Integer> list,TreeNode root, double target, int k) {
            if (root == null) {
                return false;
            }
            if (closestKValuesHelper(list, root.left, target, k)) {
                return true;
            }
            if (list.size() == k) {
                if (Math.abs(list.getFirst() - target) < Math.abs(root.val - target)) {
                    return true;
                } else {
                    list.removeFirst();
                }
            }
            list.addLast(root.val);
            return closestKValuesHelper(list, root.right, target, k);
        }
        /*
         *     270    Closest Binary Search Tree Value 
         * Given a non-empty binary search tree and a target value, find the value in the BST that is closest to the target.
         *  2016-3-26 by Mingyang
         *  其实很简单,就是在dfs的过程中不断的缩小范围,没到一个点就开始去update最小的距离
         */
        public int closestValue3(TreeNode root, double target) {
            int closest = root.val;
            while (root != null) {
                // 如果该节点的离目标更近,则更新到目前为止的最近值
                closest = Math.abs(closest - target) < Math.abs(root.val - target) ? closest: root.val;
                // 二叉搜索
                root = target < root.val ? root.left : root.right;
            }
            return closest;
        }
        /*
         * 265.Count Univalue Subtrees 
         * 2016-3-26 by Mingyang
         * Given a binary tree, count the number of uni-value subtrees.
         * A Uni-value subtree means all nodes of the subtree have the same value.
         * 这里是自底向上的模式,
         */
        private int count = 0;
        public int countUnivalSubtrees(TreeNode root) {
            unival(root);
            return count;
        }
        private boolean unival(TreeNode root) {
            if (root == null)
                return true;
            if (root.left == null && root.right == null) {
                count++;
                return true;
            }
            boolean left = unival(root.left);//自底向上第一步,走到最底的那一层
            boolean right = unival(root.right);
            if (left && right && (root.left == null || root.left.val == root.val)&& (root.right == null || root.right.val == root.val)) {
                count++;
                return true;
            }
            return false;
        }
        /*
         * 285.Inorder Successor in BST 
         * 11.21 By Mingyang
         * Case1: Node has right subtree: Go deep to leftmost node in right subtree or find min in right subtree
         * Case2:No right subtree:1.go back to parent from left, parent is successor,and parent is unvisited
         * 2.from right, parent already visited, we need on more further
         * ---Go to the nearest ancestor for which given node would be in left subtree
         */
         public TreeNode inorderSuccessor(TreeNode root, TreeNode p) {
                Stack<TreeNode> stk = new Stack<TreeNode>();
                TreeNode curr = root;
                // 找到目标节点并把路径上的节点压入栈,也就是首先找到这个节点,大概时间是logn
                while(curr != p){
                    stk.push(curr);
                    if(curr.val > p.val){
                        curr = curr.left;
                    } else {
                        curr = curr.right;
                    }
                }
                // 如果目标节点有右节点,则找到其右节点的最左边的节点,就是下一个数
                if(curr.right != null){
                    curr = curr.right;
                    while(curr.left != null){
                        curr = curr.left;
                    }
                    return curr;
                } else {
                // 如果没有右节点,pop栈找到第一个比目标节点大的节点。因为如果目标没有右节点,那么就看他从左边还是右边回到父亲,如果从左边回到父亲,父亲就是下一个
                //如果不是,go to the nearest ancestor for which given node would be in left subtree
                    while(!stk.isEmpty() && stk.peek().val < curr.val){
                        stk.pop();
                    }
                    // 如果栈都pop空了还没有比目标节点大的,说明没有更大的了
                    return stk.isEmpty() ? null : stk.pop();
                }
            }
        /*
         * 255.Verify Preorder Sequence in Binary Search Tree 
         * Given an array of numbers,
         * verify whether it is the correct preorder traversal sequence of a binary
         * search tree. 
         * 11.21 By Mingyang
         * Time complexity O(n^2), space complexity O(1). 
         */
          public boolean verifyPreorder(int[] preorder) {
                if (preorder == null || preorder.length <= 1) {
                    return true;
                }         
                return dfs(preorder, 0, preorder.length - 1);
            }     
            private boolean dfs(int[] preorder, int low, int hi) {
                if (low >= hi) {
                    return true;
                }      
                int root = preorder[low];
                int i = low + 1;
                while (i <= hi && preorder[i] < root) {
                    i++;
                }         
                int j = i;
                while (j <= hi && preorder[j] > root) {
                    j++;
                }        
                if (j <= hi) {
                    return false;
                }        
                return dfs(preorder, low + 1, i - 1) && dfs(preorder, i, hi);
            }
        /*
         * 103. Binary Tree Zigzag Level Order Traversal 
         * 11.21 By Mingyang
         */
        public static ArrayList<ArrayList<Integer>> zigzagLevelOrder2(TreeNode root) {
            ArrayList<ArrayList<Integer>> res = new ArrayList<ArrayList<Integer>>();
            if (root == null)
                return res;
            LinkedList<TreeNode> queue = new LinkedList<TreeNode>();
            queue.add(root);
            int num = 0;
            boolean reverse = false;// a flag
            while (!queue.isEmpty()) {
                num = queue.size();
                ArrayList<Integer> levelres = new ArrayList<Integer>();
                for (int i = 0; i < num; i++) {
                    TreeNode node = queue.poll();
                    levelres.add(node.val);
                    if (node.left != null)
                        queue.add(node.left);
                    if (node.right != null)
                        queue.add(node.right);
                }
                if (reverse) {
                    Collections.reverse(levelres);
                    reverse = false;
                } else {
                    reverse = true;
                }
                res.add(levelres);
            }
            return res;
        }
        /*
         * 107. Binary Tree Level Order Traversal II 11.21 By Mingyang I的解答加一行:
         * Collections.reverse(results);就好了
         */
        /*
         * 102. Binary Tree Level Order Traversal 
         * 11.21 by Mingyang 最基本的queue的做法
         */
        public List<List<Integer>> levelOrder(TreeNode root) {
            List<List<Integer>> results = new ArrayList<List<Integer>>();
            ArrayList<Integer> result = new ArrayList<Integer>();
            if (root == null)
                return results;
            LinkedList<TreeNode> queue = new LinkedList<TreeNode>();
            queue.add(root);
            int currentNumber = 1;
            int nextNumber = 0;
            while (queue.size() != 0) {
                TreeNode temp = queue.poll();
                result.add(temp.val);
                currentNumber--;
                if (temp.left != null) {
                    queue.add(temp.left);
                    nextNumber++;
                }
                if (temp.right != null) {
                    queue.add(temp.right);
                    nextNumber++;
                }
                if (currentNumber == 0) {
                    results.add(result);
                    currentNumber = nextNumber;
                    nextNumber = 0;
                    result = new ArrayList<Integer>();
                }
            }
            return results;
        }
        /*
         * 222.Count Complete Tree Nodes 
         * 11.20 By Mingyang
         * 最先各自计算最左边那一束到底的长度,再计算右边到底的长度,如果相等,ok,# of nodes = 2^h -1(计算满树很简单的!)
         * 若不相等,再继续迭代,这样做节省了很多时间
         * T(n)=logn+2T(n/2),最后算出来就是n,其实可以这么理解,每个节点都只是访问了一次,所以还是n。注意树的高度是logn
         */
        public int countNodes(TreeNode root) {
            if (root == null)
                return 0;
            int leftHeight = 1, rightHeight = 1;
            // 计算左子树
            TreeNode temp = root.left;
            while (temp != null) {
                temp = temp.left;
                leftHeight++;
            }
            // 计算右子树
            temp = root.right;
            while (temp != null) {
                temp = temp.right;
                rightHeight++;
            }
            if (leftHeight == rightHeight)
                return (1 << leftHeight) - 1;
            // 也可以:(2<<(left-1))-1,这里h是left-1
            return countNodes(root.left) + countNodes(root.right) + 1;
        }
        /*
         * 226. Invert Binary Tree 
         * 11.19 By Mingyang
         */
         public TreeNode invertTree(TreeNode root){
                exchange(root);
                return root;
            }
            public void exchange(TreeNode root) {
               if(root==null)
                 return;
               if(root.left==null&&root.right==null)
                 return;
               TreeNode Temp=root.left;
               root.left=root.right;
               root.right=Temp;
               exchange(root.left);
               exchange(root.right);
            }
        /*
         * 230.Kth Smallest Element in a BST 
         * 11.19 By Mingyang
         */
        private static int number = 0;
        private static int county = 0;
        public int kthSmallest1(TreeNode root, int k) {
            county = k;
            dfs(root);
            return number;
        }
        public void dfs(TreeNode root) {
            if (root == null)
                return;
            dfs(root.left);
            county--;
            if (county == 0) {
                number = root.val;
                return;
            }
            dfs(root.right);
        }
        public int kthSmallest(TreeNode root, int k) {
            Stack<TreeNode> stack = new Stack<TreeNode>();
            TreeNode p = root;
            int result = 0;
            // 不断的dfs,利用左中右的遍历方式进行遍历,然后依次取到最后的值
            while (!stack.isEmpty() || p != null) {
                if (p != null) {
                    stack.push(p);
                    p = p.left;
                } else {
                    TreeNode t = stack.pop();
                    k--;
                    if (k == 0)
                        result = t.val;
                    p = t.right;
                }
            }
            return result;
        }
        // 我的方法更快,利用左子树和右字数的个数的关系,如果k大于左子树的个数,那么就可以往右边走,这种方法复杂度T(n)=2T(n/2)+logn,也就是n
        //这里用了Binary Search的方法,根据count的大小来判断在哪个区间,然后去那个区间search,所以按理来说应该是logn,可是因为count用了n,所以总的时间就是n,哈哈!
        public int kthSmallest2(TreeNode root, int k) {
            int count = countNodes2(root.left);
            if (k <= count) {
                return kthSmallest2(root.left, k);
            } else if (k > count + 1) {
                return kthSmallest2(root.right, k-1-count); // 1 is counted as current node
            }
            return root.val;
        }
        public int countNodes2(TreeNode n) {
            if (n == null) return 0;
    
            return 1 + countNodes2(n.left) + countNodes2(n.right);
        }
        /*
         * 235. Lowest Common Ancestor of a Binary Search Tree 
         * 11.19 By Mingyang
         * 这题目更简单,下面两种方法都适用,现在给出更直接的方法
         */
        public TreeNode lowestCommonAncestor3(TreeNode root, TreeNode p, TreeNode q) {
            if (p.val == root.val || q.val == root.val)
                return root;
            if ((p.val < root.val && q.val > root.val)|| (p.val > root.val && q.val < root.val))
                return root;
            if (p.val < root.val) {
                return lowestCommonAncestor(root.left, p, q);
            } else {
                return lowestCommonAncestor(root.right, p, q);
            }
        }
        /*
         * 236. Lowest Common Ancestor of a Binary Tree 
         * 11.19 By Mingyang
         * 这道题目比BST更难,不过这道题目的答案可以通用的
         */
        public TreeNode lowestCommonAncestor(TreeNode root, TreeNode p, TreeNode q) {
            // 发现目标节点则通过返回值标记该子树发现了某个目标结点
            if (root == null || root == p || root == q)
                return root;
            // 查看左子树中是否有目标结点,没有为null
            TreeNode left = lowestCommonAncestor(root.left, p, q);
            // 查看右子树是否有目标节点,没有为null
            TreeNode right = lowestCommonAncestor(root.right, p, q);
            // 都不为空,说明做右子树都有目标结点,则公共祖先就是本身
            if (left != null && right != null)
                return root;
            // 如果发现了目标节点,则继续向上标记为该目标节点
            return left == null ? right : left;
        }
        /*
         * 298 Binary Tree Longest Consecutive Sequence
         *  2016-3-27 by Mingyang
         *  The path refers to any sequence of nodes from some starting node to any node in the tree along the parent-child connections. 
         *  The longest consecutive path need to be from parent to child (cannot be the reverse).
         */
        private int result = Integer.MIN_VALUE;
        public int longestConsecutive(TreeNode root) {
            if(root == null)
                return 0;
            dfs(root, 0, root);
            return result;
        }
        private void dfs(TreeNode root, int cur, TreeNode pre) {
            if(root == null)
                return;
            if(root.val == pre.val+1)
                cur++;
            else
                cur = 1;
            result = Math.max(result, cur);
            dfs(root.left, cur, root);
            dfs(root.right, cur, root);
        }
        /*
         * 333.Largest BST Subtree
         * 2016-3-27 by Mingyang
         * Given a binary tree, find the largest subtree which is a Binary Search Tree (BST)
         * where largest means subtree with largest number of nodes in it.
         * why not traverse up the tree using a bottom-up approach? 
         * In other words, we verify the deeper nodes before we verify if the above nodes satisfy the BST requirements.
         * Using a bottom-up approach, we need to pass some information up the tree. 
         * Obviously, we need to pass minimum and maximum values of the subtree as we traverse up the tree, so the above subtrees could be verified for BST’s properties
         * 自底向上的方法,不过需要存lower,upper的值以及size的大小
         */
        class Result {  // (size, rangeLower, rangeUpper) -- size of current tree, range of current tree [rangeLower, rangeUpper]
            int size;
            int lower;
            int upper;
            Result(int size, int lower, int upper) {
                this.size = size;
                this.lower = lower;
                this.upper = upper;
            }
        }
        int max = 0;
        public int largestBSTSubtree(TreeNode root) {
            if (root == null) { return 0; }    
            traverse(root, null);
            return max;
        }
        private Result traverse(TreeNode root, TreeNode parent) {
            if (root == null) { return new Result(0, parent.val, parent.val); }
            Result left = traverse(root.left, root);
            Result right = traverse(root.right, root);
            if (left.size==-1 || right.size==-1 || root.val<left.upper || root.val>right.lower) {
                return new Result(-1, 0, 0);
            }
            int size = left.size + 1 + right.size;
            max = Math.max(size, max);
            return new Result(size, left.lower, right.upper);//更新新的BST的范围,新的Size
        }
    }
    /*
     * 297. Serialize and Deserialize Binary Tree 
     * 2016-3-27 by Mingyang
     */
    class Codec {
         private static final String spliter = ",";
            private static final String NN = "X";
            // Encodes a tree to a single string.
            public String serialize(TreeNode root) {
                StringBuilder sb = new StringBuilder();
                buildString(root, sb);
                return sb.toString();
            }
            private void buildString(TreeNode node, StringBuilder sb) {
                if (node == null) {
                    sb.append(NN).append(spliter);
                } else {
                    sb.append(node.val).append(spliter);
                    buildString(node.left, sb);
                    buildString(node.right,sb);
                }
            }
            // Decodes your encoded data to tree.
            public TreeNode deserialize(String data) {
                Deque<String> nodes = new LinkedList<String>();
                nodes.addAll(Arrays.asList(data.split(spliter)));
                return buildTree(nodes);
            }
            private TreeNode buildTree(Deque<String> nodes) {
                String val = nodes.remove();
                if (val.equals(NN)) return null;
                else {
                    TreeNode node = new TreeNode(Integer.valueOf(val));
                    node.left = buildTree(nodes);
                    node.right = buildTree(nodes);
                    return node;
                }
            }
    }
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  • 原文地址:https://www.cnblogs.com/zmyvszk/p/5327977.html
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