1. Array -> Tree

var arr = [{ id: 12, parentId: 1, name: "朝阳区" },{ id: 241, parentId: 24, name: "田林街道" },{ id: 31, parentId: 3, name: "广州市" },{ id: 13, parentId: 1, name: "昌平区" },{ id: 2421, parentId: 242, name: "上海科技绿洲" },{ id: 21, parentId: 2, name: "静安区" },{ id: 242, parentId: 24, name: "漕河泾街道" },{ id: 22, parentId: 2, name: "黄浦区" },{ id: 11, parentId: 1, name: "顺义区" },{ id: 2, parentId: 0, name: "上海市" },{ id: 24, parentId: 2, name: "徐汇区" },{ id: 1, parentId: 0, name: "北京市" },{ id: 2422, parentId: 242, name: "漕河泾开发区" },{ id: 32, parentId: 3, name: "深圳市" },{ id: 33, parentId: 3, name: "东莞市" },{ id: 3, parentId: 0, name: "广东省" },
];function arrayToTreeV3(arr, root) {return arr.filter((item) => item.parentId === root).map((item) => ({ ...item, children: arrayToTreeV3(arr, item.id) }));
}
let test = arrayToTreeV3(arr, 0);

2. Tree -> Array

const treeData = [{id: 2,title: "中国",parent_id: 0,children: [{id: 3,title: "广东省",parent_id: 2,children: [{id: 4,title: "广州市",parent_id: 3,children: [{ id: 5, title: "天河区", parent_id: 4 }],},],},{ id: 6, title: "湖南省", parent_id: 2 },],},{ id: 1, title: "俄罗斯", parent_id: 0 },
];function treeToList(data) {let res = [];const dfs = (tree) => {tree.forEach((item) => {if (item.children) {dfs(item.children);delete item.children;}res.push(item);});};dfs(data);return res;
}
let testarr = treeToList(treeData);

3.Tree 查找路径（id）

function parseTreePath(tree, id, path = "") {for (let i = 0; i < tree.length; i++) {let tempPath = path;// 避免出现在最前面的/tempPath = `${tempPath ? tempPath + "/ " : tempPath}${tree[i].title}`;if (tree[i].id == id) return tempPath;else if (tree[i].children) {let reuslt = parseTreePath(tree[i].children, id, tempPath);if (reuslt) return reuslt;}}
}
console.log(parseTreePath(treeData, 5));

4. 树的深度优先遍历

思想：访问该元素后，如果该元素存在子元素，则访问该元素的第一个子元素，如果不存在，则访问该元素的兄弟节点（即退出该函数，返回上一层函数，访问上一层中未被访问的子元素），重复此操作。

//         a
//    b         c
//c d e f    g h iconst dfs = root => {if(!root) return;console.log(root.val);root.children.forEach(child => {dfs(child)})
}dfs( treeData)
// a b d e f c g h i

5. 广度优先遍历

思想：访问该元素后，如果该元素存在兄弟节点，则依次访问该元素的兄弟节点，如果不存在，则访问该元素的孩子节点

//         a
//    b         c
//c d e f    g h iconst bfs = root => {if(!root) return;const queue = [root];while(queue.length) {const top = queue.shift();console.log(top.val);top.children.forEach(child => {queue.push(child)})}
}bfs( treeData)
// a b c d e f g h i