Object.entries
返回对象所有可枚举的键值对，不会追寻原型链上的key
let obj = { key1: 'value1', key2: 'value2', key3: 'value3', } Object.entries(obj).forEach(entry => { let key = entry[0] let value = entry[1] // entry 会是这样 ["key1", "value1"] })
Object.keys
返回对象所有可枚举的键
let obj = { key1: 'value1', key2: 'value2', key3: 'value3', } Object.keys(obj).forEach(key => { let value = obj[key] })
Object.values
返回对象所有可枚举的值
let obj = { key1: 'value1', key2: 'value2', key3: 'value3', } Object.values(obj).forEach(value => { // 只能使用 value })
for…in loop
迭代可枚举属性，会顺着原型链找下去
let obj = { key1: 'value1', key2: 'value2', key3: 'value3', } for (const key in obj) { let value = obj[key] if (obj.hasOwnProperty(key)) { // 本身的 } else { // 来自原型链的 } }
Object.getOwnPropertyNames
返回对象所有（包括不可枚举）的键（原文说会找原型链是错的）
let obj = { key1: 'value1', key2: 'value2', key3: 'value3', } Object.getOwnPropertyNames(obj).forEach(key => { let value = obj[key] })
性能比较
下面的代码用上面的几种方法遍历有 1000000 个属性的对象，循环 10 次
const { PerformanceObserver, performance } = require('perf_hooks') let objectSize = 1000000 let iterations = 10 console.log( 'Starting performance test with %d object size and %d iterations', objectSize, iterations ) let values = { ENTRIES: 0, KEYS: 0, VALUES: 0, FORIN: 0, GETOWP: 0, } const obs = new PerformanceObserver(items => { let entry = items.getEntries()[0] console.log(entry.name, entry.duration) values[entry.name] += entry.duration performance.clearMarks() }) obs.observe({ entryTypes: ['measure'] }) function generateObject() { let obj = {} for (let i = 0; i < objectSize; i++) { obj['key' + Math.random()] = 'val' + Math.random() } return obj } for (let i = 0; i < iterations; i++) { let obj = generateObject() //Object.entries performance.mark('A') Object.entries(obj).forEach(entry => { let key = entry[0] let value = entry[1] }) performance.mark('B') performance.measure('ENTRIES', 'A', 'B') //Object.Keys performance.mark('A') Object.keys(obj).forEach(key => { let value = obj[key] }) performance.mark('B') performance.measure('KEYS', 'A', 'B') //Object.Values performance.mark('A') Object.values(obj).forEach(value => {}) performance.mark('B') performance.measure('VALUES', 'A', 'B') //For In performance.mark('A') for (const key in obj) { let value = obj[key] } performance.mark('B') performance.measure('FORIN', 'A', 'B') //Object.getOwnPropertyNames performance.mark('A') Object.getOwnPropertyNames(obj).forEach(key => { let value = obj[key] }) performance.mark('B') performance.measure('GETOWP', 'A', 'B') } console.log( Object.entries(values).sort((a, b) => { return a[1] - b[1] }) )
下面的结果是我自己跑的，顺序的是指赋值的时候直接用 index，随机则是键值对都插入随机数，得到的性能排序是和作者一样的，也因为 node.js 和 chrome 都是 V8，所以这个应该也是代表在浏览器上的性能排序。
// 顺序 ;[ ['FORIN', 4677.321499], ['KEYS', 4812.776572], ['GETOWP', 8610.906197], ['VALUES', 9914.674390999999], ['ENTRIES', 19338.083694], ] // 随机 ;[ ['KEYS', 4502.579589], ['FORIN', 4678.013548000001], ['GETOWP', 8880.325031999999], ['VALUES', 10104.106962], ['ENTRIES', 17089.637588999998], ]
之前听说引擎会猜测下一个值让运行速度更快，看数据似乎没有太大影响。
也算是一点干货，快点来原文给作者鼓鼓掌吧
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