js解析excel
2019-09-29 本文已影响0人
曦惜夕
在日常开发中,遇到批量导入的情况,通常是将文件上传至后端来解析excel文件流。这种做法会占用一定的带宽和后端性能。现在,JS也可以解析excel啦。
通过使用xlsx库来解析excel。兼容性方面,支持IE10及以上。在这里我写了一个小工具供大家参考。该工具的用途主要是整理xlsx库解析出来的数据。让数据更容易使用。工具中暴露出两个方法:readXlsx和downloadXlsx。
readXlsx用于解析上传的xlsx模板,downloadXlsx用于导出模板。
import Xlsx from 'xlsx'
const letters = [
'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M',
'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'
]
export async function readXlsx(file) {
if (file) {
const metaData = await readFile(file)
const xlsx = Xlsx.read(metaData, {type: 'binary'})
const data = createArray(xlsx)
return getData(data, xlsx)
}
return {}
}
export async function downloadXlsx(filename, obj) {
const wb = new WorkBook(obj)
Xlsx.writeFile(wb, filename)
}
class WorkBook {
constructor(data) {
this.SheetNames = Object.keys(data)
this.Sheets = {}
for (const name of this.SheetNames) {
const sheet = {
[name]: setData(data[name])
}
Object.assign(this.Sheets, sheet)
}
}
}
function readFile(file) {
return new Promise((resolve, reject) => {
const reader = new FileReader()
reader.readAsBinaryString(file)
reader.onload = (e) => {
resolve(e.target.result)
}
})
}
function createArray({SheetNames, Sheets}) {
const result = {}
for (const name of SheetNames) {
const arr = []
const ref = Sheets[name]['!ref']
let [x, y] = getRange(ref)
for (let i = 0; i < y; i++) {
const tp = []
for (let j = 0; j < x; j++) {
tp.push(undefined)
}
arr.push(tp)
}
Object.assign(result, {[name]: arr})
}
return result
}
function getRange(ref) {
const boundary = ref.split(':')[1]
const a1 = boundary.split(/[0-9]+/)[0]
const a2 = boundary.split(/[A-Z]+/)[1]
return [getNumber(a1), a2 * 1]
}
function getNumber(letter) {
const arr = letter.split('')
let result = 0
for (let i = 0; i < arr.length; i++) {
result += (letters.indexOf(arr[i]) + 1) * Math.pow(26, arr.length - i - 1)
}
return result
}
function getLetter(num) {
num *= 1
const t = (num - 1).toString('26')
const arr = t.split('')
let result = ''
for (let i in arr) {
i *= 1
const n = parseInt(arr[i], 26) * 1
result += letters[i !== arr.length - 1 ? n - 1 : n]
}
return result
}
function getData(data, {SheetNames, Sheets}) {
for (const name of SheetNames) {
const copySheet = JSON.parse(JSON.stringify(Sheets[name]))
delete copySheet['!margins']
delete copySheet['!ref']
const keys = Object.keys(copySheet)
for (const key of keys) {
const a1 = key.split(/[0-9]+/)[0]
const a2 = key.split(/[A-Z]+/)[1]
const point = {x: getNumber(a1), y: a2 * 1}
data[name][point.y - 1][point.x - 1] = copySheet[key].v
}
}
return data
}
function setData(data = []) {
const result = {'!ref': ''}
let width, height = data.length, start
for (let i in data) {
i *= 1
if (width) {
if (data[i].length > width) {
width = data[i].length
}
} else {
width = data[i].length
}
for (let j in data[i]) {
j *= 1
const v = data[i][j]
const k = getLetter(j + 1) + (i + 1)
if (v) {
result[k] = {v, t: 's'}
if (!start) {
start = k
}
}
}
}
if (width && height && start) {
result['!ref'] = `${start}:${getLetter(width) + height}`
}
return result
}
首先引入该工具:
import {readXlsx, downloadXlsx} from './excelUtil'
Import Example:
const file = this.$refs['file-container'].files[0]
const data = await readXlsx(file)
console.log(data)
上传的xlsx被解析成为了一个二维数组
Export Example:
downloadXlsx('hello.xlsx',{"asd": [['账号', '密码', '性别', '姓名', '昵称', '生日', '兴趣爱好']]})
导出的模板文件: hello.xlsx
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