98 lines
3.7 KiB
JavaScript
98 lines
3.7 KiB
JavaScript
import { chromium } from 'playwright-core'
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const BASE = 'http://localhost:5082'
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const browser = await chromium.launch({
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headless: true,
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executablePath: 'C:\\Program Files\\Google\\Chrome\\Application\\chrome.exe',
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})
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const page = await browser.newPage({ viewport: { width: 1440, height: 900 }, deviceScaleFactor: 1 })
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await page.addInitScript(() => {
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sessionStorage.setItem('fms-login', JSON.stringify({ loginInfo: { token: 'dev-token', user: { id: 1, name: 'dev', account: 'g3soft' } } }))
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localStorage.setItem('fms-user', JSON.stringify({ userInfo: { orgId: 'G3HD', account: 'g3soft' } }))
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})
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await page.route('**/api/**', async (route) => {
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const req = route.request()
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const url = req.url()
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let body = {}
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try { body = req.postDataJSON() || {} } catch {}
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if (url.includes('/data/loaddata')) {
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const rows = body.view_name === 's_module' ? [{ b_id: 1, b_code: 'b_port', b_name: '港口管理' }] :
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body.view_name === 'bf_files_cateid' ? [{ b_id: '10', b_name: '合同文件' }] : []
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return route.fulfill({ status: 200, contentType: 'application/json', body: JSON.stringify({ code: 0, data: rows }) })
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}
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if (url.includes('/data/page')) {
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const files = Array.from({ length: 4 }, (_, i) => ({
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subid: String(1000 + i), father: '1001', mx_moduleid: '1', mx_cate_id: '10',
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mx_filename: `文件-${i + 1}.pdf`, mx_filesize: (i + 1) * 1024 * 1024,
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mx_fileext: 'pdf', mx_mapfilename: '',
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}))
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return route.fulfill({ status: 200, contentType: 'application/json', body: JSON.stringify({ code: 0, data: { rows: files, total: files.length } }) })
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}
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return route.fulfill({ status: 200, contentType: 'application/json', body: JSON.stringify({ code: 0, data: null }) })
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})
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await page.goto(`${BASE}/file-demo`, { waitUntil: 'networkidle', timeout: 30000 })
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await page.waitForTimeout(2000)
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await page.locator('button:has-text("声明式弹窗")').click()
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await page.waitForTimeout(1500)
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// Take screenshot as base64, load into canvas inside the page, and sample pixel columns
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const b64 = await page.screenshot({ encoding: 'base64' })
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const analysis = await page.evaluate(async (b64) => {
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const img = new Image()
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img.src = 'data:image/png;base64,' + b64
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await img.decode()
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const canvas = document.createElement('canvas')
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canvas.width = img.width
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canvas.height = img.height
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const ctx = canvas.getContext('2d')
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ctx.drawImage(img, 0, 0)
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const { width, height } = canvas
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// get color at pixel
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const px = (x, y) => {
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const d = ctx.getImageData(x, y, 1, 1).data
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return `${d[0]},${d[1]},${d[2]}`
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}
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// Scan a horizontal strip at y = 500 (mid of dialog) from x=570 to x=1410
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// and report runs of distinct colors
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const y = 500
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const runs = []
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let cur = null
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for (let x = 570; x < 1410; x++) {
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const c = px(x, y)
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if (cur && cur.color === c) {
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cur.to = x
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} else {
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if (cur) runs.push(cur)
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cur = { color: c, from: x, to: x }
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}
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}
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if (cur) runs.push(cur)
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// Vertical line detection: for a given x, count how many y in [215, 850] have the same color
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const lineAt = (x) => {
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const counts = new Map()
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for (let yy = 215; yy < 850; yy += 2) {
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const c = px(x, yy)
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counts.set(c, (counts.get(c) || 0) + 1)
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}
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const sorted = [...counts.entries()].sort((a, b) => b[1] - a[1]).slice(0, 3)
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return sorted.map(([c, n]) => ({ color: c, count: n }))
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}
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// Check the two bar regions: every x in the bar area, list dominant colors
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const bars = []
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for (const [x0, x1] of [[795, 806], [1301, 1312]]) {
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const cols = []
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for (let x = x0; x <= x1; x++) cols.push({ x, colors: lineAt(x) })
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bars.push(cols)
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}
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return { runs, bars, imgW: width, imgH: height }
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}, b64)
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console.log(JSON.stringify(analysis, null, 2))
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await browser.close()
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