20260821173417

code/fms/.playwright-cli/pixel-scan2.mjs

@@ -0,0 +1,72 @@
+import { chromium } from 'playwright-core'
+
+const BASE = 'http://localhost:5082'
+const browser = await chromium.launch({
+  headless: true,
+  executablePath: 'C:\\Program Files\\Google\\Chrome\\Application\\chrome.exe',
+})
+const page = await browser.newPage({ viewport: { width: 1440, height: 900 }, deviceScaleFactor: 1 })
+
+await page.addInitScript(() => {
+  sessionStorage.setItem('fms-login', JSON.stringify({ loginInfo: { token: 'dev-token', user: { id: 1, name: 'dev', account: 'g3soft' } } }))
+  localStorage.setItem('fms-user', JSON.stringify({ userInfo: { orgId: 'G3HD', account: 'g3soft' } }))
+})
+await page.route('**/api/**', async (route) => {
+  const req = route.request()
+  const url = req.url()
+  let body = {}
+  try { body = req.postDataJSON() || {} } catch {}
+  if (url.includes('/data/loaddata')) {
+    const rows = body.view_name === 's_module' ? [{ b_id: 1, b_code: 'b_port', b_name: '港口管理' }] :
+      body.view_name === 'bf_files_cateid' ? [{ b_id: '10', b_name: '合同文件' }] : []
+    return route.fulfill({ status: 200, contentType: 'application/json', body: JSON.stringify({ code: 0, data: rows }) })
+  }
+  if (url.includes('/data/page')) {
+    const files = Array.from({ length: 4 }, (_, i) => ({
+      subid: String(1000 + i), father: '1001', mx_moduleid: '1', mx_cate_id: '10',
+      mx_filename: `文件-${i + 1}.pdf`, mx_filesize: (i + 1) * 1024 * 1024,
+      mx_fileext: 'pdf', mx_mapfilename: '',
+    }))
+    return route.fulfill({ status: 200, contentType: 'application/json', body: JSON.stringify({ code: 0, data: { rows: files, total: files.length } }) })
+  }
+  return route.fulfill({ status: 200, contentType: 'application/json', body: JSON.stringify({ code: 0, data: null }) })
+})
+
+await page.goto(`${BASE}/file-demo`, { waitUntil: 'networkidle', timeout: 30000 })
+await page.waitForTimeout(2000)
+await page.locator('button:has-text("声明式弹窗")').click()
+await page.waitForTimeout(1500)
+
+const b64 = await page.screenshot({ encoding: 'base64' })
+const analysis = await page.evaluate(async (b64) => {
+  const bin = atob(b64)
+  const bytes = new Uint8Array(bin.length)
+  for (let i = 0; i < bin.length; i++) bytes[i] = bin.charCodeAt(i)
+  const blob = new Blob([bytes], { type: 'image/png' })
+  const bmp = await createImageBitmap(blob)
+  const canvas = document.createElement('canvas')
+  canvas.width = bmp.width
+  canvas.height = bmp.height
+  const ctx = canvas.getContext('2d')
+  ctx.drawImage(bmp, 0, 0)
+  const { width, height } = canvas
+
+  const px = (x, y) => {
+    const d = ctx.getImageData(x, y, 1, 1).data
+    return `${d[0]},${d[1]},${d[2]}`
+  }
+
+  // For each x in the splitter region, count how many sample rows are the border-gray color
+  // and report a compact "row" profile at several y positions
+  const yPositions = [220, 300, 400, 500, 600, 700]
+  const profile = []
+  for (let x = 370; x <= 930; x++) {
+    const row = {}
+    for (const y of yPositions) row[`y${y}`] = px(x, y)
+    profile.push({ x, ...row })
+  }
+  return { imgW: width, imgH: height, profile }
+}, b64)
+
+console.log(JSON.stringify(analysis, null, 2))
+await browser.close()