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()