# coding=utf-8 import asyncio import os import sys import time import json import cv2 from Apps.TeLaiDian.Kit import ( take_screenshot, get_image_content_md5, clean_station_name, setup_logger, detect_price_click_point_cv, read_image, save_image ) from Apps.TeLaiDian.ReadImageKit import ReadImageKit from Apps.TeLaiDian.Service import TeLaiDianService from Apps.TeLaiDian.Config.Setting import ( SCROLL_DISTANCE_RATIO, WAIT_AFTER_SCROLL, MAX_STATIONS_COUNT, SAFE_EXCLUDE_RATIO, BOTTOM_SAFE_EXCLUDE_RATIO, WAIT_DETAIL_PAGE_LOAD, WAIT_BACK_TO_LIST, DETAIL_SCROLL_DISTANCE_RATIO, FIRST_RUN_ONLY_ONE_STATION ) from Core.BaseCrawler import BaseCrawler import uiautomator2 as u2 # 项目根目录处理 project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) if project_root not in sys.path: sys.path.append(project_root) # 初始化日志 logger = setup_logger("TeLaiDianCrawler") PRICE_TAB_X_NORM = 220 PRICE_TAB_Y_NORM = 130 PRICE_ENTRY_X_NORM = 230 PRICE_ENTRY_Y_NORM = 380 class TeLaiDianCrawler(BaseCrawler): def __init__(self, service=None): super().__init__(service or TeLaiDianService()) self.read_image_kit = ReadImageKit() async def start(self): """ 实现 BaseCrawler 的启动入口 注意：在 T4 等全流程脚本中，小程序由 Opener 提前打开， 此处直接开始爬取逻辑。 """ d = u2.connect() await self.crawl_list_logic(d) async def open_app(self): """ 打开特来电小程序 """ from Apps.TeLaiDian import Opener return await Opener.open_mini_program() async def clear_ads(self, d, max_rounds=3): """ 清理页面上的广告弹窗，支持多轮检测 """ logger.info(f"--- [广告清理] 开始检测，最多尝试 {max_rounds} 轮 ---") for i in range(max_rounds): round_idx = i + 1 logger.info(f"[广告清理] 第 {round_idx} 轮：正在截屏分析...") ad_screen = take_screenshot(d, f"tld_ad_check_r{round_idx}_{int(time.time())}.jpg") try: res = await self.read_image_kit.find_close_button_vlm(ad_screen) if res.get("has_ad") and res.get("close_point"): close_point = res.get("close_point") reason = res.get("reason", "未提供原因") w, h = d.window_size() target_x = int(close_point[0] * w / 1000) target_y = int(close_point[1] * h / 1000) logger.info(f"[广告清理] 第 {round_idx} 轮：VLM 发现广告！原因: {reason}") logger.info(f"[广告清理] 计划点击坐标: ({target_x}, {target_y})，归一化坐标: {close_point}") # 安全校验：绝对不能点击微信小程序的胶囊按钮区 (右上角) if target_x > w * 0.75 and target_y < 150: logger.warning(f"[广告清理] ⚠️ 拒绝点击疑似微信胶囊按钮的区域: ({target_x}, {target_y})，跳过本轮。") continue logger.info(f"[广告清理] 正在执行点击关闭操作...") d.click(target_x, target_y) # 点击后等待一下，让弹窗消失或下一轮广告弹出 await asyncio.sleep(2.0) else: logger.info(f"[广告清理] 第 {round_idx} 轮：未发现广告弹窗。VLM 理由: {res.get('reason', '无')}") if os.path.exists(ad_screen): os.remove(ad_screen) break except Exception as e: logger.error(f"[广告清理] 第 {round_idx} 轮检测发生异常: {e}") finally: if os.path.exists(ad_screen): os.remove(ad_screen) logger.info("--- [广告清理] 任务结束 ---") async def crawl_list_logic(self, d): # 1. 启动即清理广告 (已根据要求关闭) # await self.clear_ads(d, max_rounds=3) # [优化] 向下滚动以刷新/校准地理位置 # 使用更加显式的 swipe 方式：从屏幕 30% 划到 80% popup_screen_path = take_screenshot(d, f"tld_detail_popup_{int(time.time())}.jpg") logger.info(f"[详情页] 截图用于检测温馨提示弹窗: {popup_screen_path}") template_xczs = os.path.join(os.path.dirname(__file__), "Template", "xczs.jpg") template_point = None if os.path.exists(template_xczs): try: match_res = d.image.match(template_xczs) if match_res: if hasattr(match_res, "point") and match_res.point: template_point = match_res.point elif isinstance(match_res, dict): if match_res.get("point"): template_point = match_res["point"] elif "x" in match_res and "y" in match_res: template_point = (match_res["x"], match_res["y"]) elif isinstance(match_res, (list, tuple)) and len(match_res) >= 2: template_point = (match_res[0], match_res[1]) if template_point: logger.info(f"[详情页] 模板检测到疑似温馨提示弹窗位置: {template_point}") else: logger.info("[详情页] 模板未能确定温馨提示弹窗位置") except Exception as e: logger.error(f"[详情页] 模板检测温馨提示弹窗失败: {e}") else: logger.info(f"[详情页] 温馨提示模板文件不存在: {template_xczs}") vlm_popup = {"has_popup": False} try: vlm_popup = await self.read_image_kit.check_warm_popup_vlm(popup_screen_path) except Exception as e: logger.error(f"[详情页] VLM 检测温馨提示弹窗失败: {e}") has_vlm_popup = isinstance(vlm_popup, dict) and vlm_popup.get("has_popup") if template_point and has_vlm_popup: click_x = int(template_point[0]) click_y = int(template_point[1]) logger.info(f"[详情页] 模板与 VLM 均确认存在温馨提示弹窗，即将点击关闭按钮: ({click_x}, {click_y})") debug_popup_path = popup_screen_path.replace(".jpg", f"_xczs_click_{click_x}_{click_y}.jpg") try: img_popup = read_image(popup_screen_path) if img_popup is not None: cv2.circle(img_popup, (click_x, click_y), 20, (0, 0, 255), -1) save_image(debug_popup_path, img_popup) logger.info(f"[详情页] 已生成温馨提示弹窗点击诊断图片: {debug_popup_path}") except Exception as e: logger.error(f"[详情页] 生成温馨提示弹窗诊断图片失败: {e}") try: d.click(click_x, click_y) await asyncio.sleep(1.5) except Exception as e: logger.error(f"[详情页] 点击温馨提示“下次再说”失败: {e}") else: logger.info(f"[详情页] 温馨提示弹窗未通过双重确认，模板检测: {bool(template_point)} | VLM 检测: {vlm_popup}") w, h = d.window_size() logger.info(f"执行显式下拉刷新操作: (x={w//2}, y1={int(h*0.3)} -> y2={int(h*0.8)})") d.swipe(w // 2, int(h * 0.3), w // 2, int(h * 0.8), duration=0.5) logger.info(f"等待 {WAIT_AFTER_SCROLL} 秒确保位置校准和列表刷新完成...") await asyncio.sleep(WAIT_AFTER_SCROLL) processed_count = 0 last_md5 = None processed_station_names = set() # 用于列表级去重 while processed_count < MAX_STATIONS_COUNT: # 1. 截图并分析 screenshot_path = take_screenshot(d, f"tld_list_{int(time.time())}.jpg") # 检测是否滚动到底部 curr_md5 = get_image_content_md5(screenshot_path, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO) if last_md5 == curr_md5: logger.info("内容无变化，判定已到底部") if os.path.exists(screenshot_path): os.remove(screenshot_path) break last_md5 = curr_md5 stations = await self.read_image_kit.analyze_station_list(screenshot_path) if not stations: # 检查是否意外退出了小程序 is_wrong_page = await self.check_wrong_page(d, screenshot_path) if is_wrong_page: logger.error("检测到已退出详情列表页（可能回到了搜索页），尝试重新进入...") await self.open_app() await asyncio.sleep(5) continue logger.info("本页未检测到场站，尝试滑动...") d.swipe_ext("up", scale=SCROLL_DISTANCE_RATIO) await asyncio.sleep(WAIT_AFTER_SCROLL) continue for station in stations: if processed_count >= MAX_STATIONS_COUNT: break name = station.get("name") point = station.get("point") if not name or not point: continue if name in processed_station_names: logger.info(f"跳过已处理场站: {name}") continue logger.info(f"处理场站: {name} (坐标: {point})") # 点击进入详情 d.click(point[0], point[1]) logger.info(f"已点击场站 '{name}'，等待 {WAIT_DETAIL_PAGE_LOAD}s 加载详情页...") await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD) # 截图验证是否进入详情页 detail_check_path = take_screenshot(d, f"tld_detail_check_{int(time.time())}.jpg") logger.info(f"详情页快照已保存: {detail_check_path}") # 简单验证：如果标题包含 "我的卡券"、"优惠券"、"新人福利" 等，说明点错了 is_wrong_page = await self.check_wrong_page(d, detail_check_path) if is_wrong_page: logger.warning(f"检测到进入了错误页面，尝试返回列表...") # 尝试点击左上角的返回箭头，如果没有，则执行系统 back d.click(40, 70) # 特来电通常左上角有返回箭头 await asyncio.sleep(1.0) d.press("back") await asyncio.sleep(WAIT_BACK_TO_LIST) if os.path.exists(detail_check_path): os.remove(detail_check_path) continue # 爬取详情 await self.crawl_detail_logic(d, station) processed_station_names.add(name) d.press("back") await asyncio.sleep(WAIT_BACK_TO_LIST) d.press("back") await asyncio.sleep(WAIT_BACK_TO_LIST) processed_count += 1 if FIRST_RUN_ONLY_ONE_STATION: logger.info("已完成首个场站的全流程采集，根据配置退出爬取任务。") if os.path.exists(screenshot_path): os.remove(screenshot_path) return # 滑动到下一页 d.swipe_ext("up", scale=SCROLL_DISTANCE_RATIO) await asyncio.sleep(WAIT_AFTER_SCROLL) if os.path.exists(screenshot_path): os.remove(screenshot_path) async def check_wrong_page(self, d, image_path): """ 检查是否误触进入了错误的页面（如：我的卡券、活动页等） """ data = await self.read_image_kit.check_wrong_page_vlm(image_path) is_detail = data.get("is_detail_page", True) if not is_detail: logger.warning(f"⚠️ 确认进入错误页面: {data.get('page_type')} ({data.get('reason')})") return not is_detail async def crawl_detail_logic(self, d, station_info): """ 在详情页提取价格和状态信息 """ first_screen_path = take_screenshot(d, f"tld_detail_basic_{int(time.time())}.jpg") station_name = station_info.get("name") address = station_info.get("address") logger.info(f"[详情页] 进入 crawl_detail_logic，场站: {station_name} | 地址: {address}") logger.info(f"[详情页] 已截取首屏截图，准备识别基础信息: {first_screen_path}") try: basic_info = await self.read_image_kit.analyze_detail_basic_info(first_screen_path) if isinstance(basic_info, dict): name2 = basic_info.get("name") addr2 = basic_info.get("address") if name2: station_name = name2 if addr2: address = addr2 logger.info(f"[详情页] 同步基础信息识别结果用于写库: {station_name} | {address}") except Exception as ex: logger.error(f"[详情页] 同步分析详情页基础信息失败: {ex}") finally: if os.path.exists(first_screen_path): try: os.remove(first_screen_path) except: pass w, h = d.window_size() logger.info("[详情页] 根据用户要求：进入页面后多等会，然后向上滑动一整屏，通过 VLM 查找价格入口") w, h = d.window_size() # 1. 增加等待时间，确保页面加载完成 logger.info(f"[详情页] 等待 {WAIT_DETAIL_PAGE_LOAD + 2}s 确保页面稳定 (根据要求多等会)...") await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD + 2) # 2. 向上滑动一部分屏 (从屏幕底部的 85% 划到顶部的 15%) # [优化] 避免滑过头，从全屏改为 0.7 屏幕左右 logger.info("[详情页] 执行向上滑动操作 (y: 85% -> 15%)") d.swipe(w // 2, int(h * 0.85), w // 2, int(h * 0.15), duration=0.8) await asyncio.sleep(2.0) # 滑动后再次等待稳定 # 3. 截图并识别 final_screen_path = take_screenshot(d, f"tld_detail_vlm_input_{int(time.time())}.jpg") logger.info(f"[详情页] 已截取 VLM 识别用图: {final_screen_path}") logger.info("[详情页] 优先使用 VLM 识别顶部“价格”标签和价格入口") price_tab_screen = final_screen_path entrance_clicked = False try: # 1. 尝试使用 VLM 寻找顶部“价格”标签 tab_data = await self.read_image_kit.find_price_tab_vlm(final_screen_path) tab_x, tab_y = None, None if tab_data.get("found") and tab_data.get("point"): p = tab_data["point"] tab_x = int(p[0] * w / 1000) tab_y = int(p[1] * h / 1000) logger.info(f"[详情页] VLM 成功找到价格标签: 归一化{p} -> 像素({tab_x}, {tab_y})") else: tab_x = int(PRICE_TAB_X_NORM * w / 1000) tab_y = int(PRICE_TAB_Y_NORM * h / 1000) logger.warning(f"[详情页] VLM 未找到价格标签，使用固定坐标兜底: 像素({tab_x}, {tab_y})") logger.info(f"[详情页] 正在点击价格标签...") d.click(tab_x, tab_y) await asyncio.sleep(2.0) # 点击标签后多等会 price_tab_screen = take_screenshot(d, f"tld_detail_after_price_tab_{int(time.time())}.jpg") logger.info(f"[详情页] 点击价格标签后的界面截图已保存: {price_tab_screen}") # 2. 尝试使用 VLM 寻找价格入口 (重点识别“全部时段 >”) entry_data = await self.read_image_kit.find_price_entrance_vlm(price_tab_screen) entry_x, entry_y = None, None if entry_data.get("found") and entry_data.get("point"): p = entry_data["point"] # 安全校验：严禁点击 y > 850 (85%) 的区域，那是底部浮动条 if p[1] > 850: logger.warning(f"[详情页] VLM 虽返回坐标 {p}，但 Y 轴过大 (疑似底部浮动条)，强制判定为未找到。") entry_x = int(PRICE_ENTRY_X_NORM * w / 1000) entry_y = int(PRICE_ENTRY_Y_NORM * h / 1000) else: entry_x = int(p[0] * w / 1000) entry_y = int(p[1] * h / 1000) logger.info(f"[详情页] VLM 成功找到价格入口 (匹配全部时段标识): 归一化{p} -> 像素({entry_x}, {entry_y})，原因: {entry_data.get('reason')}") else: entry_x = int(PRICE_ENTRY_X_NORM * w / 1000) entry_y = int(PRICE_ENTRY_Y_NORM * h / 1000) logger.warning(f"[详情页] VLM 未找到价格入口，使用固定坐标兜底: 像素({entry_x}, {entry_y})") click_x = max(5, min(w - 5, entry_x)) click_y = max(5, min(h - 5, entry_y)) debug_click_path = price_tab_screen.replace( ".jpg", f"_click_tab_{tab_x}_{tab_y}_entry_{click_x}_{click_y}.jpg" ) try: img = read_image(price_tab_screen) if img is not None: cv2.circle(img, (tab_x, tab_y), 20, (0, 0, 255), -1) cv2.circle(img, (click_x, click_y), 20, (0, 0, 255), -1) save_image(debug_click_path, img) logger.info(f"[详情页] 已生成价格点击诊断红点图: {debug_click_path}") except Exception as e: logger.error(f"[详情页] 生成诊断图片失败: {e}") logger.info(f"[详情页] 正在点击电价入口...") d.click(click_x, click_y) entrance_clicked = True await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD) except Exception as e: logger.error(f"[详情页] 识别或点击价格入口失败: {e}") if entrance_clicked: entered_price_path = take_screenshot(d, f"tld_detail_price_after_enter_{int(time.time())}.jpg") logger.info(f"[电价页] 入口点击后的电价页截图已保存: {entered_price_path}") await asyncio.sleep(1.0) logger.info("[电价页] 先多次向下滚动，使列表回到起始位置") top_last_md5 = None top_stable = 0 max_top_round = 8 price_top_screen = entered_price_path for idx in range(max_top_round): price_top_screen = take_screenshot(d, f"tld_detail_price_top_{int(time.time())}_{idx}.jpg") logger.info(f"[电价页] 向下滚动前后的截图: {price_top_screen}") curr_md5 = get_image_content_md5(price_top_screen, top_ratio=0.2, bottom_ratio=0.2) if top_last_md5 is not None and curr_md5 == top_last_md5: top_stable += 1 logger.info(f"[电价页] 页面内容连续第 {top_stable} 次无变化，可能已到顶部") if top_stable >= 2: break else: top_stable = 0 top_last_md5 = curr_md5 d.swipe_ext("down", scale=0.8) await asyncio.sleep(1.0) all_prices = [] last_price_md5 = None price_page_count = 0 max_price_pages = 4 screenshot_tasks = [] temp_screenshots = [] price_screen_path = price_top_screen try: while price_page_count < max_price_pages: price_screen_path = take_screenshot(d, f"tld_detail_price_{int(time.time())}_{price_page_count}.jpg") curr_md5 = get_image_content_md5(price_screen_path, top_ratio=0.2, bottom_ratio=0.2) if curr_md5 == last_price_md5: logger.info("价格页面内容无变化，判定已触底") if os.path.exists(price_screen_path): os.remove(price_screen_path) break last_price_md5 = curr_md5 temp_screenshots.append(price_screen_path) logger.info(f"已截取价格详情页第 {price_page_count + 1} 页: {price_screen_path}，启动后台异步分析") task = asyncio.create_task(self.read_image_kit.analyze_detail_price(price_screen_path)) screenshot_tasks.append(task) logger.info("向上滚动列表，准备截取下一屏价格...") d.swipe_ext("up", scale=0.8) await asyncio.sleep(1.0) price_page_count += 1 if screenshot_tasks: logger.info(f"UI 操作已完成，等待 {len(screenshot_tasks)} 个后台分析任务结束...") results = await asyncio.gather(*screenshot_tasks, return_exceptions=True) for res in results: if isinstance(res, Exception): logger.error(f"后台分析任务出错: {res}") continue if res: for p in res: is_duplicate = False for existing in all_prices: if p.get('start') == existing.get('start') and p.get('end') == existing.get('end'): is_duplicate = True for key in ['price', 'plus_price', 'market_price', 'elec_price', 'service_price']: if p.get(key) is not None and (existing.get(key) is None or existing.get(key) == 0): existing[key] = p[key] break if not is_duplicate: all_prices.append(p) except Exception as e: logger.error(f"抓取价格详情过程中发生异常: {e}") finally: for task in screenshot_tasks: if not task.done(): task.cancel() for path in temp_screenshots: if os.path.exists(path): try: os.remove(path) except: pass if all_prices: station_name_clean = clean_station_name(station_name) try: all_prices.sort(key=lambda x: x.get('start', '00:00')) except: pass logger.info(f"✅ 场站 {station_name_clean} 共提取到 {len(all_prices)} 条价格信息，准备保存...") await self.service.save_station_data(station_name_clean, address, all_prices) else: logger.warning(f"❌ 未能提取到任何价格信息，请检查页面识别逻辑") if address: station_name_clean = clean_station_name(station_name) logger.info(f"[详情页] 虽未获取价格，但已获取地址，尝试仅保存基础信息: {station_name_clean} | {address}") try: await self.service.save_station_profile_only(station_name_clean, address) except Exception as e: logger.error(f"[详情页] 仅保存基础信息失败: {e}") if os.path.exists(price_screen_path): os.remove(price_screen_path) async def crawl_list(self): """ 实现 BaseCrawler 的抽象方法 """ d = u2.connect() await self.crawl_list_logic(d) async def crawl_detail(self, station_info): """ 实现 BaseCrawler 的抽象方法 """ # 逻辑已在 crawl_list_logic 中通过 crawl_detail_logic 调用 pass async def main(service=None): crawler = TeLaiDianCrawler(service=service) await crawler.start() if __name__ == "__main__": asyncio.run(main())