import asyncio import logging import uuid import os import sys import json import time from datetime import datetime from Apps.YeLiTe.Kit import take_screenshot, clean_station_name, get_image_content_md5, detect_price_info_container_cv from Apps.YeLiTe.ReadImageKit import ReadImageKit from Apps.YeLiTe.Service import YeLiTeService from Apps.YeLiTe.Config.Setting import ( SCROLL_DISTANCE_RATIO, WAIT_AFTER_SCROLL, MAX_STATIONS_COUNT, WAIT_DETAIL_PAGE_LOAD, WAIT_BACK_TO_LIST, TEST_CLEAR_REDIS, SAFE_EXCLUDE_RATIO, BOTTOM_SAFE_EXCLUDE_RATIO, FIRST_RUN_ONLY_ONE_STATION ) from Util.RedisKit import RedisKit 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) logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s') logger = logging.getLogger("YeLiTeCrawler") class YeLiTeCrawler(BaseCrawler): def __init__(self, service=None): super().__init__(service or YeLiTeService()) self.read_image_kit = ReadImageKit() self.redis_kit = RedisKit() async def start(self): """ 实现 BaseCrawler 的启动入口 """ await main(self.service) async def open_app(self): """ 打开驿来特小程序 """ from Apps.YeLiTe import Opener return await Opener.open_mini_program() async def crawl_list(self): """ 开始爬取列表页 """ d = u2.connect() return await self.crawl_list_logic(d) async def crawl_detail(self, station_info): """ 爬取详情页 (BaseCrawler 要求，此处逻辑已集成在 crawl_list_logic 中) """ pass async def clean_redis_data(self): """ 清除测试用的 Redis 记录 """ if TEST_CLEAR_REDIS: logger.info("清理 Redis 中的场站处理记录...") pattern = "crawled:ylt:*" keys = await self.redis_kit.keys(pattern) if keys: await self.redis_kit.delete(*keys) async def crawl_list_logic(self, d): w, h = d.window_size() max_to_crawl = 1 if FIRST_RUN_ONLY_ONE_STATION else MAX_STATIONS_COUNT processed_count = 0 no_new_data_count = 0 last_md5 = None background_tasks = [] while processed_count < max_to_crawl: # 1. 截图并分析 screenshot_path = take_screenshot(d, f"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: no_new_data_count += 1 if no_new_data_count >= 5: logger.info("连续 5 页无新数据，停止") break # 滑动 d.swipe_ext("up", scale=SCROLL_DISTANCE_RATIO) await asyncio.sleep(WAIT_AFTER_SCROLL) continue no_new_data_count = 0 new_stations_in_page = 0 for station in stations: if processed_count >= max_to_crawl: break name = station.get('name') address = station.get('address') distance = station.get('distance') point = station.get('point') if not name or not point: continue # 去重 redis_key = f"crawled:ylt:{clean_station_name(name)}" if await self.redis_kit.get_data(redis_key): logger.info(f"场站 {name} 已处理过，跳过") continue current_idx = processed_count + 1 remaining = max_to_crawl - current_idx logger.info(f"--- [进度: {current_idx}/{max_to_crawl}, 剩余: {remaining}] 发现新场站: {name} (坐标: {point}, 距离: {distance}) ---") # 点击进入前截图，用于对比是否成功进入二级页 before_click_path = take_screenshot(d, f"before_{clean_station_name(name)}") before_md5 = get_image_content_md5(before_click_path, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO) # 稍微等待一下，确保 UI 稳定 await asyncio.sleep(0.5) # 使用 input tap 替代 d.click，提高点击成功率 (部分小程序对 click 响应不佳) d.shell(f"input tap {int(point[0])} {int(point[1])}") await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD) # 分析详情页 (采用异步后台模式) detail_shot = take_screenshot(d, f"detail_{clean_station_name(name)}_{int(time.time())}") after_md5 = get_image_content_md5(detail_shot, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO) # 清理临时对比图 if os.path.exists(before_click_path): os.remove(before_click_path) if before_md5 == after_md5: logger.warning(f"首次点击 {name} 未跳转，尝试稍微偏移位置重试...") # 尝试向下偏移 20px 点击 offset_y = point[1] + 20 d.shell(f"input tap {int(point[0])} {int(offset_y)}") await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD) # 再次截图检查 if os.path.exists(detail_shot): os.remove(detail_shot) detail_shot = take_screenshot(d, f"detail_{clean_station_name(name)}_{int(time.time())}") after_md5 = get_image_content_md5(detail_shot, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO) if before_md5 != after_md5: logger.info(f"成功进入详情页: {name}") # 兜底：在进入详情页后，先基于列表页信息一次性写入 Profile 与 Status try: await self.service.save_station_profile_and_status( station_name=name, address=address, total_piles=station.get("total_piles"), free_piles=station.get("free_piles"), piles_detail=None, parking_info=None, distance=distance ) except Exception as e: logger.warning(f"兜底写入场站基础信息失败: {name}, {e}") # --- 新增：点击“阶段性电价”按钮以获取完整电价列表 --- # 使用 OCR 探测价格入口 dqdf_pos = detect_price_info_container_cv(detail_shot) detail_shots = [] if dqdf_pos: logger.info(f"发现价格入口按钮 (阶段性电价/当前电费) {dqdf_pos}，点击进入...") d.click(dqdf_pos[0], dqdf_pos[1]) await asyncio.sleep(0.5) # 等待列表加载 # 删除旧的详情页截图 if os.path.exists(detail_shot): os.remove(detail_shot) # 1. 向下滚动到底 (根据用户反馈：只有不断向下滚动，才能看到00点的) logger.info("正在向下滚动价格列表到底部 (快速多次滚动以尽快看到 00:00)...") max_scroll_down = 10 for i in range(max_scroll_down): before_scroll_path = take_screenshot(d, f"scroll_dn_{i}") before_scroll_md5 = get_image_content_md5(before_scroll_path) d.swipe_ext("up", scale=0.8) await asyncio.sleep(0.3) after_scroll_path = take_screenshot(d, f"scroll_dn_after_{i}") after_scroll_md5 = get_image_content_md5(after_scroll_path) # 清理临时截图 if os.path.exists(before_scroll_path): os.remove(before_scroll_path) if os.path.exists(after_scroll_path): os.remove(after_scroll_path) if before_scroll_md5 == after_scroll_md5: logger.info(f"价格列表已到达底部 (滚动次数: {i})") break # 2. 向上滚动并逐页截图 (从底向上抓取) logger.info("正在向上滚动价格列表并逐页截图...") max_scroll_up = 10 for p_idx in range(1, max_scroll_up + 1): # 截图当前页 p_shot = take_screenshot(d, f"detail_price_{clean_station_name(name)}_{int(time.time())}_{p_idx}") # 检查是否还能向上滚动 before_up_md5 = get_image_content_md5(p_shot) d.swipe_ext("down", scale=0.85) await asyncio.sleep(0.3) # 检查是否还有新内容 check_up_shot = take_screenshot(d, f"check_up_{p_idx}") after_up_md5 = get_image_content_md5(check_up_shot) if os.path.exists(check_up_shot): os.remove(check_up_shot) detail_shots.append(p_shot) if before_up_md5 == after_up_md5: logger.info(f"价格列表已到达顶部 (共抓取页数: {p_idx})") break # 关闭分时段定价列表 (点击屏幕最顶部空白处) logger.info("点击屏幕上部空白处以关闭定价列表...") d.click(w * 0.5, h * 0.1) await asyncio.sleep(1.0) else: logger.info("未发现价格入口按钮 (阶段性电价/当前电费)，直接分析当前页") detail_shots.append(detail_shot) # -------------------------------------------------- # 启动后台任务处理详情页 task = asyncio.create_task(self.analyze_detail_background(name, detail_shots, address=address, distance=distance)) background_tasks.append(task) processed_count += 1 new_stations_in_page += 1 await self.redis_kit.set_data(redis_key, "1", expire=86400*7) # 返回列表页 (现在应该已经回到了详情页主界面) d.press("back") await asyncio.sleep(WAIT_BACK_TO_LIST) # 再次检查是否回到了列表页，如果没回，再点一次 back after_back_shot = take_screenshot(d, "check_back") after_back_md5 = get_image_content_md5(after_back_shot, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO) if os.path.exists(after_back_shot): os.remove(after_back_shot) if after_back_md5 == after_md5: # 还在详情页/电费页 logger.info("似乎还在二级页面，尝试再次返回...") d.press("back") await asyncio.sleep(WAIT_BACK_TO_LIST) if FIRST_RUN_ONLY_ONE_STATION: logger.info("已完成首个场站的全流程采集，根据配置退出驿来特爬取任务。") return processed_count else: logger.warning(f"点击场站 {name} 后页面似乎未跳转，跳过返回操作") if os.path.exists(detail_shot): os.remove(detail_shot) # 即使没进去，也记录一下，避免短时间内重复尝试 await self.redis_kit.set_data(redis_key, "1", expire=3600) if new_stations_in_page == 0 and stations: no_new_data_count += 1 if no_new_data_count >= 5: logger.info("连续 5 页均无新场站，停止") break else: no_new_data_count = 0 # 滑动翻页 d.swipe_ext("up", scale=SCROLL_DISTANCE_RATIO) await asyncio.sleep(WAIT_AFTER_SCROLL) # 等待后台任务完成 if background_tasks: logger.info(f"等待 {len(background_tasks)} 个后台分析任务完成...") await asyncio.gather(*background_tasks, return_exceptions=True) return processed_count async def analyze_detail_background(self, station_name, image_paths, address=None, distance=None): """ 后台异步分析详情页 (支持多张截图合并) """ try: if isinstance(image_paths, str): image_paths = [image_paths] logger.info(f"开始后台分析场站: {station_name} (图片数: {len(image_paths)})") all_prices = [] for img_path in image_paths: prices = await self.read_image_kit.analyze_detail_price(img_path) if prices: all_prices.extend(prices) # 去重合并 unique_prices = [] seen_periods = set() for p in all_prices: start = str(p.get('start', '')).strip() end = str(p.get('end', '')).strip() if not start or not end: continue key = f"{start}-{end}" if key not in seen_periods: seen_periods.add(key) unique_prices.append(p) # 按开始时间排序 unique_prices.sort(key=lambda x: x.get('start', '00:00')) if unique_prices: await self.service.process_price_detail_data(station_name, unique_prices, address=address, distance=distance) logger.info(f"场站 {station_name} 价格分析完成并入库 (记录数: {len(unique_prices)}, 地址: {address}, 距离: {distance})") else: logger.warning(f"场站 {station_name} 未识别到价格信息") except Exception as e: logger.error(f"后台分析 {station_name} 失败: {e}") finally: # 调试阶段暂时不删除截图，方便排查 VLM 识别失败原因 pass # if isinstance(image_paths, list): # for p in image_paths: # if os.path.exists(p): os.remove(p) # elif isinstance(image_paths, str) and os.path.exists(image_paths): # os.remove(image_paths) async def main(service=None): if service is None: service = YeLiTeService() await service.init_db() crawler = YeLiTeCrawler(service) d = u2.connect() # 清理 Redis await crawler.clean_redis_data() # 记录任务日志 task_id = str(uuid.uuid4()) await service.log_task_start(task_id) total_count = 0 status = "success" error_msg = None try: total_count = await crawler.crawl_list_logic(d) except Exception as e: logger.error(f"主流程执行失败: {e}") status = "failed" error_msg = str(e) finally: await service.log_task_end(task_id, total_count, status, error_msg) # 如果是内部初始化的 service，则关闭 if service and not isinstance(service, YiLaiTeService): await service.close_db() async def get_image_md5_async(path): return get_image_md5(path) if __name__ == "__main__": asyncio.run(main())