500 lines
23 KiB
Python
500 lines
23 KiB
Python
# coding=utf-8
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import asyncio
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import os
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import sys
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import time
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import json
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import cv2
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from Apps.TeLaiDian.Kit import (
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take_screenshot, get_image_content_md5, clean_station_name,
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setup_logger, detect_price_click_point_cv, read_image, save_image
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)
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from Apps.TeLaiDian.ReadImageKit import ReadImageKit
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from Apps.TeLaiDian.Service import TeLaiDianService
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from Apps.TeLaiDian.Config.Setting import (
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SCROLL_DISTANCE_RATIO, WAIT_AFTER_SCROLL, MAX_STATIONS_COUNT,
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SAFE_EXCLUDE_RATIO, BOTTOM_SAFE_EXCLUDE_RATIO, WAIT_DETAIL_PAGE_LOAD,
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WAIT_BACK_TO_LIST, DETAIL_SCROLL_DISTANCE_RATIO, FIRST_RUN_ONLY_ONE_STATION
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)
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from Core.BaseCrawler import BaseCrawler
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import uiautomator2 as u2
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# 项目根目录处理
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project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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if project_root not in sys.path:
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sys.path.append(project_root)
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# 初始化日志
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logger = setup_logger("TeLaiDianCrawler")
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PRICE_TAB_X_NORM = 220
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PRICE_TAB_Y_NORM = 130
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PRICE_ENTRY_X_NORM = 230
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PRICE_ENTRY_Y_NORM = 380
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class TeLaiDianCrawler(BaseCrawler):
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def __init__(self, service=None):
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super().__init__(service or TeLaiDianService())
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self.read_image_kit = ReadImageKit()
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async def start(self):
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"""
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实现 BaseCrawler 的启动入口
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注意：在 T4 等全流程脚本中，小程序由 Opener 提前打开，
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此处直接开始爬取逻辑。
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"""
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d = u2.connect()
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await self.crawl_list_logic(d)
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async def open_app(self):
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"""
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打开特来电小程序
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"""
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from Apps.TeLaiDian import Opener
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return await Opener.open_mini_program()
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async def clear_ads(self, d, max_rounds=3):
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"""
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清理页面上的广告弹窗
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"""
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logger.info(f"开始清理广告弹窗，最多尝试 {max_rounds} 轮...")
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for i in range(max_rounds):
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ad_screen = take_screenshot(d, f"tld_ad_check_{int(time.time())}.jpg")
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res = await self.read_image_kit.find_close_button_vlm(ad_screen)
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if res.get("has_ad") and res.get("close_point"):
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close_point = res.get("close_point")
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w, h = d.window_size()
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target_x = int(close_point[0] * w / 1000)
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target_y = int(close_point[1] * h / 1000)
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# 安全校验：绝对不能点击微信小程序的胶囊按钮区 (右上角)
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# 胶囊按钮通常在 x > 80% 宽度 且 y < 100 像素(或 8% 高度) 的区域
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if target_x > w * 0.75 and target_y < 150:
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logger.warning(f"⚠️ 拒绝点击疑似微信胶囊按钮的区域: ({target_x}, {target_y})")
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continue
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logger.info(f"第 {i+1} 轮发现广告: {res.get('reason')}，点击关闭: ({target_x}, {target_y})")
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d.click(target_x, target_y)
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await asyncio.sleep(1.5)
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else:
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logger.info(f"第 {i+1} 轮未发现明显广告，清理结束。")
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if os.path.exists(ad_screen): os.remove(ad_screen)
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break
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if os.path.exists(ad_screen): os.remove(ad_screen)
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async def crawl_list_logic(self, d):
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# [临时禁用] 广告清理逻辑误触严重，先解决主流程问题
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# await self.clear_ads(d)
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# [优化] 向下滚动以刷新/校准地理位置
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# 使用更加显式的 swipe 方式：从屏幕 30% 划到 80%
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popup_screen_path = take_screenshot(d, f"tld_detail_popup_{int(time.time())}.jpg")
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logger.info(f"[详情页] 截图用于检测温馨提示弹窗: {popup_screen_path}")
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template_xczs = os.path.join(os.path.dirname(__file__), "Template", "xczs.jpg")
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template_point = None
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if os.path.exists(template_xczs):
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try:
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match_res = d.image.match(template_xczs)
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if match_res:
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if hasattr(match_res, "point") and match_res.point:
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template_point = match_res.point
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elif isinstance(match_res, dict):
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if match_res.get("point"):
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template_point = match_res["point"]
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elif "x" in match_res and "y" in match_res:
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template_point = (match_res["x"], match_res["y"])
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elif isinstance(match_res, (list, tuple)) and len(match_res) >= 2:
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template_point = (match_res[0], match_res[1])
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if template_point:
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logger.info(f"[详情页] 模板检测到疑似温馨提示弹窗位置: {template_point}")
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else:
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logger.info("[详情页] 模板未能确定温馨提示弹窗位置")
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except Exception as e:
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logger.error(f"[详情页] 模板检测温馨提示弹窗失败: {e}")
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else:
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logger.info(f"[详情页] 温馨提示模板文件不存在: {template_xczs}")
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vlm_popup = {"has_popup": False}
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try:
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vlm_popup = await self.read_image_kit.check_warm_popup_vlm(popup_screen_path)
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except Exception as e:
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logger.error(f"[详情页] VLM 检测温馨提示弹窗失败: {e}")
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has_vlm_popup = isinstance(vlm_popup, dict) and vlm_popup.get("has_popup")
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if template_point and has_vlm_popup:
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click_x = int(template_point[0])
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click_y = int(template_point[1])
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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})")
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debug_popup_path = popup_screen_path.replace(".jpg", f"_xczs_click_{click_x}_{click_y}.jpg")
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try:
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img_popup = read_image(popup_screen_path)
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if img_popup is not None:
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cv2.circle(img_popup, (click_x, click_y), 20, (0, 0, 255), -1)
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save_image(debug_popup_path, img_popup)
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logger.info(f"[详情页] 已生成温馨提示弹窗点击诊断图片: {debug_popup_path}")
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except Exception as e:
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logger.error(f"[详情页] 生成温馨提示弹窗诊断图片失败: {e}")
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try:
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d.click(click_x, click_y)
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await asyncio.sleep(1.5)
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except Exception as e:
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logger.error(f"[详情页] 点击温馨提示“下次再说”失败: {e}")
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else:
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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}")
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w, h = d.window_size()
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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)})")
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d.swipe(w // 2, int(h * 0.3), w // 2, int(h * 0.8), duration=0.5)
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logger.info(f"等待 {WAIT_AFTER_SCROLL} 秒确保位置校准和列表刷新完成...")
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await asyncio.sleep(WAIT_AFTER_SCROLL)
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processed_count = 0
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last_md5 = None
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processed_station_names = set() # 用于列表级去重
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while processed_count < MAX_STATIONS_COUNT:
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# 1. 截图并分析
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screenshot_path = take_screenshot(d, f"tld_list_{int(time.time())}.jpg")
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# 检测是否滚动到底部
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curr_md5 = get_image_content_md5(screenshot_path, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO)
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if last_md5 == curr_md5:
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logger.info("内容无变化，判定已到底部")
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if os.path.exists(screenshot_path): os.remove(screenshot_path)
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break
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last_md5 = curr_md5
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stations = await self.read_image_kit.analyze_station_list(screenshot_path)
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if not stations:
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# 检查是否意外退出了小程序
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is_wrong_page = await self.check_wrong_page(d, screenshot_path)
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if is_wrong_page:
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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...")
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await self.open_app()
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await asyncio.sleep(5)
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continue
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logger.info("本页未检测到场站，尝试滑动...")
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d.swipe_ext("up", scale=SCROLL_DISTANCE_RATIO)
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await asyncio.sleep(WAIT_AFTER_SCROLL)
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continue
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for station in stations:
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if processed_count >= MAX_STATIONS_COUNT:
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break
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name = station.get("name")
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point = station.get("point")
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if not name or not point:
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continue
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if name in processed_station_names:
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logger.info(f"跳过已处理场站: {name}")
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continue
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logger.info(f"处理场站: {name} (坐标: {point})")
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# 点击进入详情
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d.click(point[0], point[1])
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logger.info(f"已点击场站 '{name}'，等待 {WAIT_DETAIL_PAGE_LOAD}s 加载详情页...")
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await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
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# 截图验证是否进入详情页
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detail_check_path = take_screenshot(d, f"tld_detail_check_{int(time.time())}.jpg")
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logger.info(f"详情页快照已保存: {detail_check_path}")
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# 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
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is_wrong_page = await self.check_wrong_page(d, detail_check_path)
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if is_wrong_page:
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logger.warning(f"检测到进入了错误页面，尝试返回列表...")
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# 尝试点击左上角的返回箭头，如果没有，则执行系统 back
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d.click(40, 70) # 特来电通常左上角有返回箭头
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await asyncio.sleep(1.0)
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d.press("back")
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await asyncio.sleep(WAIT_BACK_TO_LIST)
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if os.path.exists(detail_check_path): os.remove(detail_check_path)
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continue
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# 爬取详情
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await self.crawl_detail_logic(d, station)
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processed_station_names.add(name)
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d.press("back")
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await asyncio.sleep(WAIT_BACK_TO_LIST)
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d.press("back")
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await asyncio.sleep(WAIT_BACK_TO_LIST)
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processed_count += 1
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if FIRST_RUN_ONLY_ONE_STATION:
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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。")
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if os.path.exists(screenshot_path):
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os.remove(screenshot_path)
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return
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# 滑动到下一页
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d.swipe_ext("up", scale=SCROLL_DISTANCE_RATIO)
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await asyncio.sleep(WAIT_AFTER_SCROLL)
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if os.path.exists(screenshot_path): os.remove(screenshot_path)
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async def check_wrong_page(self, d, image_path):
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"""
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检查是否误触进入了错误的页面（如：我的卡券、活动页等）
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"""
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data = await self.read_image_kit.check_wrong_page_vlm(image_path)
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is_detail = data.get("is_detail_page", True)
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if not is_detail:
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logger.warning(f"⚠️ 确认进入错误页面: {data.get('page_type')} ({data.get('reason')})")
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return not is_detail
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async def crawl_detail_logic(self, d, station_info):
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"""
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在详情页提取价格和状态信息
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"""
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first_screen_path = take_screenshot(d, f"tld_detail_basic_{int(time.time())}.jpg")
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station_name = station_info.get("name")
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address = station_info.get("address")
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logger.info(f"[详情页] 进入 crawl_detail_logic，场站: {station_name} | 地址: {address}")
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logger.info(f"[详情页] 已截取首屏截图，准备识别基础信息: {first_screen_path}")
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try:
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basic_info = await self.read_image_kit.analyze_detail_basic_info(first_screen_path)
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if isinstance(basic_info, dict):
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name2 = basic_info.get("name")
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addr2 = basic_info.get("address")
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if name2:
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station_name = name2
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if addr2:
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address = addr2
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logger.info(f"[详情页] 同步基础信息识别结果用于写库: {station_name} | {address}")
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except Exception as ex:
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logger.error(f"[详情页] 同步分析详情页基础信息失败: {ex}")
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finally:
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if os.path.exists(first_screen_path):
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try:
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os.remove(first_screen_path)
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except:
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pass
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w, h = d.window_size()
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logger.info("[详情页] 根据用户策略: 多次大幅向上滑动，直到页面基本不再变化")
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last_md5 = None
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stable_count = 0
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max_round = 30
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final_screen_path = None
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from Apps.TeLaiDian.Kit import get_image_content_md5
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for idx in range(max_round):
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start_x = int(w * 0.9)
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start_y = int(h * 0.85)
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end_y = int(h * 0.25)
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logger.info(f"[详情页] 第 {idx + 1} 轮大幅向上滑动: ({start_x}, {start_y}) -> ({start_x}, {end_y})")
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d.swipe(start_x, start_y, start_x, end_y, 0.25)
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await asyncio.sleep(1.0)
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screen_path = take_screenshot(d, f"tld_detail_scan_{int(time.time())}_{idx}.jpg")
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logger.info(f"[详情页] 第 {idx + 1} 轮滑动后的截图: {screen_path}")
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curr_md5 = get_image_content_md5(
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screen_path,
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top_ratio=SAFE_EXCLUDE_RATIO,
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bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO,
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)
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if last_md5 is not None and curr_md5 == last_md5:
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stable_count += 1
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logger.info(f"[详情页] 页面内容连续第 {stable_count} 次无变化，可能已到稳定区域")
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else:
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stable_count = 0
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last_md5 = curr_md5
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final_screen_path = screen_path
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if stable_count >= 2:
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logger.info("[详情页] 检测到页面多次无变化，认为已到达顶部固定区域，提前结束扫描。")
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break
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if not final_screen_path:
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final_screen_path = take_screenshot(d, f"tld_detail_scan_final_{int(time.time())}.jpg")
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logger.info(f"[详情页] 扫描流程未生成截图，使用兜底截图: {final_screen_path}")
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else:
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logger.info(f"[详情页] 使用最终稳定区域截图作为价格页识别输入: {final_screen_path}")
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logger.info("[详情页] 使用固定归一化坐标点击顶部“价格”标签，并点击左侧当前价数字进入全时段电价")
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price_tab_screen = final_screen_path
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entrance_clicked = False
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try:
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tab_x = int(PRICE_TAB_X_NORM * w / 1000)
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tab_y = int(PRICE_TAB_Y_NORM * h / 1000)
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logger.info(f"[详情页] 固定坐标点击价格标签: 归一化({PRICE_TAB_X_NORM}, {PRICE_TAB_Y_NORM}) -> 像素({tab_x}, {tab_y})")
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d.click(tab_x, tab_y)
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await asyncio.sleep(1.0)
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price_tab_screen = take_screenshot(d, f"tld_detail_after_price_tab_{int(time.time())}.jpg")
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logger.info(f"[详情页] 点击价格标签后的界面截图已保存: {price_tab_screen}")
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entry_x = int(PRICE_ENTRY_X_NORM * w / 1000)
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entry_y = int(PRICE_ENTRY_Y_NORM * h / 1000)
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click_x = max(5, min(w - 5, entry_x))
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click_y = max(5, min(h - 5, entry_y))
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debug_click_path = price_tab_screen.replace(
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".jpg",
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f"_click_{tab_x}_{tab_y}_price_{click_x}_{click_y}.jpg"
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)
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try:
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img = read_image(price_tab_screen)
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if img is not None:
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cv2.circle(img, (tab_x, tab_y), 20, (0, 0, 255), -1)
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cv2.circle(img, (click_x, click_y), 20, (0, 0, 255), -1)
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save_image(debug_click_path, img)
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logger.info(f"[详情页] 已生成价格标签与当前价入口红点标记图: {debug_click_path}")
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else:
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logger.warning(f"[详情页] 加载价格页截图失败，无法绘制诊断红点: {price_tab_screen}")
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except Exception as e:
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logger.error(f"[详情页] 生成价格入口点击诊断图片失败: {e}")
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logger.info(f"[详情页] 点击当前价入口: 像素({click_x}, {click_y})，屏幕大小: ({w}, {h})")
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d.click(click_x, click_y)
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entrance_clicked = True
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await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
|
||
except Exception as e:
|
||
logger.error(f"[详情页] 固定坐标点击价格标签或入口失败: {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())
|