527 lines
25 KiB
Python
527 lines
25 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, 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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REDIS_STATION_EXPIRE
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)
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from Core.BaseCrawler import BaseCrawler
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from Util.RedisKit import RedisKit
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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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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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self.redis_kit = RedisKit()
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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，支持多轮检测
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"""
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logger.info(f"--- [广告清理] 开始检测，最多尝试 {max_rounds} 轮 ---")
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for i in range(max_rounds):
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round_idx = i + 1
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logger.info(f"[广告清理] 第 {round_idx} 轮：正在截屏分析...")
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ad_screen = take_screenshot(d, f"tld_ad_check_r{round_idx}_{int(time.time())}.jpg")
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try:
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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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reason = res.get("reason", "未提供原因")
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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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logger.info(f"[广告清理] 第 {round_idx} 轮：VLM 发现广告！原因: {reason}")
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logger.info(f"[广告清理] 计划点击坐标: ({target_x}, {target_y})，归一化坐标: {close_point}")
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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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if target_x > w * 0.75 and target_y < 150:
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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。")
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continue
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logger.info(f"[广告清理] 正在执行点击关闭操作...")
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d.click(target_x, target_y)
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# 点击后等待一下，让弹窗消失或下一轮广告弹出
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await asyncio.sleep(2.0)
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else:
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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')}")
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if os.path.exists(ad_screen): os.remove(ad_screen)
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break
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except Exception as e:
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logger.error(f"[广告清理] 第 {round_idx} 轮检测发生异常: {e}")
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finally:
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if os.path.exists(ad_screen): os.remove(ad_screen)
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logger.info("--- [广告清理] 任务结束 ---")
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async def crawl_list_logic(self, d):
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# 1. 启动即清理广告 (已根据要求关闭)
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# await self.clear_ads(d, max_rounds=3)
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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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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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# [优化] 使用 Redis 进行跨运行去重
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cleaned_name = clean_station_name(name)
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redis_key = f"crawled:tld:{cleaned_name}"
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if await self.redis_kit.get_data(redis_key):
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logger.info(f"跳过已处理场站 (Redis): {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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# 标记为已处理
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await self.redis_kit.set_data(redis_key, "1", expire=REDIS_STATION_EXPIRE)
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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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total_piles = None
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free_piles = None
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piles_detail = None
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parking_info = None
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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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if basic_info.get("name"):
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station_name = basic_info.get("name")
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if basic_info.get("address"):
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address = basic_info.get("address")
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# 提取电桩信息
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total_piles = basic_info.get("total_piles")
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free_piles = basic_info.get("free_piles")
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piles_detail = basic_info.get("piles_detail")
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parking_info = basic_info.get("parking_info")
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logger.info(f"[详情页] 基础信息识别结果: {station_name} | {address} | 桩数: {total_piles}/{free_piles} | 停车费: {parking_info}")
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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")
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w, h = d.window_size()
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# 1. 增加等待时间，确保页面加载完成
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logger.info(f"[详情页] 等待 {WAIT_DETAIL_PAGE_LOAD}s 确保页面稳定...")
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await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
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# --- [优化] 小步快跑滚动查找逻辑 ---
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# 目标：通过多次小幅度滚动 + OCR 实时探测，精准捕获“全部时段”入口，避免滑过头
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max_scroll_attempts = 6 # 最大滚动尝试次数
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scroll_step_ratio = 0.3 # 每次滚动的步长（屏幕高度的 30%）
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found_entry = None
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logger.info(f"[详情页] 开始“小步快跑”滚动查找‘全部时段’入口 (最多 {max_scroll_attempts} 次)...")
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for i in range(max_scroll_attempts):
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# 1. 截图识别当前屏
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curr_screen = take_screenshot(d, f"tld_scroll_ocr_{i}_{int(time.time())}.jpg")
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# 2. 尝试 OCR 识别“全部时段”
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entry_data = await self.read_image_kit.find_price_entrance_ocr(curr_screen)
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if entry_data.get("found"):
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logger.info(f"[详情页] 第 {i+1} 次尝试：成功探测到‘全部时段’入口！")
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found_entry = {
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"screen": curr_screen,
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"point": entry_data["point"]
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}
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break
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# 3. 如果没找到，小幅向上滚动一段距离
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if i < max_scroll_attempts - 1:
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logger.info(f"[详情页] 第 {i+1} 次尝试未找到，小幅向上滚动 (步长: {scroll_step_ratio*100}%)...")
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d.swipe(w // 2, int(h * 0.7), w // 2, int(h * (0.7 - scroll_step_ratio)), duration=0.5)
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await asyncio.sleep(1.5) # 滚动后短暂停留
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# 清理过程截图
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if os.path.exists(curr_screen):
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try: os.remove(curr_screen)
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except: pass
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entrance_clicked = False
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try:
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if found_entry:
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price_tab_screen = found_entry["screen"]
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p = found_entry["point"]
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# 2. 点击“全部时段”入口
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entry_x = int(p[0] * w / 1000)
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entry_y = int(p[1] * h / 1000)
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# 安全校验
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if entry_y > h * 0.9:
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logger.warning(f"[详情页] 入口坐标偏低 ({entry_y})，可能在底部遮罩，尝试微调。")
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# 绘制最终点击诊断图
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debug_click_path = price_tab_screen.replace(".jpg", "_final_click.jpg")
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img = read_image(price_tab_screen)
|
||
if img is not None:
|
||
cv2.circle(img, (entry_x, entry_y), 25, (0, 255, 0), -1)
|
||
save_image(debug_click_path, img)
|
||
logger.info(f"[详情页] 已生成最终点击诊断图: {debug_click_path}")
|
||
|
||
logger.info(f"[详情页] 正在点击电价入口: ({entry_x}, {entry_y})")
|
||
d.click(entry_x, entry_y)
|
||
entrance_clicked = True
|
||
await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
|
||
else:
|
||
# 按照用户要求：找不到文字时输出日志、截图并停止程序
|
||
fail_screen = take_screenshot(d, f"tld_ocr_fail_{int(time.time())}.jpg")
|
||
logger.error(f"❌ [OCR失败] 经过 {max_scroll_attempts} 次滚动仍未在页面中找到‘全部时段’文字！")
|
||
logger.error(f"❌ [OCR失败] 最终截图已保存至: {fail_screen}")
|
||
logger.error("❌ [OCR失败] 程序将停止运行，请检查页面内容或识别逻辑。")
|
||
sys.exit(1) # 停止程序
|
||
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,
|
||
total_piles=total_piles,
|
||
free_piles=free_piles,
|
||
piles_detail=piles_detail,
|
||
parking_info=parking_info
|
||
)
|
||
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())
|