aiData/Apps/TeLaiDian/Crawler.py

# coding=utf-8
import asyncio
import asyncio
import os
import sys
import time
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
)
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")

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 crawl_list_logic(self, d):
        processed_count = 0
        last_md5 = None
        
        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:
                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
                
                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 (可选：可以加入更复杂的页面特征判断)
                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}")

                # 爬取详情
                await self.crawl_detail_logic(d, station)
                
                # 返回列表
                d.press("back")
                await asyncio.sleep(WAIT_BACK_TO_LIST)
                processed_count += 1
            
            # 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 crawl_detail_logic(self, d, station_info):
        """
        在详情页提取价格和状态信息
        """
        # 1. 识别第一屏的基础信息 (名称、精确地址)
        first_screen_path = take_screenshot(d, f"tld_detail_basic_{int(time.time())}.jpg")
        basic_info = await self.read_image_kit.analyze_detail_basic_info(first_screen_path)
        
        station_name = basic_info.get("name") or station_info.get("name")
        address = basic_info.get("address") or station_info.get("address")
        logger.info(f"详情页基础信息识别完成: {station_name} | {address}")

        # 2. 向上滑动以露出价格按钮
        logger.info(f"执行滑动操作以显示价格按钮 (距离比例: {DETAIL_SCROLL_DISTANCE_RATIO})...")
        # 从屏幕中间向上滑动
        d.swipe_ext("up", scale=DETAIL_SCROLL_DISTANCE_RATIO)
        await asyncio.sleep(1.5)

        # 3. 点击“价格信息”区域 (识别橘红色价格 P0)
        price_button_screen = take_screenshot(d, f"tld_before_price_click_{int(time.time())}.jpg")
        logger.info("正在通过 CV 寻找橘红色价格区域 (P0)...")
        
        click_point = detect_price_click_point_cv(price_button_screen)
        
        # 调试：生成点击点标注图
        if click_point:
            debug_flag_path = price_button_screen.replace(".jpg", "_click_debug.jpg")
            img_debug = read_image(price_button_screen)
            if img_debug is not None:
                cv2.circle(img_debug, (click_point[0], click_point[1]), 20, (0, 0, 255), -1) # 红色大圆点
                cv2.line(img_debug, (click_point[0]-40, click_point[1]), (click_point[0]+40, click_point[1]), (255, 255, 255), 3)
                cv2.line(img_debug, (click_point[0], click_point[1]-40), (click_point[0], click_point[1]+40), (255, 255, 255), 3)
                save_image(debug_flag_path, img_debug)
                logger.info(f"点击点调试图已保存: {debug_flag_path}")
        
        try:
            if click_point:
                logger.info(f"CV 成功定位价格区域，点击坐标: {click_point}")
                d.click(click_point[0], click_point[1])
                await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
            else:
                logger.warning("CV 未能定位价格区域，尝试模板匹配兜底...")
                template_path = os.path.join(project_root, "Apps", "TeLaiDian", "Template", "jgxx.jpg")
                match = d.image.match(template_path)
                if match:
                    d.image.click(template_path)
                else:
                    logger.warning("模板匹配也失败，执行坐标兜底...")
                    w, h = d.window_size()
                    d.click(w // 2, int(h * 0.45)) # 滑动后价格通常在屏幕中上部
                await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
        except Exception as e:
            logger.error(f"点击价格区域失败: {e}")
        finally:
            if os.path.exists(price_button_screen): os.remove(price_button_screen)

        # 4. 循环滑动抓取完整分时电价
        all_prices = []
        last_price_md5 = None
        price_page_count = 0
        max_price_pages = 3 # 分时电价通常不会超过3页

        logger.info("开始循环滑动抓取完整分时电价...")
        
        while price_page_count < max_price_pages:
            price_screen_path = take_screenshot(d, f"tld_detail_price_{int(time.time())}.jpg")
            
            # 校验页面是否发生滚动变化
            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

            logger.info(f"正在分析价格详情页第 {price_page_count + 1} 页: {price_screen_path}")
            page_prices = await self.read_image_kit.analyze_detail_price(price_screen_path)
            
            if page_prices:
                # 简单去重：根据时段合并
                for p in page_prices:
                    if p not in all_prices:
                        all_prices.append(p)
            
            # 向上滑动一点点，继续抓取
            d.swipe_ext("up", scale=0.6)
            await asyncio.sleep(1.5)
            price_page_count += 1
            
            # 清理临时截图
            if os.path.exists(price_screen_path): os.remove(price_screen_path)

        # 5. 保存数据
        if all_prices:
            station_name_clean = clean_station_name(station_name)
            # 对价格按时间排序
            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")
        
        # 清理临时截图
        for p in [first_screen_path, price_screen_path]:
            if os.path.exists(p): os.remove(p)

    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())