376 lines
17 KiB
Python
376 lines
17 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
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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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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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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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# 进入列表页先清理广告
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await self.clear_ads(d)
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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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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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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 (可选：可以加入更复杂的页面特征判断)
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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" 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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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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# 返回列表
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d.press("back")
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await asyncio.sleep(WAIT_BACK_TO_LIST)
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# 返回列表后也检查一下是否有新广告弹出
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await self.clear_ads(d, max_rounds=1)
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processed_count += 1
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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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prompt = """
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分析这张截图，判断这是否是一个“充电站详情页”。
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特征：详情页通常包含场站名称、电价列表、电桩状态等。
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如果页面显示的是“我的卡券”、“优惠券”、“个人中心”或“活动广告”，则不是详情页。
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输出格式为 JSON：
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{
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"is_detail_page": true/false,
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"page_type": "detail" / "coupons" / "ad" / "other",
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"reason": "判断依据"
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}
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"""
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try:
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res_text = await self.read_image_kit.vlm.analyze_image(image_path, prompt)
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json_str = self.read_image_kit.vlm.extract_json(res_text)
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data = json.loads(json_str)
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return not data.get("is_detail_page", True)
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except Exception as e:
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logger.error(f"检查页面类型失败: {e}")
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return False
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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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# 1. 识别第一屏的基础信息 (名称、精确地址)
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first_screen_path = take_screenshot(d, f"tld_detail_basic_{int(time.time())}.jpg")
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basic_info = await self.read_image_kit.analyze_detail_basic_info(first_screen_path)
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station_name = basic_info.get("name") or station_info.get("name")
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address = basic_info.get("address") or station_info.get("address")
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logger.info(f"详情页基础信息识别完成: {station_name} | {address}")
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# 2. 小步快跑寻找价格入口 (结合 CV 和 VLM)
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found_entrance = False
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entrance_point = None
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max_search_steps = 4
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logger.info(f"开始“小步快跑”策略寻找价格入口，最多尝试 {max_search_steps} 次小幅度滑动...")
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for step in range(max_search_steps):
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current_screen = take_screenshot(d, f"tld_search_price_step_{step}.jpg")
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logger.info(f"--- 寻找入口 第 {step+1} 步 ---")
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# 优先使用 CV 快速识别橘红色价格 P0
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logger.info("尝试 CV 识别价格卡片 (P0)...")
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cv_point = detect_price_click_point_cv(current_screen)
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if cv_point:
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logger.info(f"✅ CV 在第 {step+1} 步成功定位入口: {cv_point}")
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entrance_point = cv_point
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found_entrance = True
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else:
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# CV 没找到，使用 VLM 进行深度语义检查
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logger.info("CV 未找到，启动 VLM 深度语义识别...")
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vlm_res = await self.read_image_kit.find_price_entrance_vlm(current_screen)
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if vlm_res.get("found"):
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norm_point = vlm_res.get("point") # [x, y] in 0-1000
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if norm_point and len(norm_point) == 2:
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w, h = d.window_size()
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entrance_point = [int(norm_point[0] * w / 1000), int(norm_point[1] * h / 1000)]
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logger.info(f"✅ VLM 在第 {step+1} 步成功定位入口: {entrance_point} ({vlm_res.get('reason')})")
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found_entrance = True
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else:
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logger.info(f"第 {step+1} 步未发现入口: {vlm_res.get('reason', '未知原因')}")
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# 如果找到入口，进行标注并点击
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if found_entrance and entrance_point:
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debug_flag_path = current_screen.replace(".jpg", "_entrance_found.jpg")
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img_debug = read_image(current_screen)
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if img_debug is not None:
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cv2.circle(img_debug, (entrance_point[0], entrance_point[1]), 25, (0, 255, 0), 5) # 绿色大圆圈
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save_image(debug_flag_path, img_debug)
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logger.info(f"入口位置标注图已保存: {debug_flag_path}")
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logger.info(f"正在点击价格入口: {entrance_point}")
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d.click(entrance_point[0], entrance_point[1])
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await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
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# 清理临时截图
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if os.path.exists(current_screen): os.remove(current_screen)
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break
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# 没找到，小步向上滚动
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if step < max_search_steps - 1:
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scroll_scale = 0.35
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logger.info(f"未发现入口，执行小幅度向上滑动 (scale={scroll_scale})...")
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d.swipe_ext("up", scale=scroll_scale)
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await asyncio.sleep(1.2)
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# 清理临时截图
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if os.path.exists(current_screen): os.remove(current_screen)
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if not found_entrance:
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logger.warning("“小步快跑”策略未能找到价格入口，尝试坐标兜底...")
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w, h = d.window_size()
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d.click(w // 2, int(h * 0.45))
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await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
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# 3. 进入分时电价页面后的处理
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try:
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# 1. 延长等待时间，等待小程序自动定位到当前时段的滚动完成
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logger.info("已点击进入价格详情，等待小程序自动滚动定位完成 (4秒)...")
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await asyncio.sleep(4.0)
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# 2. 回到 00:00 原点：要看到上面的内容，需要“向下拉动”页面（即向上滚动列表）
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logger.info("执行向下拉动，尝试回到 00:00 时段顶部...")
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for i in range(3):
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# swipe_ext("down") 是手指从上往下划，动作是“向下”，结果是页面“向上”滚动
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d.swipe_ext("down", scale=0.8)
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await asyncio.sleep(0.5)
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except Exception as e:
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logger.error(f"处理分时电价页面初始状态失败: {e}")
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# 4. 循环滑动抓取完整分时电价
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all_prices = []
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last_price_md5 = None
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price_page_count = 0
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max_price_pages = 4 # 增加到4页确保覆盖 00:00-24:00
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screenshot_tasks = [] # 用于异步分析图片的任务列表
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temp_screenshots = [] # 记录临时文件以便后续清理
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logger.info("开始循环截图（UI操作优先，后台并行分析）...")
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try:
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while price_page_count < max_price_pages:
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price_screen_path = take_screenshot(d, f"tld_detail_price_{int(time.time())}_{price_page_count}.jpg")
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# 校验页面是否发生滚动变化
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curr_md5 = get_image_content_md5(price_screen_path, top_ratio=0.2, bottom_ratio=0.2)
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if curr_md5 == last_price_md5:
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logger.info("价格页面内容无变化，判定已触底")
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if os.path.exists(price_screen_path): os.remove(price_screen_path)
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break
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last_price_md5 = curr_md5
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temp_screenshots.append(price_screen_path)
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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")
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# 使用 asyncio.create_task 立即在后台开始执行分析
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task = asyncio.create_task(self.read_image_kit.analyze_detail_price(price_screen_path))
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screenshot_tasks.append(task)
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# 向上滚动列表（手指向上划），看后面的时段
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logger.info("向上滚动列表，准备截取下一屏价格...")
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d.swipe_ext("up", scale=0.8)
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await asyncio.sleep(1.0)
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price_page_count += 1
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# 等待所有后台分析任务完成
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if screenshot_tasks:
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logger.info(f"UI 操作已完成，等待 {len(screenshot_tasks)} 个后台分析任务结束...")
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results = await asyncio.gather(*screenshot_tasks, return_exceptions=True)
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for res in results:
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if isinstance(res, Exception):
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logger.error(f"后台分析任务出错: {res}")
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continue
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if res:
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# 深度去重：根据时段 (start, end) 合并
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for p in res:
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is_duplicate = False
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for existing in all_prices:
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if p.get('start') == existing.get('start') and p.get('end') == existing.get('end'):
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is_duplicate = True
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# 字段补全逻辑
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for key in ['price', 'plus_price', 'market_price', 'elec_price', 'service_price']:
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if p.get(key) is not None and (existing.get(key) is None or existing.get(key) == 0):
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existing[key] = p[key]
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break
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if not is_duplicate:
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all_prices.append(p)
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except Exception as e:
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logger.error(f"抓取价格详情过程中发生异常: {e}")
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finally:
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# 无论是否异常，都要确保清理未完成的任务，避免 "never awaited" 警告
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for task in screenshot_tasks:
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if not task.done():
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task.cancel()
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# 清理所有临时截图
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for path in temp_screenshots:
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if os.path.exists(path):
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try:
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os.remove(path)
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except:
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pass
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# 5. 保存数据
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if all_prices:
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station_name_clean = clean_station_name(station_name)
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# 对价格按时间排序
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try:
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all_prices.sort(key=lambda x: x.get('start', '00:00'))
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except:
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pass
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logger.info(f"✅ 场站 {station_name_clean} 共提取到 {len(all_prices)} 条价格信息，准备保存...")
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await self.service.save_station_data(station_name_clean, address, all_prices)
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else:
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logger.warning(f"❌ 未能提取到任何价格信息，请检查页面识别逻辑")
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# 清理临时截图
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for p in [first_screen_path, price_screen_path]:
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if os.path.exists(p): os.remove(p)
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async def crawl_list(self):
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"""
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实现 BaseCrawler 的抽象方法
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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 crawl_detail(self, station_info):
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"""
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实现 BaseCrawler 的抽象方法
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"""
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# 逻辑已在 crawl_list_logic 中通过 crawl_detail_logic 调用
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pass
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async def main(service=None):
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crawler = TeLaiDianCrawler(service=service)
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await crawler.start()
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if __name__ == "__main__":
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asyncio.run(main())
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