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aiData/Apps/XinDianTu/Crawler.py

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# coding=utf-8
import asyncio
import logging
import uuid
import os
import sys
import json
import time
import hashlib
from PIL import Image
# 将项目根目录添加到 sys.path
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)
import uiautomator2 as u2
from Core.BaseCrawler import BaseCrawler
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from Apps.XinDianTu import Kit
from Apps.XinDianTu.Kit import take_screenshot
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from Apps.XinDianTu.FirstPageKit import run_ocr_rect
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from Util.ObsUtil import ObsUploader
from Util.RedisKit import RedisKit
import cv2
from Apps.XinDianTu.Service import XinDianTuService
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from Apps.XinDianTu.ReadImageKit import ReadImageKit
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from Config.Config import (
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OBS_TMP_PREFIX, CDN_DOMAIN, TEMP_IMAGE_DIR
)
from Apps.XinDianTu.Config.Setting import (
SCROLL_DISTANCE_RATIO,
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MAX_STATIONS_COUNT, REDIS_STATION_EXPIRE,
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WAIT_DETAIL_PAGE_LOAD, WAIT_BACK_TO_LIST, WAIT_AFTER_SCROLL,
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SAFE_EXCLUDE_RATIO,
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BOTTOM_SAFE_EXCLUDE_RATIO,
FIRST_RUN_ONLY_ONE_STATION,
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)
# --- 用户配置区域 ---
# 是否保留截图文件(True=保留备查,False=随用随删)
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KEEP_SCREENSHOTS = True
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# [Testing] 是否在启动时清除 Redis 中的场站处理记录
# True: 每次运行前清除记录,方便反复测试同一个场站
# False: 生产模式,保留记录以避免重复爬取
TEST_CLEAR_REDIS = True
# 配置说明:
# SCROLL_DISTANCE_RATIO 控制翻页时的滑动距离(在 Config.py 中修改)。
# 对于华为 Mate 20x 等分辨率较低或屏幕较小的手机,如果发现翻页时跳过了某些场站,
# 请尝试减小 SCROLL_DISTANCE_RATIO(例如设置为 0.4 或 0.3)。
# 这样每次滑动的距离变短,可以确保所有场站都能被完整显示并识别。
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from Apps.XinDianTu.Kit import setup_logger
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logger = setup_logger("StationList")
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class XinDianTuCrawler(BaseCrawler):
"""
新电途小程序爬虫实现
"""
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def __init__(self, service=None):
super().__init__(service)
# 初始化配置参数
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self.max_stations_count = MAX_STATIONS_COUNT
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self.uploader = ObsUploader()
self.redis_kit = RedisKit()
async def start(self):
"""
实现 BaseCrawler 的启动入口
"""
# 兼容旧逻辑,直接调用 main
await main(self.service)
async def open_app(self):
# 实际逻辑在 Opener.py,此处可作为封装层
pass
async def crawl_list(self):
# 实际逻辑在 get_station_list,此处可作为封装层
pass
async def crawl_detail(self, station_info):
pass
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async def is_already_crawled(redis_kit, station_name):
"""
检查场站是否已经爬取过,仅按名称去重
"""
cleaned_name = Kit.clean_station_name(station_name)
if not cleaned_name:
return False
redis_key = f"crawled:xdt:{cleaned_name}"
if await redis_kit.get_data(redis_key):
return True
return False
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async def analyze_prices_background(service, station_name, image_paths, device_info=None):
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"""
后台异步处理价格图片分析
"""
try:
# 使用多图解析并去重
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all_rows = await ReadImageKit.parse_price_schedule_multi(station_name, image_paths, device_info=device_info)
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if all_rows:
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await service.process_price_detail_data(station_name, all_rows)
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logger.info(f"后台处理完成: {station_name} 的分时价格已保存。")
else:
logger.warning(f"后台处理失败: {station_name} 未能解析出价格时段。")
# 处理完成后清理图片
for path in image_paths:
try:
if os.path.exists(path):
os.remove(path)
except:
pass
except Exception as e:
logger.error(f"分析价格后台任务异常 ({station_name}): {e}")
return True
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async def get_station_list(d, service, uploader, max_stations_count=MAX_STATIONS_COUNT):
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"""
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获取场站列表并处理翻页 (异步优化版)
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"""
redis_kit = RedisKit()
window_size = d.window_size()
w, h = window_size[0], window_size[1]
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device_info = d.info
device_info['width'] = w
device_info['height'] = h
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logger.info(f"开始爬取列表,设备: {device_info.get('productName')} | 分辨率: {w}x{h} | 目标数量: {max_stations_count}")
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background_tasks = []
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last_list_md5 = None
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no_new_data_count = 0
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total_encountered_count = 0
total_new_processed_count = 0
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scroll_count = 0
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while total_new_processed_count < max_stations_count:
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scroll_count += 1
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logger.info(f"正在处理第 {scroll_count} 次滚动 (已遇到: {total_encountered_count}, 新采集: {total_new_processed_count}/{max_stations_count})...")
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# 1. 拍摄截图
image_uuid = str(uuid.uuid4())
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screenshot_path = take_screenshot(d, image_uuid, save_dir=TEMP_IMAGE_DIR)
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ad_top_y_norm = 0.78 # 默认的点击边界 (0.78)
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if scroll_count > 1:
ad_top_y_norm = 1.0
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logger.info(f"当前列表页广告安全下边界: {ad_top_y_norm:.2f} (scroll_count={scroll_count})")
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# 检查是否已经滚动到底部 (排除状态栏后,内容与上次一致)
current_md5 = Kit.get_image_content_md5(
screenshot_path,
top_ratio=SAFE_EXCLUDE_RATIO,
bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO
)
if last_list_md5 and current_md5 == last_list_md5:
logger.info("检测到列表核心内容无变化,已到达底部或加载完成,提前结束。")
if os.path.exists(screenshot_path): os.remove(screenshot_path)
break
last_list_md5 = current_md5
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logger.info(f"列表页截图已完成: {screenshot_path}")
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logger.info("正在使用 OCR+LLM 分析场站列表...")
try:
stations_page = await run_ocr_rect(screenshot_path)
except Exception as e:
logger.error(f"OCR+LLM 识别列表页失败: {e}")
stations_page = []
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if not stations_page:
logger.warning("OCR+LLM 未识别到任何场站,跳过当前页")
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continue
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new_stations_processed_in_page = 0
for idx, st in enumerate(stations_page):
station_name = st.get("station_name") or st.get("name")
if not station_name:
continue
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if FIRST_RUN_ONLY_ONE_STATION and scroll_count == 1 and idx > 0:
logger.info("首屏仅处理第一个场站,跳过当前卡片。")
continue
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if total_new_processed_count >= max_stations_count:
break
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total_encountered_count += 1
if await is_already_crawled(redis_kit, station_name):
logger.info(f"场站 {station_name} 匹配到已处理记录,跳过。({total_encountered_count}/{max_stations_count})")
continue
rect = st.get("rect") or []
if not isinstance(rect, (list, tuple)) or len(rect) < 4:
logger.warning(f"场站 '{station_name}' 缺少有效矩形信息,跳过。")
continue
x1, y1, x2, y2 = rect[0], rect[1], rect[2], rect[3]
card_bottom = float(y2) / float(h) if h else 1.0
if card_bottom > ad_top_y_norm:
logger.warning(f"场站 '{station_name}' 被遮挡或太靠近底部 (Bottom {card_bottom:.2f} > {ad_top_y_norm}),留待下次滚动处理。")
total_encountered_count -= 1
continue
click_point = st.get("click_point") or st.get("click") or []
click_x = None
click_y = None
if isinstance(click_point, (list, tuple)) and len(click_point) >= 2:
click_x, click_y = click_point[0], click_point[1]
if click_x is None or click_y is None:
click_x = int((x1 + x2) / 2)
click_y = int((y1 + y2) / 2)
if click_x is None or click_y is None:
logger.warning(f"场站 '{station_name}' 缺少有效点击坐标,跳过。")
continue
busy_list = st.get("busy_list") or []
piles = []
if isinstance(busy_list, list):
for bi in busy_list:
if not isinstance(bi, dict):
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continue
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mode = bi.get("mode") or bi.get("type") or "未知"
idle = bi.get("idle")
total = bi.get("total")
try:
idle_val = int(idle) if idle is not None else 0
except Exception:
idle_val = 0
try:
total_val = int(total) if total is not None else 0
except Exception:
total_val = 0
piles.append(
{
"type": mode,
"total": total_val,
"free": idle_val,
}
)
if piles:
try:
await service.record_station_status(
{
"station_name": station_name,
"piles": piles,
}
)
except Exception as e:
logger.error(f"记录列表页状态失败 ({station_name}): {e}")
current_idx = total_new_processed_count + 1
remaining = max_stations_count - current_idx
logger.info(f"--- [进度: {current_idx}/{max_stations_count}, 剩余: {remaining}] 发现新场站 '{station_name}',开始处理... ---")
new_stations_processed_in_page += 1
total_new_processed_count += 1
logger.info(f"准备处理场站: {station_name}, 点击坐标: ({click_x}, {click_y})")
d.click(int(click_x), int(click_y))
await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
should_back_to_list = True
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detail_uuid = str(uuid.uuid4())
detail_path = take_screenshot(d, detail_uuid, save_dir=TEMP_IMAGE_DIR)
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logger.info(f"已启动后台分析详情页: {station_name}")
task_addr = asyncio.create_task(service.process_station_address(station_name, detail_path, device_info=device_info))
background_tasks.append(task_addr)
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detail_object_key = f"{OBS_TMP_PREFIX}/{detail_uuid}.jpg"
loop = asyncio.get_running_loop()
loop.run_in_executor(None, uploader.upload_file, detail_object_key, detail_path)
before_click_md5 = Kit.get_image_content_md5(detail_path)
click_pos = None
try:
logger.info("正在使用 OCR 识别 '全部时段' 按钮...")
ocr_res = await ReadImageKit.find_price_entrance_ocr(detail_path)
if ocr_res.get("found"):
p = ocr_res["point"]
w, h = d.window_size()
click_pos = (int(p[0] * w / 1000), int(p[1] * h / 1000))
logger.info(f"OCR 成功找到 '全部时段' 按钮: {click_pos}")
if not click_pos:
logger.info("OCR 未找到,降级使用 VL 识别...")
res = await ReadImageKit.find_all_time_button_coordinate(detail_path, device_info=device_info)
if res.get("uia_center_x"):
click_pos = (res.get("uia_center_x"), res.get("uia_center_y"))
logger.info(f"VL 识别成功找到 '全部时段' 按钮: {click_pos}")
if click_pos:
d.click(click_pos[0], click_pos[1])
await asyncio.sleep(0.5)
w, h = d.window_size()
scroll_x = int(w * 0.5)
scroll_top_y = int(h * 0.6)
scroll_bottom_y = int(h * 0.85)
logger.info("从当前时段开始向下浏览价格列表并逐页截图...")
max_scroll_up = 10
price_screenshots = []
for p_idx in range(1, max_scroll_up + 1):
p_uuid = f"{hashlib.md5(station_name.encode('utf-8')).hexdigest()}_p_{p_idx}"
p_path = take_screenshot(d, p_uuid, save_dir=TEMP_IMAGE_DIR)
price_screenshots.append(p_path)
before_up_md5 = Kit.get_image_content_md5(p_path)
d.swipe(scroll_x, scroll_bottom_y, scroll_x, scroll_top_y, 0.2)
await asyncio.sleep(0.3)
check_up_path = take_screenshot(d, f"check_up_{p_idx}", save_dir=TEMP_IMAGE_DIR)
after_up_md5 = Kit.get_image_content_md5(check_up_path)
if os.path.exists(check_up_path):
os.remove(check_up_path)
if before_up_md5 == after_up_md5:
logger.info(f"价格列表已到达顶部 (共抓取页数: {p_idx})")
break
logger.info(f"已启动后台分析价格页: {station_name}")
task_price = asyncio.create_task(
analyze_prices_background(service, station_name, price_screenshots, device_info=device_info)
)
background_tasks.append(task_price)
else:
logger.info(f"场站 {station_name} 经过模板匹配与 VL 识别均未发现 '全部时段' 按钮。")
except Exception as e:
logger.error(f"处理 '全部时段' 按钮点击流程异常: {e}")
if should_back_to_list:
d.press("back")
logger.info(f"等待 {WAIT_BACK_TO_LIST + 1} 秒返回列表...")
await asyncio.sleep(WAIT_BACK_TO_LIST + 1)
cleaned = Kit.clean_station_name(station_name)
await redis_kit.set_data(f"crawled:xdt:{cleaned}", "1", expire=REDIS_STATION_EXPIRE)
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# 如果内层循环已达上限,外层循环也应退出,避免不必要的滑动
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if total_encountered_count >= max_stations_count:
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break
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# 清理已完成的后台任务
done_tasks = [t for t in background_tasks if t.done()]
for t in done_tasks:
if t.exception():
logger.error(f"后台任务异常: {t.exception()}")
background_tasks.remove(t)
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if stations_page and new_stations_processed_in_page == 0:
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no_new_data_count += 1
logger.info(f"本页所有场站均已处理过,连续 {no_new_data_count} 页无新数据。")
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# 【优化】由于滑动步长已调大 (0.5),连续多页重复的可能性降低
if no_new_data_count >= 5:
logger.info("连续 5 页无新数据,判定为已到底或重复循环,提前结束。")
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break
else:
no_new_data_count = 0
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# 6. 翻页
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# 【优化】使用“小步快跑”策略,减小滑动距离以避免跳过场站,并能更平滑地躲避广告
# 步长已在 Setting.py 中统一配置为 SCROLL_DISTANCE_RATIO
logger.info(f"执行翻页滑动 (步长: {SCROLL_DISTANCE_RATIO})...")
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d.swipe_ext("up", scale=SCROLL_DISTANCE_RATIO)
await asyncio.sleep(WAIT_AFTER_SCROLL)
# 等待所有后台任务完成
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if background_tasks:
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logger.info(f"正在等待剩余 {len(background_tasks)} 个后台任务完成...")
await asyncio.gather(*background_tasks, return_exceptions=True)
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logger.info(f"采集任务完成,共遇到 {total_encountered_count} 个场站,新处理 {total_new_processed_count} 个。")
return total_new_processed_count
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def clean_images_dir():
"""清理 Images 目录下除保留文件外的所有文件"""
base_dir = os.path.dirname(os.path.abspath(__file__))
images_dir = os.path.join(base_dir, "Images")
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if not os.path.exists(images_dir):
return
keep_files = {'1.jpg', '2.jpg', '3.jpg', '4.jpg'}
logger.info(f"正在清理 Images 目录 (保留: {keep_files})...")
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deleted_count = 0
for filename in os.listdir(images_dir):
if filename in keep_files:
continue
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file_path = os.path.join(images_dir, filename)
try:
if os.path.isfile(file_path):
os.remove(file_path)
deleted_count += 1
except Exception as e:
logger.warning(f"删除文件失败 {filename}: {e}")
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logger.info(f"清理完成,共删除 {deleted_count} 个文件。")
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async def clean_redis_data(redis_kit):
"""清除 Redis 中的场站处理记录"""
if TEST_CLEAR_REDIS:
logger.info("测试模式开启:正在清除 Redis 中的场站处理记录 (processed_station:*)...")
keys = await redis_kit.keys("processed_station:*")
if keys:
count = await redis_kit.delete(*keys)
logger.info(f"已清除 {count} 条场站处理记录")
else:
logger.info("未发现旧的场站处理记录")
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async def main(service=None, do_cleanup=True):
# 连接设备
d = u2.connect()
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# 初始化服务
should_close_service = False
if service is None:
service = XinDianTuService()
should_close_service = True
# 初始化数据库连接(XinDianTuService 需要)
await service.init_db()
uploader = ObsUploader()
redis_kit = RedisKit()
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# 任务日志记录
from datetime import datetime
task_id = str(uuid.uuid4())
start_time = datetime.now()
operator = "新电途"
# 记录任务开始
try:
await service.db.save("t_crawl_task_log", {
"task_id": task_id,
"operator": operator,
"start_time": start_time,
"status": "running"
}, "task_id")
except Exception as e:
logger.error(f"无法记录任务开始日志: {e}")
total_count = 0
status = "success"
error_msg = None
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try:
if do_cleanup:
# 清理图片目录
clean_images_dir()
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# [Testing] 如果配置为测试模式,启动时清除 Redis 记录
await clean_redis_data(redis_kit)
# 清理过期数据
# await service.cleanup_old_data()
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# 获取场站列表
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total_count = await get_station_list(d, service, uploader, max_stations_count=MAX_STATIONS_COUNT)
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if total_count:
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logger.info("场站列表采集完成。")
else:
logger.warning("未采集到任何场站信息。")
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return True
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except Exception as e:
logger.exception(f"运行过程中出现异常: {e}")
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status = "failed"
error_msg = str(e)
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return False
finally:
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# 记录任务结束
end_time = datetime.now()
duration = int((end_time - start_time).total_seconds())
try:
await service.db.update("t_crawl_task_log", {
"task_id": task_id,
"end_time": end_time,
"duration_seconds": duration,
"station_count": total_count,
"status": status,
"error_msg": error_msg
}, "task_id")
logger.info(f"任务执行日志已更新: {operator} | 耗时: {duration}s | 数量: {total_count} | 状态: {status}")
except Exception as e:
logger.error(f"无法更新任务执行日志: {e}")
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# 关闭数据库连接
if should_close_service:
await service.close_db()
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if __name__ == "__main__":
try:
asyncio.run(main())
except KeyboardInterrupt:
logger.info("程序被用户中断.")
except Exception as e:
logger.exception(f"程序崩溃: {e}")