508 lines
20 KiB
Python
508 lines
20 KiB
Python
#!/usr/bin/env python3
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"""
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自选股监控预警工具 - OpenClaw集成版
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支持 A股、ETF 及 国际现货黄金 (伦敦金)
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"""
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import requests
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import json
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import time
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import os
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from datetime import datetime
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from pathlib import Path
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# ============ 配置区 ============
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# 监控列表 - 长期挂机通用配置
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# 注意: 伦敦金使用新浪hf_XAU接口，价格为 人民币/克 (约4800元/克 = $2740/盎司)
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#
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# 预警规则设计原则 (适合长期挂机):
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# 1. 成本百分比预警: 基于持仓成本设置 ±10%/±15% 预警，比固定价格更合理
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# 2. 单日涨跌幅预警:
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# - 个股 ±3%~5% (波动大)
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# - ETF ±1.5%~2.5% (波动小)
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# - 黄金 ±2%~3% (24H特殊)
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# 3. 防骚扰: 同类预警30分钟内只发一次
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# 标的类型定义
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STOCK_TYPE = {
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"INDIVIDUAL": "individual", # 个股
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"ETF": "etf", # ETF
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"GOLD": "gold" # 黄金/贵金属
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}
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WATCHLIST = [
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# ===== 用户自定义监控个股 =====
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{
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"code": "000630",
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"name": "铜陵有色",
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"market": "sz",
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"type": "individual",
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"cost": 7.00, # 参考成本价
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"alerts": {
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"change_pct_above": 5.0, # 日内涨超 5% 预警
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"change_pct_below": -5.0, # 日内跌超 5% 预警
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"volume_surge": 2.0 # 成交量异动
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}
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},
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{
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"code": "688313",
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"name": "仕佳光子",
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"market": "sh",
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"type": "individual",
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"cost": 15.00, # 参考成本价（待确认）
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"alerts": {
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"change_pct_above": 5.0, # 日内涨超 5% 预警
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"change_pct_below": -5.0, # 日内跌超 5% 预警
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"volume_surge": 2.0 # 成交量异动
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}
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},
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{
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"code": "600096",
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"name": "云天化",
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"market": "sh",
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"type": "individual",
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"cost": 42.00, # 老大确认的实际成本价
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"alerts": {
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"change_pct_above": 5.0, # 日内涨超 5% 预警
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"change_pct_below": -5.0, # 日内跌超 5% 预警
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"volume_surge": 2.0 # 成交量异动
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}
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},
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{
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"code": "002195",
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"name": "岩山科技",
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"market": "sz",
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"type": "individual",
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"cost": 10.68, # 200 股，成本 10.68 元
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"alerts": {
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"cost_pct_above": 5.0, # 盈利超 5% 快跑 (目标价 ¥11.21)
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"change_pct_above": 5.0, # 日内涨超 5% 预警
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"change_pct_below": -5.0, # 日内跌超 5% 预警
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"volume_surge": 2.0 # 成交量异动
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}
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}
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]
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# 智能频率配置
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SMART_SCHEDULE = {
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"market_open": {"hours": [(9, 30), (11, 30), (13, 0), (15, 0)], "interval": 300}, # 交易时间: 5分钟
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"after_hours": {"interval": 1800}, # 收盘后: 30分钟
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"night": {"hours": [(0, 0), (8, 0)], "interval": 3600}, # 凌晨: 1小时(仅伦敦金)
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}
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# ============ 核心代码 ============
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class StockAlert:
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def __init__(self):
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self.prev_data = {}
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self.alert_log = []
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self.session = requests.Session()
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self.session.headers.update({"User-Agent": "Mozilla/5.0"})
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def should_run_now(self):
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"""智能频率控制: 判断当前是否应该执行监控 (基于北京时间)"""
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# 服务器在纽约(EST)，中国股市用北京时间(CST = EST + 13小时)
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from datetime import timedelta
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now = datetime.now() + timedelta(hours=13) # 转换成北京时间
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hour, minute = now.hour, now.minute
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time_val = hour * 100 + minute
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weekday = now.weekday()
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# 周末只监控伦敦金
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if weekday >= 5: # 周六日
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return {"run": True, "mode": "weekend", "stocks": [s for s in WATCHLIST if s['market'] == 'fx']}
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# 交易时间 (9:30-11:30, 13:00-15:00)
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morning_session = 930 <= time_val <= 1130
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afternoon_session = 1300 <= time_val <= 1500
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if morning_session or afternoon_session:
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return {"run": True, "mode": "market", "stocks": WATCHLIST, "interval": 300}
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# 午休 (11:30-13:00)
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if 1130 < time_val < 1300:
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return {"run": True, "mode": "lunch", "stocks": WATCHLIST, "interval": 600} # 10分钟
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# 收盘后 (15:00-24:00)
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if 1500 <= time_val <= 2359:
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return {"run": True, "mode": "after_hours", "stocks": WATCHLIST, "interval": 1800} # 30分钟
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# 凌晨 (0:00-9:30)
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if 0 <= time_val < 930:
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return {"run": True, "mode": "night", "stocks": [s for s in WATCHLIST if s['market'] == 'fx'], "interval": 3600} # 1小时
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return {"run": False}
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def fetch_eastmoney_kline(self, symbol, market):
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"""获取最新日K线数据 (收盘后也能获取收盘价)"""
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secid = f"{market}.{symbol}"
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url = "https://push2his.eastmoney.com/api/qt/stock/kline/get"
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params = {
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'secid': secid,
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'fields1': 'f1,f2,f3,f4,f5,f6',
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'fields2': 'f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61',
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'klt': '101', # 日线
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'fqt': '0',
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'end': '20500101',
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'lmt': '2' # 取最近2天，用于计算涨跌幅
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}
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try:
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resp = self.session.get(url, params=params, timeout=10)
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data = resp.json()
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klines = data.get('data', {}).get('klines', [])
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if len(klines) >= 1:
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# 格式: 日期,开盘,收盘,最高,最低,成交量,成交额,振幅,涨跌幅,涨跌额,换手率
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today = klines[-1].split(',')
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prev_close = float(today[2]) # 昨收
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if len(klines) >= 2:
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prev_close = float(klines[-2].split(',')[2]) # 前一天收盘
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return {
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'name': data.get('data', {}).get('name', symbol),
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'price': float(today[2]), # 收盘
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'prev_close': prev_close,
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'volume': int(float(today[5])),
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'amount': float(today[6]),
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'date': today[0],
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'time': '15:00:00'
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}
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except Exception as e:
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print(f"东财K线获取失败 {symbol}: {e}")
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return None
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def fetch_volume_ma5(self, symbol, market):
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"""获取5日平均成交量"""
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secid = f"{market}.{symbol}"
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url = "https://push2his.eastmoney.com/api/qt/stock/kline/get"
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params = {
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'secid': secid,
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'fields1': 'f1,f2,f3,f4,f5,f6',
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'fields2': 'f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61',
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'klt': '101',
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'fqt': '0',
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'end': '20500101',
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'lmt': '6' # 取最近6天(今天+前5天)
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}
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try:
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resp = self.session.get(url, params=params, timeout=10)
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data = resp.json()
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klines = data.get('data', {}).get('klines', [])
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if len(klines) >= 2:
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# 计算前5日平均成交量(不含今天)
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volumes = []
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for k in klines[:-1]: # 排除最后一天(今天)
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p = k.split(',')
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volumes.append(float(p[5])) # 成交量
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return sum(volumes) / len(volumes) if volumes else 0
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except Exception as e:
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print(f"获取均量失败 {symbol}: {e}")
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return 0
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def fetch_ma_data(self, symbol, market):
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"""获取均线数据 (MA5, MA10, MA20) 和 RSI"""
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secid = f"{market}.{symbol}"
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url = "https://push2his.eastmoney.com/api/qt/stock/kline/get"
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params = {
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'secid': secid,
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'fields1': 'f1,f2,f3,f4,f5,f6',
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'fields2': 'f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61',
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'klt': '101',
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'fqt': '0',
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'end': '20500101',
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'lmt': '30' # 取最近30天计算MA20和RSI
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}
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try:
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resp = self.session.get(url, params=params, timeout=10)
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data = resp.json()
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klines = data.get('data', {}).get('klines', [])
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if len(klines) >= 20:
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closes = []
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for k in klines:
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p = k.split(',')
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closes.append(float(p[2])) # 收盘价
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# 计算均线
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ma5 = sum(closes[-5:]) / 5
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ma10 = sum(closes[-10:]) / 10
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ma20 = sum(closes[-20:]) / 20
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# 判断均线趋势
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prev_ma5 = sum(closes[-6:-1]) / 5
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prev_ma10 = sum(closes[-11:-1]) / 10
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# 计算RSI(14)
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rsi = self._calculate_rsi(closes, 14)
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return {
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'MA5': ma5,
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'MA10': ma10,
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'MA20': ma20,
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'MA5_trend': 'up' if ma5 > prev_ma5 else 'down',
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'MA10_trend': 'up' if ma10 > prev_ma10 else 'down',
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'golden_cross': prev_ma5 <= prev_ma10 and ma5 > ma10,
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'death_cross': prev_ma5 >= prev_ma10 and ma5 < ma10,
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'RSI': rsi,
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'RSI_overbought': rsi > 70 if rsi else False,
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'RSI_oversold': rsi < 30 if rsi else False
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}
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except Exception as e:
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print(f"获取均线失败 {symbol}: {e}")
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return None
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def _calculate_rsi(self, closes, period=14):
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"""计算RSI指标"""
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if len(closes) < period + 1:
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return None
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gains = []
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losses = []
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for i in range(1, period + 1):
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change = closes[-i] - closes[-i-1]
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if change > 0:
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gains.append(change)
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losses.append(0)
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else:
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gains.append(0)
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losses.append(abs(change))
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avg_gain = sum(gains) / period
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avg_loss = sum(losses) / period
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if avg_loss == 0:
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return 100
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rs = avg_gain / avg_loss
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rsi = 100 - (100 / (1 + rs))
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return round(rsi, 2)
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def fetch_tencent_realtime(self, stocks):
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"""获取实时行情 (腾讯财经接口，更稳定)"""
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stock_list = [s for s in stocks if s['market'] != 'fx']
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fx_list = [s for s in stocks if s['market'] == 'fx']
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results = {}
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# 1. A 股/ETF - 腾讯财经接口
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if stock_list:
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for stock in stock_list:
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code = f"{stock['market']}{stock['code']}"
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url = f"http://qt.gtimg.cn/q={code}"
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try:
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resp = self.session.get(url, timeout=5)
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resp.encoding = 'gbk'
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data = resp.text.strip()
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if '="' not in data:
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continue
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parts = data.strip('"').split('~')
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start_idx = 0
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for j, p in enumerate(parts):
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if p.isdigit() and len(p) == 2:
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start_idx = j
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break
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if len(parts) > start_idx + 20:
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current = float(parts[start_idx+3])
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prev_close = float(parts[start_idx+4])
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open_p = float(parts[start_idx+5])
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change = 0
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change_pct = 0
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high = 0
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low = 0
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for j in range(len(parts)-5):
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try:
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if parts[j].startswith('-') and '.' in parts[j]:
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v1 = float(parts[j])
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v2 = float(parts[j+1])
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if -10 < v2 < 10:
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change = v1
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change_pct = v2
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high = float(parts[j+2])
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low = float(parts[j+3])
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break
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except:
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continue
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results[stock['code']] = {
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'name': parts[start_idx+1],
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'price': current,
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'prev_close': prev_close,
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'open': open_p,
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'high': high,
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'low': low,
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'volume': 0,
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'amount': 0,
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'date': datetime.now().strftime('%Y-%m-%d'),
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'time': datetime.now().strftime('%H:%M:%S')
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}
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print(f"✅ {stock['name']} ({stock['code']}): ¥{current:.2f}")
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except Exception as e:
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print(f"腾讯行情获取失败 {stock['code']}: {e}")
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# 2. 伦敦金 (保留原逻辑)
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if fx_list:
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url = "https://hq.sinajs.cn/list=hf_XAU"
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try:
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resp = self.session.get(url, timeout=5)
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line = resp.text.strip()
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if '"' in line:
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data_str = line[line.index('"')+1 : line.rindex('"')]
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p = data_str.split(',')
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if len(p) >= 13:
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price = float(p[0])
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results['XAU'] = {
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'name': '伦敦金',
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'price': price,
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'prev_close': float(p[7]),
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'volume': 0, 'amount': 0,
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'date': datetime.now().strftime('%Y-%m-%d'),
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'time': p[6]
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}
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except Exception as e:
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print(f"伦敦金获取失败：{e}")
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return results
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def record_alert(self, code, icon):
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"""记录预警日志 (简化版)"""
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# 简单打印日志，实际可以写入文件
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print(f" 📝 预警记录：{code} - {icon}")
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def check_alerts(self, stock_config, data):
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"""检查预警条件 (返回格式：[(icon, text), ...], level)"""
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alerts = []
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code = stock_config['code']
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cfg = stock_config.get('alerts', {})
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cost = stock_config.get('cost', 0)
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price = data['price']
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prev_close = data['prev_close']
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change_pct = ((price - prev_close) / prev_close) * 100 if prev_close else 0
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# 1. 成本百分比预警
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if cost > 0:
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if 'cost_pct_above' in cfg:
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threshold = cost * (1 + cfg['cost_pct_above'] / 100)
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if price >= threshold:
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alerts.append(("🎯", f"盈利 {cfg['cost_pct_above']}% (目标价 ¥{threshold:.2f})"))
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if 'cost_pct_below' in cfg:
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threshold = cost * (1 + cfg['cost_pct_below'] / 100)
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if price <= threshold:
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alerts.append(("📉", f"亏损 {abs(cfg['cost_pct_below'])}% (止损价 ¥{threshold:.2f})"))
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# 2. 日内涨跌幅预警
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if 'change_pct_above' in cfg and change_pct >= cfg['change_pct_above']:
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alerts.append(("📈", f"日内大涨 {change_pct:.2f}% (阈值 {cfg['change_pct_above']}%)"))
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if 'change_pct_below' in cfg and change_pct <= cfg['change_pct_below']:
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alerts.append(("📉", f"日内大跌 {change_pct:.2f}% (阈值 {cfg['change_pct_below']}%)"))
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# 确定预警级别
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if len(alerts) >= 3:
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level = "critical"
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elif len(alerts) >= 2:
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level = "warning"
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elif len(alerts) >= 1:
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level = "info"
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else:
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level = "none"
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return alerts, level
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def fetch_news(self, symbol):
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"""抓取个股最近新闻 (新浪/东财聚合) - 简化版"""
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try:
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# 使用东财个股新闻API
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url = f"https://emweb.securities.eastmoney.com/PC_HSF10/CompanySurvey/CompanySurveyAjax"
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params = {"code": symbol}
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resp = self.session.get(url, params=params, timeout=5)
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return ["新闻模块已就绪 (市场收盘中)"]
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except:
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return []
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def run_once(self, smart_mode=True):
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"""执行监控 (支持智能频率)"""
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if smart_mode:
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schedule = self.should_run_now()
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if not schedule.get("run"):
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return []
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stocks_to_check = schedule.get("stocks", WATCHLIST)
|
||
mode = schedule.get("mode", "normal")
|
||
|
||
# 只在特定模式打印日志
|
||
if mode in ["market", "weekend"]:
|
||
print(f"[{datetime.now().strftime('%H:%M')}] {mode}模式扫描 {len(stocks_to_check)} 只标的...")
|
||
else:
|
||
stocks_to_check = WATCHLIST
|
||
|
||
data_map = self.fetch_tencent_realtime(stocks_to_check)
|
||
triggered = []
|
||
|
||
for stock in stocks_to_check:
|
||
code = stock['code']
|
||
if code not in data_map: continue
|
||
|
||
data = data_map[code]
|
||
|
||
# 数据有效性检查
|
||
if data['price'] <= 0 or data['prev_close'] <= 0:
|
||
continue
|
||
|
||
alerts, level = self.check_alerts(stock, data)
|
||
|
||
if alerts:
|
||
change_pct = (data['price'] - data['prev_close']) / data['prev_close'] * 100 if data['prev_close'] else 0
|
||
|
||
# 中国习惯: 红色=上涨, 绿色=下跌
|
||
if change_pct > 0:
|
||
color_emoji = "🔴" # 红涨
|
||
elif change_pct < 0:
|
||
color_emoji = "🟢" # 绿跌
|
||
else:
|
||
color_emoji = "⚪"
|
||
|
||
# 预警级别标识
|
||
level_icons = {
|
||
"critical": "🚨", # 紧急
|
||
"warning": "⚠️", # 警告
|
||
"info": "📢" # 提醒
|
||
}
|
||
level_icon = level_icons.get(level, "📢")
|
||
level_text = {"critical": "【紧急】", "warning": "【警告】", "info": "【提醒】"}.get(level, "")
|
||
|
||
msg = f"<b>{level_icon} {level_text}{color_emoji} {stock['name']} ({code})</b>\n"
|
||
msg += f"━━━━━━━━━━━━━━━━━━━━\n"
|
||
msg += f"💰 当前价格: <b>{data['price']:.2f}</b> ({change_pct:+.2f}%)\n"
|
||
|
||
# 显示持仓盈亏
|
||
cost = stock.get('cost', 0)
|
||
if cost > 0:
|
||
cost_change = (data['price'] - cost) / cost * 100
|
||
profit_icon = "🔴+" if cost_change > 0 else "🟢"
|
||
msg += f"📊 持仓成本: ¥{cost:.2f} | 盈亏: {profit_icon}{cost_change:.2f}%\n"
|
||
|
||
msg += f"\n🎯 触发预警 ({len(alerts)}项):\n"
|
||
for _, text in alerts:
|
||
msg += f" • {text}\n"
|
||
self.record_alert(code, _)
|
||
|
||
# Pro版：集成智能分析
|
||
try:
|
||
from analyser import StockAnalyser
|
||
analyser = StockAnalyser()
|
||
insight = analyser.generate_insight(stock, {
|
||
'price': data['price'],
|
||
'change_pct': change_pct
|
||
}, alerts)
|
||
msg += f"\n{insight}"
|
||
except Exception:
|
||
pass
|
||
|
||
triggered.append(msg)
|
||
|
||
return triggered
|
||
|
||
if __name__ == '__main__':
|
||
monitor = StockAlert()
|
||
for alert in monitor.run_once():
|
||
print(alert)
|