256 lines
8.9 KiB
Python
256 lines
8.9 KiB
Python
#!/usr/bin/env python3
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"""
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小唯每日股票信号 — 五粮液(000858)
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=================================
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每日收盘后自动计算MA20状态，推送操作信号
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状态说明:
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- LONG: 收盘价在20日均线上方 → 持仓信号
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- SHORT: 收盘价在20日均线下方 → 空仓信号
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- 无信号: 均线附近震荡
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用法:
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python3 stock_signal.py # 今日五粮液信号
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python3 stock_signal.py --watch # 持续监控模式
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"""
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import json, sys, urllib.request
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from datetime import datetime
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from pathlib import Path
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import numpy as np
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import pandas as pd
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OUTPUT = Path.home() / ".hermes" / "stock_backtest"
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OUTPUT.mkdir(exist_ok=True)
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FEISHU_WEBHOOK = "https://open.feishu.cn/open-apis/bot/v2/hook/446db983-e392-4d2c-bfb8-f9060e5df3ad"
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# 关注股票名称映射（与 stock_portfolio.py 一致）
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STOCK_NAMES = {
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"000858": "五粮液",
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"600519": "贵州茅台",
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"000568": "泸州老窖",
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"002304": "洋河股份",
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"600036": "招商银行",
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"601318": "中国平安",
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"000001": "平安银行",
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}
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def send_feishu(msg):
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payload = json.dumps({"msg_type": "text", "content": {"text": msg}}).encode()
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req = urllib.request.Request(FEISHU_WEBHOOK, data=payload,
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headers={"Content-Type": "application/json"})
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try:
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with urllib.request.urlopen(req, timeout=10):
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pass
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except Exception:
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pass
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def get_data(code, count=30):
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mc = f"sh{code}" if code.startswith("6") else f"sz{code}"
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today = datetime.now().strftime("%Y-%m-%d")
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url = (f"https://web.ifzq.gtimg.cn/appstock/app/fqkline/get"
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f"?_var=kline_dayqfq¶m={mc},day,{today},{today},{count},qfq")
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try:
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text = urllib.request.urlopen(url, timeout=10).read().decode("utf-8")
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data = json.loads(text.replace("kline_dayqfq=", "", 1))
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qfq = (data.get("data", {}).get(mc, {}).get("qfqday") or
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data.get("data", {}).get(mc, {}).get("day") or [])
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rows = []
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for item in qfq:
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if len(item) < 6:
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continue
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try:
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rows.append({"date": item[0],
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"open": float(item[1]), "close": float(item[2]),
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"high": float(item[3]), "low": float(item[4]),
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"volume": float(item[5])})
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except (ValueError, IndexError):
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continue
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df = pd.DataFrame(rows)
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df["date"] = pd.to_datetime(df["date"])
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df.set_index("date", inplace=True)
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df.sort_index(inplace=True)
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return df
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except Exception:
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return None
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def get_long_data(code, start, end):
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"""获取一段历史数据用于计算MA20"""
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mc = f"sh{code}" if code.startswith("6") else f"sz{code}"
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url = (f"https://web.ifzq.gtimg.cn/appstock/app/fqkline/get"
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f"?_var=kline_dayqfq¶m={mc},day,{start},{end},500,qfq")
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try:
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text = urllib.request.urlopen(url, timeout=10).read().decode("utf-8")
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data = json.loads(text.replace("kline_dayqfq=", "", 1))
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qfq = (data.get("data", {}).get(mc, {}).get("qfqday") or
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data.get("data", {}).get(mc, {}).get("day") or [])
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rows = []
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for item in qfq:
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if len(item) < 6:
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continue
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try:
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rows.append({"date": item[0],
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"open": float(item[1]), "close": float(item[2]),
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"high": float(item[3]), "low": float(item[4]),
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"volume": float(item[5])})
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except (ValueError, IndexError):
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continue
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df = pd.DataFrame(rows)
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df["date"] = pd.to_datetime(df["date"])
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df.set_index("date", inplace=True)
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df.sort_index(inplace=True)
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return df
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except Exception:
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return None
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def compute_signal(code="000858", hist_days=60):
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"""计算股票MA20信号"""
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name = STOCK_NAMES.get(code, code)
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end = datetime.now().strftime("%Y-%m-%d")
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start = (datetime.now().replace(year=datetime.now().year-1)).strftime("%Y-%m-%d")
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df = get_long_data(code, "2025-01-01", end)
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if df is None or len(df) < 25:
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return None
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ma20 = df["close"].rolling(20).mean()
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last_close = df["close"].iloc[-1]
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last_ma20 = ma20.iloc[-1]
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prev_close = df["close"].iloc[-2]
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prev_ma20 = ma20.iloc[-2]
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# 计算信号
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if last_close > last_ma20 and prev_close <= prev_ma20:
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signal = "BUY" # 金叉
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signal_text = "🟢 买入信号"
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signal_desc = "收盘价上穿20日均线，金叉买入"
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elif last_close < last_ma20 and prev_close >= prev_ma20:
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signal = "SELL" # 死叉
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signal_text = "🔴 卖出信号"
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signal_desc = "收盘价下穿20日均线，死叉卖出"
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elif last_close > last_ma20:
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signal = "HOLD_LONG"
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signal_text = "🟢 持仓"
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signal_desc = "价格站稳均线上方，持有"
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else:
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signal = "HOLD_SHORT"
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signal_text = "🔴 空仓"
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signal_desc = "价格跌破均线，保持空仓"
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pct_above = (last_close - last_ma20) / last_ma20 * 100
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macd_fast = df["close"].ewm(span=12).mean().iloc[-1]
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macd_slow = df["close"].ewm(span=26).mean().iloc[-1]
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macd_val = macd_fast - macd_slow
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signal_line = pd.Series(df["close"]).ewm(span=12).mean().iloc[-1] - pd.Series(df["close"]).ewm(span=26).mean().iloc[-1]
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signal_line = pd.Series(pd.Series(df["close"]).ewm(span=12).mean() - pd.Series(df["close"]).ewm(span=26).mean()).ewm(span=9).mean().iloc[-1]
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return {
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"code": code,
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"name": name,
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"date": str(df.index[-1].date()),
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"close": last_close,
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"ma20": last_ma20,
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"pct_above_ma": pct_above,
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"signal": signal,
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"signal_text": signal_text,
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"signal_desc": signal_desc,
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"macd": macd_val,
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"signal_line": signal_line,
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}
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def get_price_simple(code):
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"""快速获取当前价格"""
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mc = f"sh{code}" if code.startswith("6") else f"sz{code}"
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try:
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url = f"https://qt.gtimg.cn/q={mc}"
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data = urllib.request.urlopen(url, timeout=5).read()
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text = data.decode("gbk")
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parts = text.split("~")
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if len(parts) > 10:
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return {
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"name": parts[1],
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"code": parts[2],
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"price": float(parts[3]),
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"yesterday": float(parts[4]),
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"change": float(parts[3]) - float(parts[4]),
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"change_pct": (float(parts[3]) - float(parts[4])) / float(parts[4]) * 100,
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}
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except Exception:
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pass
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return None
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def send_daily_signal(code="000858", auto_trade=False):
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"""发送每日信号到飞书，可选自动执行模拟交易"""
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info = get_price_simple(code)
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sig = compute_signal(code)
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name = STOCK_NAMES.get(code, code)
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if info is None:
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send_feishu(f"⚠️ 无法获取{name}({code})行情数据")
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return
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if sig is None:
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send_feishu(f"⚠️ 无法计算{name}({code})技术信号")
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return
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change_emoji = "📈" if info["change"] > 0 else "📉"
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msg = f"""🍶 {name}({code}) 每日信号
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{change_emoji} 今日: {info['price']:.2f} ({info['change']:+.2f}, {info['change_pct']:+.2f}%)
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{sig['signal_text']}
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{sig['signal_desc']}
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均线状态:
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• 收盘价: {sig['close']:.2f}
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• MA20: {sig['ma20']:.2f}
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• 价格偏离: {sig['pct_above_ma']:+.2f}%
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• MACD: {sig['macd']:+.2f} vs Signal {sig['signal_line']:.2f}
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{'✅ 可买入' if sig['signal'] == 'BUY' else '❌ 继续观察' if sig['signal'] == 'HOLD_SHORT' else '⏸️ 持仓观望'}
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生成: {datetime.now().strftime('%Y-%m-%d %H:%M')}
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小唯股票投研 · MA20突破策略"""
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# 信号 → 模拟账户自动执行（打通两套系统）
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if auto_trade:
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import stock_paper
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# v2：弱势行业金叉半仓参与（2026-08-01 回测优化：全拦截损失 α，半仓最优）
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industry = STOCK_NAMES.get(code, "")
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weak_industry = {"白酒", "医药", "通信", "汽车", "地产"} # 与 stock_portfolio.WEAK_TREND_INDUSTRIES 同步
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if sig["signal"] == "BUY" and industry in weak_industry:
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action, detail = ("BUY_HALF", f"弱势行业({industry}动量负)金叉，半仓买入")
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msg += f"\n\n📝 模拟账户: [⚠️ {action}] {detail}"
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else:
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action, detail = stock_paper.execute_signal(sig)
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msg += f"\n\n📝 模拟账户: [{action}] {detail}"
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send_feishu(msg)
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print(msg)
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if __name__ == "__main__":
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code = "000858"
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auto_trade = False
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if "--code" in sys.argv:
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idx = sys.argv.index("--code")
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if idx + 1 < len(sys.argv):
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code = sys.argv[idx + 1]
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if "--paper" in sys.argv:
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auto_trade = True
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if "--watch" in sys.argv:
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print("监控模式: 每60秒检查一次 (Ctrl+C退出)")
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import time
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while True:
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send_daily_signal(code, auto_trade)
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time.sleep(60)
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else:
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send_daily_signal(code, auto_trade) |