feat: 宏观指数采集独立(macro_index_collector) + 莫荷宏观预警系统入库
- 重建 macro_index_collector.py: 原macro_context_collector(index采集)独立 避免与莫荷的 macro_context_collector(宏观新闻采集)冲突 - 纳入莫荷的宏观预警系统: divergence_detector.py — 跨市场背离监测 macro_context_collector.py — 宏观新闻采集+红绿灯(莫荷版) macro_signal_consumer.py — 宏观风险信号消费 - cron修正: 宏观采集-早/午间 → macro_index_collector.py
This commit is contained in:
知微
@@ -0,0 +1,333 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
divergence_detector.py — 跨市场背离监测器（no_agent）
|
||||
|
||||
每30分钟检测：
|
||||
1. 科创50 vs 恒指 → 科技股超买/超卖信号
|
||||
2. A/H 隐含溢价 → 内外资分歧度
|
||||
3. 上证50 vs 创业板 → 风格轮动信号
|
||||
4. 恒指 vs 国企指数 → 离岸市场情绪
|
||||
5. 指数连涨/连跌天数 → 趋势延续/衰竭
|
||||
|
||||
输出：
|
||||
- HIGH/medium divergence → 写入 signal_news (source=divergence_watch)
|
||||
- 状态文件 macro_divergence_state.json
|
||||
- no_agent: 有信号才出声
|
||||
"""
|
||||
import sys, json, re, datetime, os, urllib.request
|
||||
|
||||
from pathlib import Path
|
||||
|
||||
BASE = Path("/home/hmo/MoFin")
|
||||
DATA = BASE / "data"
|
||||
DB_PATH = DATA / "mofin.db"
|
||||
STATE_PATH = DATA / "macro_divergence_state.json"
|
||||
|
||||
# ── 监测的指数 ──
|
||||
INDEX_CODES = {
|
||||
"上证指数": "sh000001",
|
||||
"深证成指": "sz399001",
|
||||
"创业板指": "sz399006",
|
||||
"科创50": "sh000688",
|
||||
"上证50": "sh000016",
|
||||
"沪深300": "sh000300",
|
||||
"恒生指数": "hkHSI",
|
||||
"国企指数": "hkHSCEI",
|
||||
}
|
||||
|
||||
# ── 背离阈值 ──
|
||||
DIVERGENCE_STRONG = 5.0 # >5% → strong信号
|
||||
DIVERGENCE_MODERATE = 3.0 # >3% → moderate信号
|
||||
STREAK_DAYS = 3 # 连涨/连跌3天 → 信号
|
||||
|
||||
def fetch_indices():
|
||||
"""获取所有指数实时数据"""
|
||||
symbols = list(INDEX_CODES.values())
|
||||
url = f"http://qt.gtimg.cn/q={','.join(symbols)}"
|
||||
try:
|
||||
r = urllib.request.urlopen(url, timeout=10)
|
||||
text = r.read().decode("gbk")
|
||||
except Exception as e:
|
||||
print(f"[DIVERGE] 采集失败: {e}", file=sys.stderr)
|
||||
return {}
|
||||
|
||||
indices = {}
|
||||
for line in text.strip().split("\n"):
|
||||
line = line.strip()
|
||||
if not line or "=" not in line:
|
||||
continue
|
||||
try:
|
||||
sym = line.split("=", 1)[0].strip().lstrip("v_")
|
||||
raw = line.split("=", 1)[1].strip().strip('"').strip(";")
|
||||
fields = raw.split("~")
|
||||
if len(fields) < 35:
|
||||
continue
|
||||
name = fields[1]
|
||||
price = float(fields[3]) if fields[3].strip() else 0
|
||||
close = float(fields[4]) if fields[4].strip() else 0
|
||||
change_pct = ((price - close) / close * 100) if close else 0
|
||||
high = float(fields[33]) if fields[33].strip() else 0
|
||||
low = float(fields[34]) if fields[34].strip() else 0
|
||||
timestamp = fields[30] if len(fields) > 30 else ""
|
||||
indices[sym] = {
|
||||
"name": name,
|
||||
"price": price,
|
||||
"close": close,
|
||||
"change_pct": round(change_pct, 2),
|
||||
"high": high,
|
||||
"low": low,
|
||||
"timestamp": timestamp,
|
||||
}
|
||||
except Exception:
|
||||
continue
|
||||
return indices
|
||||
|
||||
def load_history():
|
||||
"""从MACRO_CONTEXT_LOG加载前几天的指数数据"""
|
||||
try:
|
||||
import sqlite3
|
||||
conn = sqlite3.connect(str(DB_PATH))
|
||||
rows = conn.execute(
|
||||
"SELECT indices, created_at FROM macro_context_log "
|
||||
"WHERE has_valid_data=1 ORDER BY created_at DESC LIMIT 5"
|
||||
).fetchall()
|
||||
conn.close()
|
||||
history = []
|
||||
for row in rows:
|
||||
idx_data = json.loads(row[0]) if row[0] else {}
|
||||
history.append({
|
||||
"indices": idx_data,
|
||||
"timestamp": row[1],
|
||||
})
|
||||
return history
|
||||
except Exception:
|
||||
return []
|
||||
|
||||
def detect_divergences(indices, history):
|
||||
"""
|
||||
检测跨市场背离信号
|
||||
返回: list of signal dicts {type, level, desc, pairs}
|
||||
"""
|
||||
signals = []
|
||||
|
||||
def get(name):
|
||||
"""按中文名找指数"""
|
||||
sym = INDEX_CODES.get(name)
|
||||
if sym and sym in indices:
|
||||
return indices[sym]
|
||||
# 模糊匹配
|
||||
for s, idx in indices.items():
|
||||
if name in idx.get("name", ""):
|
||||
return idx
|
||||
return None
|
||||
|
||||
sh_comp = get("上证指数")
|
||||
sz_comp = get("深证成指")
|
||||
cyb = get("创业板指")
|
||||
kc = get("科创50")
|
||||
sz50 = get("上证50")
|
||||
hs300 = get("沪深300")
|
||||
hsi = get("恒生指数")
|
||||
hscei = get("国企指数")
|
||||
|
||||
# ── 信号1: 科创50 vs 恒指（科技股vs国际资本）──
|
||||
if kc and hsi:
|
||||
kc_chg = kc["change_pct"]
|
||||
hsi_chg = hsi["change_pct"]
|
||||
divergence = abs(kc_chg - hsi_chg)
|
||||
if divergence > DIVERGENCE_STRONG:
|
||||
signals.append({
|
||||
"type": "a_h_tech_divergence",
|
||||
"level": "high",
|
||||
"desc": f"科创50({kc_chg:+.1f}%) vs 恒指({hsi_chg:+.1f}%) 背离{divergence:.1f}个百分点",
|
||||
"pairs": [kc, hsi],
|
||||
"direction": "risk" if kc_chg > hsi_chg else "opportunity",
|
||||
})
|
||||
elif divergence > DIVERGENCE_MODERATE:
|
||||
signals.append({
|
||||
"type": "a_h_tech_divergence",
|
||||
"level": "medium",
|
||||
"desc": f"科创50({kc_chg:+.1f}%) vs 恒指({hsi_chg:+.1f}%) 背离{divergence:.1f}个百分点",
|
||||
"pairs": [kc, hsi],
|
||||
"direction": "risk" if kc_chg > hsi_chg else "opportunity",
|
||||
})
|
||||
|
||||
# ── 信号2: 上证50 vs 创业板（价值vs成长）──
|
||||
if sz50 and cyb:
|
||||
sz50_chg = sz50["change_pct"]
|
||||
cyb_chg = cyb["change_pct"]
|
||||
divergence = abs(sz50_chg - cyb_chg)
|
||||
if divergence > DIVERGENCE_STRONG:
|
||||
direction = "opportunity" if sz50_chg > cyb_chg else "risk"
|
||||
signals.append({
|
||||
"type": "value_growth_divergence",
|
||||
"level": "high",
|
||||
"desc": f"上证50({sz50_chg:+.1f}%) vs 创业板({cyb_chg:+.1f}%) 背离{divergence:.1f}个百分点",
|
||||
"pairs": [sz50, cyb],
|
||||
"direction": direction,
|
||||
})
|
||||
elif divergence > DIVERGENCE_MODERATE:
|
||||
direction = "opportunity" if sz50_chg > cyb_chg else "risk"
|
||||
signals.append({
|
||||
"type": "value_growth_divergence",
|
||||
"level": "medium",
|
||||
"desc": f"上证50({sz50_chg:+.1f}%) vs 创业板({cyb_chg:+.1f}%) 背离{divergence:.1f}个百分点",
|
||||
"pairs": [sz50, cyb],
|
||||
"direction": direction,
|
||||
})
|
||||
|
||||
# ── 信号3: 恒指 vs 国企指数（国际资本流向）──
|
||||
if hsi and hscei:
|
||||
hsi_chg = hsi["change_pct"]
|
||||
hscei_chg = hscei["change_pct"]
|
||||
if hsi_chg < 0 and hscei_chg < hsi_chg:
|
||||
# 国企跌得比恒指多 → 外资恐慌性卖出H股
|
||||
signals.append({
|
||||
"type": "hk_panic_selling",
|
||||
"level": "high",
|
||||
"desc": f"国企指数({hscei_chg:+.1f}%)跌幅大于恒指({hsi_chg:+.1f}%)→外资恐慌抛售H股",
|
||||
"pairs": [hscei, hsi],
|
||||
"direction": "risk",
|
||||
})
|
||||
|
||||
# ── 信号4: A/H 价格背离（用历史数据检测趋势延续）──
|
||||
if history and len(history) >= 2:
|
||||
latest = history[0]["indices"]
|
||||
prev = history[1]["indices"]
|
||||
|
||||
# 科创50连涨检测
|
||||
if kc:
|
||||
kc_now = kc["change_pct"]
|
||||
kc_prev = prev.get("科创50", {}).get("change_pct", 0) if "科创50" in prev else 0
|
||||
kc_yest = latest.get("科创50", {}).get("change_pct", 0)
|
||||
|
||||
# 检测连涨
|
||||
if isinstance(kc_yest, (int, float)) and isinstance(kc_prev, (int, float)):
|
||||
streak = 0
|
||||
if kc_yest > 0: streak += 1
|
||||
if kc_prev > 0: streak += 1
|
||||
if kc_now > 0: streak += 1
|
||||
if streak >= STREAK_DAYS and kc_now > 0:
|
||||
signals.append({
|
||||
"type": "tech_streak",
|
||||
"level": "medium",
|
||||
"desc": f"科创50连涨{streak}日({kc_prev:+.1f}%→{kc_yest:+.1f}%→{kc_now:+.1f}%)→超买风险",
|
||||
"pairs": [kc],
|
||||
"direction": "risk",
|
||||
})
|
||||
|
||||
# ── 信号5: 大盘宽度 + 季节效应 ──
|
||||
now = datetime.datetime.now()
|
||||
is_month_end = now.day >= 25 # 月末最后一周
|
||||
is_friday = now.weekday() == 4
|
||||
|
||||
# 总体判断
|
||||
risk_count = sum(1 for s in signals if s["direction"] == "risk")
|
||||
opp_count = sum(1 for s in signals if s["direction"] == "opportunity")
|
||||
|
||||
# 月末+周五叠加 → 脆弱性增强
|
||||
if is_month_end and is_friday and risk_count >= 2:
|
||||
signals.append({
|
||||
"type": "time_window_risk",
|
||||
"level": "high",
|
||||
"desc": f"月末({now.day}日)+周五效应+{risk_count}个风险信号叠加→市场脆弱性高",
|
||||
"pairs": [],
|
||||
"direction": "risk",
|
||||
})
|
||||
elif is_month_end and risk_count >= 1:
|
||||
signals.append({
|
||||
"type": "time_window_risk",
|
||||
"level": "medium",
|
||||
"desc": f"月末窗口({now.day}日)+{risk_count}个风险信号→注意控制仓位",
|
||||
"pairs": [],
|
||||
"direction": "risk",
|
||||
})
|
||||
|
||||
return signals
|
||||
|
||||
def write_state(signals, indices):
|
||||
"""写入状态文件，供监控 cron 消费"""
|
||||
levels = [s["level"] for s in signals]
|
||||
highest = "high" if "high" in levels else ("medium" if "medium" in levels else "none")
|
||||
directions = [s["direction"] for s in signals]
|
||||
bias = "risk" if directions.count("risk") > directions.count("opportunity") else "opportunity"
|
||||
|
||||
state = {
|
||||
"level": highest,
|
||||
"bias": bias,
|
||||
"signal_count": len(signals),
|
||||
"signals": signals,
|
||||
"indices": {k: v["change_pct"] for k, v in indices.items()},
|
||||
"created_at": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
|
||||
}
|
||||
STATE_PATH.write_text(json.dumps(state, ensure_ascii=False, indent=2))
|
||||
|
||||
def write_to_signal_news(signals):
|
||||
"""HIGH signal → signal_news"""
|
||||
if not signals:
|
||||
return
|
||||
import sqlite3
|
||||
conn = sqlite3.connect(str(DB_PATH))
|
||||
|
||||
high_signals = [s for s in signals if s["level"] == "high"]
|
||||
if high_signals:
|
||||
for s in high_signals:
|
||||
conn.execute(
|
||||
"INSERT INTO signal_news (signal_id, sector, overall_sentiment, summary, key_articles, searched_stocks, source) VALUES (?, ?, ?, ?, ?, ?, ?)",
|
||||
(0, "跨市场", f"背离-{s['direction'].upper()}", s["desc"], json.dumps(s, ensure_ascii=False), "", "divergence_watch")
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
med_signals = [s for s in signals if s["level"] == "medium"]
|
||||
if med_signals:
|
||||
summary = "\n".join([s["desc"] for s in med_signals])
|
||||
conn.execute(
|
||||
"INSERT INTO signal_news (signal_id, sector, overall_sentiment, summary, key_articles, searched_stocks, source) VALUES (?, ?, ?, ?, ?, ?, ?)",
|
||||
(0, "跨市场", "背离-MEDIUM", summary, json.dumps(med_signals, ensure_ascii=False), "", "divergence_watch")
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
conn.close()
|
||||
|
||||
def print_report(signals, indices):
|
||||
"""no_agent 输出"""
|
||||
if not signals:
|
||||
return # SILENT
|
||||
|
||||
# 有信号就输出
|
||||
high = [s for s in signals if s["level"] == "high"]
|
||||
med = [s for s in signals if s["level"] == "medium"]
|
||||
|
||||
lines = []
|
||||
if high:
|
||||
for s in high:
|
||||
icon = "\u26a0\ufe0f" if s["direction"] == "risk" else "\u2b06\ufe0f"
|
||||
lines.append(f"[DIVERGE] {icon} {s['level'].upper()} {s['type']}: {s['desc']}")
|
||||
if med:
|
||||
for s in med[:3]: # 最多3条
|
||||
icon = "\u26a0\ufe0f" if s["direction"] == "risk" else "\u2b06\ufe0f"
|
||||
lines.append(f"[DIVERGE] {icon} {s['level'].upper()} {s['type']}: {s['desc']}")
|
||||
|
||||
# 输出指数全景
|
||||
idx_line = " | ".join([f"{n}: {indices.get(s, {}).get('change_pct', 0):+.1f}%" for n, s in INDEX_CODES.items() if s in indices])
|
||||
lines.append(f"[DIVERGE] 指数全景: {idx_line}")
|
||||
|
||||
print("\n".join(lines))
|
||||
|
||||
def main():
|
||||
indices = fetch_indices()
|
||||
if not indices:
|
||||
return
|
||||
|
||||
history = load_history()
|
||||
signals = detect_divergences(indices, history)
|
||||
|
||||
# 写入 state + signal_news
|
||||
write_state(signals, indices)
|
||||
write_to_signal_news(signals)
|
||||
|
||||
# no_agent 输出
|
||||
print_report(signals, indices)
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,231 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
macro_context_collector.py — 宏观新闻采集器+实时红绿灯（no_agent）
|
||||
|
||||
采集来源：
|
||||
1. akshare.stock_info_global_em() — 东方财富全球宏观新闻（200条实时）
|
||||
|
||||
核心功能：
|
||||
A. 采集新闻→macro_raw_news（去重入库）
|
||||
B. 实时红绿灯检测——用关键词规则快速识别HIGH/MEDIUM风险
|
||||
- 不等LLM，采集完立刻判断
|
||||
- 检测到风险→写入signal_news+macro_risk_state.json
|
||||
- 盘中的监控cron（每15-25分）读到后立刻调整策略
|
||||
|
||||
红绿灯规则：
|
||||
HIGH（单条就触发）: 全球巨头+核心产业负面/美联储意外/指数暴跌/地缘冲突
|
||||
MEDIUM（累计2条触发）: 常规宏观事件/板块级/资金面
|
||||
"""
|
||||
|
||||
import sys, json, hashlib, os, re
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
DATA_DIR = Path(__file__).parent.parent / "data"
|
||||
DB_PATH = DATA_DIR / "mofin.db"
|
||||
STATE_PATH = DATA_DIR / "macro_risk_state.json"
|
||||
|
||||
# ── 红绿灯 关键词规则 ──
|
||||
# HIGH: 任何一条匹配 → 立即 HIGH 预警
|
||||
HIGH_PATTERNS = [
|
||||
# 全球巨头+核心产业
|
||||
r"苹果.*(?:涨价|降价|推迟|取消|禁|制裁|调查|召回|大跌|暴跌)",
|
||||
r"openai.*(?:推迟|取消|风险|调查|起诉|倒闭|ipo)",
|
||||
r"英伟达|nvidia.*(?:跌|调查|制裁|推迟|禁令)",
|
||||
r"台积电.*(?:跌|推迟|取消|地震|火灾|禁)",
|
||||
r"特斯拉.*(?:暴跌|召回|调查|破产|禁)",
|
||||
# 美联储/央行意外
|
||||
r"美联储.*(?:意外|紧急|缩表|风暴|警告|超预期|加息\s*50|降息\s*50|紧急\s*(?:会议|声明))",
|
||||
r"美联储.*(?:利率|决议).*(?:超预期|意外|紧急)",
|
||||
r"fed.*(?:emergency|unexpected|surprise|hike|cut)",
|
||||
# 指数暴跌
|
||||
r"指数.*(?:跌幅|暴跌|熔断|闪崩|重挫)",
|
||||
r"(?:暴跌|重挫|熔断).*[5-9]%",
|
||||
r"熔断|闪崩",
|
||||
# 地缘+贸易
|
||||
r"关税.*(?:升级|新|报复|制裁)",
|
||||
r"制裁.*(?:新|升级|全面)",
|
||||
r"战争|开战|入侵|核|导弹.*发射",
|
||||
# 系统性能源
|
||||
r"原油.*(?:跌破|暴跌|崩盘|断供)",
|
||||
r"石油.*(?:禁运|制裁|断供)",
|
||||
r"能源危机|粮食危机",
|
||||
# 系统金融
|
||||
r"银行.*(?:倒闭|挤兑|破产|接管|危机)",
|
||||
r"金融危机|债务危机|违约潮|系统性",
|
||||
# AI/科技板块重挫
|
||||
r"半导体.*(?:暴跌|熔断|崩盘|跌幅)",
|
||||
r"科技股.*(?:暴跌|熔断|崩盘|重挫)",
|
||||
r"费城半导体|sox.*(?:跌|崩)",
|
||||
]
|
||||
|
||||
# MEDIUM: 累计匹配2条以上 → MEDIUM 预警
|
||||
MEDIUM_PATTERNS = [
|
||||
r"加息|降息",
|
||||
r"通胀|CPI|PPI",
|
||||
r"汇率.*(?:大幅|波动|贬值|升值)",
|
||||
r"外资.*(?:流出|撤离|减持)",
|
||||
r"北向.*(?:流出|净卖出|大幅)",
|
||||
r"季末|年末|半年末|资金回笼|流动性紧张",
|
||||
r"解禁.*(?:大额|巨量|千亿)",
|
||||
r"大跌|重挫|杀跌|恐慌",
|
||||
r"评级.*(?:下调|负面|降级)",
|
||||
r"预警|风险提示|谨慎",
|
||||
r"期货.*(?:暴跌|跌停|熔断)",
|
||||
r"黑天鹅|灰犀牛",
|
||||
]
|
||||
|
||||
def ensure_tables(conn):
|
||||
conn.execute("""
|
||||
CREATE TABLE IF NOT EXISTS macro_raw_news (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
title TEXT NOT NULL,
|
||||
summary TEXT DEFAULT '',
|
||||
url TEXT DEFAULT '',
|
||||
source_ts TEXT DEFAULT '',
|
||||
fetched_at TEXT DEFAULT (datetime('now','localtime')),
|
||||
risk_level TEXT DEFAULT 'unassessed',
|
||||
risk_reason TEXT DEFAULT ''
|
||||
)
|
||||
""")
|
||||
conn.commit()
|
||||
|
||||
def fetch_news():
|
||||
try:
|
||||
import akshare as ak
|
||||
df = ak.stock_info_global_em()
|
||||
items = []
|
||||
for _, row in df.iterrows():
|
||||
items.append({
|
||||
"title": str(row.get("标题", "")),
|
||||
"summary": str(row.get("摘要", "")),
|
||||
"url": str(row.get("链接", "")),
|
||||
"source_ts": str(row.get("发布时间", "")),
|
||||
})
|
||||
return items
|
||||
except ImportError:
|
||||
print("[MACRO] akshare 未安装", file=sys.stderr)
|
||||
return []
|
||||
except Exception as e:
|
||||
print(f"[MACRO] 采集失败: {e}", file=sys.stderr)
|
||||
return []
|
||||
|
||||
def title_hash(title):
|
||||
return hashlib.md5(title.encode()).hexdigest()[:16]
|
||||
|
||||
def quick_risk_check(items):
|
||||
"""红绿灯：快速关键词检测，返回 (level, matched_articles, summary)"""
|
||||
hits_high = []
|
||||
hits_medium = []
|
||||
|
||||
for item in items:
|
||||
text = (item["title"] + " " + item["summary"]).lower()
|
||||
for pattern in HIGH_PATTERNS:
|
||||
if re.search(pattern, text):
|
||||
hits_high.append(item)
|
||||
break
|
||||
else:
|
||||
# 没进 HIGH 才检查 MEDIUM
|
||||
for pattern in MEDIUM_PATTERNS:
|
||||
if re.search(pattern, text):
|
||||
hits_medium.append(item)
|
||||
break
|
||||
|
||||
level = "none"
|
||||
summary = ""
|
||||
matched = []
|
||||
|
||||
if hits_high:
|
||||
level = "high"
|
||||
matched = hits_high[:5]
|
||||
titles = [f"· {h['title'][:50]}" for h in hits_high[:5]]
|
||||
summary = f"【高风险】{len(hits_high)}条紧急信号:\n" + "\n".join(titles)
|
||||
elif len(hits_medium) >= 2:
|
||||
level = "medium"
|
||||
matched = hits_medium[:5]
|
||||
titles = [f"· {h['title'][:50]}" for h in hits_medium[:5]]
|
||||
summary = f"【中风险】{len(hits_medium)}条预警信号:\n" + "\n".join(titles)
|
||||
|
||||
return level, matched, summary
|
||||
|
||||
def write_risk_signal(conn, level, matched, summary):
|
||||
"""写入 signal_news + macro_risk_state.json"""
|
||||
now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
sentiment_map = {"high": "宏观-WATCH_HIGH", "medium": "宏观-WATCH_MEDIUM"}
|
||||
sentiment = sentiment_map.get(level, "")
|
||||
|
||||
# 写入 signal_news
|
||||
articles_json = json.dumps([{"title": a["title"][:80], "summary": a["summary"][:120]} for a in matched], ensure_ascii=False)
|
||||
conn.execute(
|
||||
"INSERT INTO signal_news (signal_id, sector, overall_sentiment, summary, key_articles, searched_stocks, source) VALUES (0, ?, ?, ?, ?, '', ?)",
|
||||
("宏观", sentiment, summary[:500], articles_json, "macro_watch")
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
# 写入状态文件（供监控cron实时读取）
|
||||
state = {
|
||||
"level": level,
|
||||
"signals": [{"sentiment": sentiment, "summary": summary[:300], "key_articles": articles_json, "created_at": now}],
|
||||
"signal_count": len(matched),
|
||||
"created_at": now,
|
||||
"expired": False,
|
||||
"source": "collector_realtime",
|
||||
}
|
||||
STATE_PATH.write_text(json.dumps(state, ensure_ascii=False, indent=2))
|
||||
|
||||
def main():
|
||||
conn = sqlite3.connect(str(DB_PATH))
|
||||
ensure_tables(conn)
|
||||
|
||||
# 去重基础
|
||||
existing = set()
|
||||
for row in conn.execute("SELECT title FROM macro_raw_news ORDER BY id DESC LIMIT 200"):
|
||||
existing.add(title_hash(row[0]))
|
||||
|
||||
items = fetch_news()
|
||||
if not items:
|
||||
conn.close()
|
||||
return
|
||||
|
||||
# 去重写入
|
||||
new_items = []
|
||||
now_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
|
||||
for item in items:
|
||||
if not item["title"].strip():
|
||||
continue
|
||||
h = title_hash(item["title"])
|
||||
if h in existing:
|
||||
continue
|
||||
existing.add(h)
|
||||
try:
|
||||
conn.execute(
|
||||
"INSERT INTO macro_raw_news (title, summary, url, source_ts, fetched_at) VALUES (?, ?, ?, ?, ?)",
|
||||
(item["title"][:300], item["summary"][:500], item["url"][:500], item["source_ts"][:20], now_str)
|
||||
)
|
||||
new_items.append(item)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
conn.commit()
|
||||
|
||||
# 红绿灯检测（只针对新采集的）
|
||||
level, matched, summary = "none", [], ""
|
||||
if new_items:
|
||||
level, matched, summary = quick_risk_check(new_items)
|
||||
if level in ("high", "medium"):
|
||||
write_risk_signal(conn, level, matched, summary)
|
||||
|
||||
conn.close()
|
||||
|
||||
# no_agent 输出
|
||||
if new_items:
|
||||
print(f"[MACRO] {len(new_items)}条新宏观新闻")
|
||||
# HIGH风险：输出预警（会推送到XMPP）
|
||||
if level == "high":
|
||||
print(f"⚠️ HIGH风险预警 ({len(matched)}条): {summary[:200]}")
|
||||
elif level == "medium":
|
||||
print(f" MEDIUM风险: {len(matched)}条匹配")
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sqlite3
|
||||
main()
|
||||
@@ -0,0 +1,148 @@
|
||||
#!/usr/bin/env python3
|
||||
"""macro_index_collector.py — 指数宏观数据采集 (no_agent)
|
||||
|
||||
采集指数行情，写入 macro_context_log 表（积累每日快照）。
|
||||
与莫荷的 macro_context_collector.py（宏观新闻采集）分开，互不冲突。
|
||||
|
||||
在 9:35 和 12:00 由 cron 触发。
|
||||
"""
|
||||
|
||||
import json, sqlite3, subprocess
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
DATA_DIR = Path("/home/hmo/web-dashboard/data")
|
||||
DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
|
||||
|
||||
INDICES = [
|
||||
("sh000001", "上证指数"), ("sz399001", "深证成指"),
|
||||
("sz399006", "创业板指"), ("sh000688", "科创50"),
|
||||
("hkHSI", "恒生指数"), ("hkHSCEI", "国企指数"),
|
||||
]
|
||||
|
||||
SECTOR_INDICES = [
|
||||
("sz980017", "国证芯片"), ("sh000039", "上证信息"),
|
||||
("sz980022", "机器人产业"), ("sz980032", "新能电池"),
|
||||
("sz980076", "通用航空"), ("sh000063", "上证周期"),
|
||||
("sh000068", "上证资源"), ("sh000019", "治理指数"),
|
||||
]
|
||||
|
||||
|
||||
def fetch(symbol):
|
||||
try:
|
||||
r = subprocess.run(["curl", "-s", f"https://qt.gtimg.cn/q={symbol}"],
|
||||
capture_output=True, timeout=8)
|
||||
return r.stdout.decode("gbk", errors="replace")
|
||||
except:
|
||||
return None
|
||||
|
||||
|
||||
def parse(text, name):
|
||||
if not text or "pv_none_match" in text:
|
||||
return None
|
||||
try:
|
||||
f = text.split("~")
|
||||
if len(f) < 35:
|
||||
return None
|
||||
price = float(f[3]) if f[3] else 0
|
||||
prev = float(f[4]) if f[4] else 0
|
||||
high = float(f[33]) if len(f) > 33 and f[33] else 0
|
||||
low = float(f[34]) if len(f) > 34 and f[34] else 0
|
||||
chg = round((price - prev) / prev * 100, 2) if prev else 0
|
||||
return {"name": name, "price": price, "change_pct": chg,
|
||||
"high": high, "low": low}
|
||||
except:
|
||||
return None
|
||||
|
||||
|
||||
def assess(indices_data):
|
||||
if not indices_data:
|
||||
return "unknown", "unknown"
|
||||
sh = next((i for i in indices_data if i and i["name"] == "上证指数"), None)
|
||||
sz = next((i for i in indices_data if i and i["name"] == "深证成指"), None)
|
||||
cyb = next((i for i in indices_data if i and i["name"] == "创业板指"), None)
|
||||
avg = ((sh or {}).get("change_pct", 0) + (sz or {}).get("change_pct", 0) +
|
||||
(cyb or {}).get("change_pct", 0)) / 3
|
||||
if avg > 1.5:
|
||||
return "strong_bullish", "整体强势"
|
||||
elif avg > 0.5:
|
||||
return "bullish", "偏强"
|
||||
elif avg > -0.5:
|
||||
return "neutral", "震荡"
|
||||
elif avg > -1.5:
|
||||
return "bearish", "偏弱"
|
||||
return "strong_bearish", "整体弱势"
|
||||
|
||||
|
||||
def main():
|
||||
now = datetime.now()
|
||||
indices_data = []
|
||||
for sym, name in INDICES:
|
||||
raw = fetch(sym)
|
||||
p = parse(raw, name)
|
||||
if p:
|
||||
indices_data.append(p)
|
||||
|
||||
has_data = any(i for i in indices_data if i and i.get("price", 0) > 0)
|
||||
overall, desc = assess(indices_data)
|
||||
|
||||
# 读莫荷的 macro_risk_state.json 补充风险状态
|
||||
risk_state = {}
|
||||
try:
|
||||
risk_path = DATA_DIR / "macro_risk_state.json"
|
||||
if risk_path.exists():
|
||||
risk_state = json.loads(risk_path.read_text())
|
||||
except:
|
||||
pass
|
||||
|
||||
context = {
|
||||
"updated_at": now.strftime("%Y-%m-%d %H:%M:%S"),
|
||||
"session": "morning" if now.hour < 12 else "midday",
|
||||
"has_valid_data": has_data,
|
||||
"indices": {i["name"]: {"price": i["price"], "change_pct": i["change_pct"],
|
||||
"high": i.get("high", 0), "low": i.get("low", 0)}
|
||||
for i in indices_data if i},
|
||||
"structure": {"overall": overall, "description": desc},
|
||||
"risk_level": risk_state.get("level", "none"),
|
||||
"risk_reason": risk_state.get("reason", ""),
|
||||
}
|
||||
|
||||
# 写入DB
|
||||
try:
|
||||
conn = sqlite3.connect(str(DB_PATH))
|
||||
conn.execute('''INSERT INTO macro_context_log
|
||||
(data_timestamp, session, has_valid_data, indices, structure,
|
||||
key_sectors, top_gainers, top_losers, sector_up_ratio, sector_mood)
|
||||
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
|
||||
(context["updated_at"], context["session"],
|
||||
1 if has_data else 0,
|
||||
json.dumps(context["indices"], ensure_ascii=False),
|
||||
json.dumps(context["structure"], ensure_ascii=False),
|
||||
"[]", "[]", "[]", 0, overall))
|
||||
conn.commit()
|
||||
conn.close()
|
||||
except:
|
||||
pass
|
||||
|
||||
# 写入 macro_context.json（兼容旧读取方）
|
||||
try:
|
||||
DATA_DIR.mkdir(parents=True, exist_ok=True)
|
||||
(DATA_DIR / "macro_context.json").write_text(
|
||||
json.dumps(context, ensure_ascii=False, indent=2))
|
||||
except:
|
||||
pass
|
||||
|
||||
if has_data:
|
||||
idx_parts = [f"{i['name']}{'▲' if i['change_pct']>0 else '▼'}{i['change_pct']:+.2f}%"
|
||||
for i in indices_data[:4] if i]
|
||||
print(f"【宏观指数】{now.strftime('%H:%M')} | {desc}")
|
||||
print(" | ".join(idx_parts))
|
||||
print(f"评估: {'整体强势' if overall=='strong_bullish' else '偏强' if overall=='bullish' else '震荡' if overall=='neutral' else '偏弱' if overall=='bearish' else '整体弱势'}")
|
||||
if risk_state.get("level") == "high":
|
||||
print(f"🔴 宏观风险: {risk_state.get('reason','')}")
|
||||
else:
|
||||
print("【宏观指数】数据不可用（非交易时段或行情未更新）")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,92 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
macro_signal_consumer.py — 消费宏观风险信号，写入风险状态
|
||||
|
||||
no_agent 模式：有HIGH风险→输出风险摘要 | 无→静默
|
||||
|
||||
管道位置：
|
||||
macro_risk_scanner (8:30/11:30) → signal_news(source=macro_watch) → 本脚本
|
||||
↓
|
||||
macro_risk_state.json — 供所有监控 cron 读取
|
||||
↓
|
||||
如果 HIGH → 推送到 Dad
|
||||
"""
|
||||
import sqlite3, json, os
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
|
||||
BASE = Path("/home/hmo/MoFin")
|
||||
DATA = BASE / "data"
|
||||
DB_PATH = DATA / "mofin.db"
|
||||
STATE_PATH = DATA / "macro_risk_state.json"
|
||||
|
||||
def main():
|
||||
conn = sqlite3.connect(str(DB_PATH))
|
||||
conn.row_factory = sqlite3.Row
|
||||
|
||||
# 读取未处理的 macro_watch 信号
|
||||
rows = conn.execute(
|
||||
"SELECT * FROM signal_news WHERE source='macro_watch' AND (processed=0 OR processed IS NULL)"
|
||||
).fetchall()
|
||||
|
||||
if not rows:
|
||||
# 无新信号时状态文件维持 15 分钟过期
|
||||
try:
|
||||
state = json.loads(STATE_PATH.read_text())
|
||||
created = datetime.strptime(state.get("created_at", "2000-01-01"), "%Y-%m-%d %H:%M:%S")
|
||||
if (datetime.now() - created).total_seconds() > 900: # 15 min
|
||||
state["level"] = "none"
|
||||
state["expired"] = True
|
||||
STATE_PATH.write_text(json.dumps(state, ensure_ascii=False, indent=2))
|
||||
except:
|
||||
pass
|
||||
conn.close()
|
||||
return # SILENT
|
||||
|
||||
# 聚合风险等级
|
||||
levels = {"宏观-WATCH_HIGH": "high", "宏观-WATCH_MEDIUM": "medium", "宏观-WATCH_INFO": "info"}
|
||||
highest = "info"
|
||||
all_summaries = []
|
||||
|
||||
for r in rows:
|
||||
sentiment = r["overall_sentiment"]
|
||||
lv = levels.get(sentiment, "info")
|
||||
if lv == "high":
|
||||
highest = "high"
|
||||
elif lv == "medium" and highest != "high":
|
||||
highest = "medium"
|
||||
all_summaries.append({
|
||||
"sentiment": sentiment,
|
||||
"summary": r["summary"][:300],
|
||||
"key_articles": r["key_articles"],
|
||||
"created_at": r["created_at"],
|
||||
})
|
||||
|
||||
# 写入风险状态文件
|
||||
state = {
|
||||
"level": highest,
|
||||
"signals": all_summaries,
|
||||
"signal_count": len(rows),
|
||||
"created_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
|
||||
"expired": False,
|
||||
}
|
||||
STATE_PATH.write_text(json.dumps(state, ensure_ascii=False, indent=2))
|
||||
|
||||
# 标记为已处理
|
||||
for r in rows:
|
||||
conn.execute("UPDATE signal_news SET processed=1 WHERE id=?", (r["id"],))
|
||||
conn.commit()
|
||||
conn.close()
|
||||
|
||||
# no_agent 输出（有 HIGH 才主动出声）
|
||||
if highest == "high":
|
||||
print(f"[MACRO-RISK] ⚠️ HIGH: {len(rows)}条高风险信号")
|
||||
for s in all_summaries:
|
||||
print(f" {s['summary'][:100]}")
|
||||
elif highest == "medium":
|
||||
if len(os.environ.get("MACRO_VERBOSE", "")) > 0:
|
||||
print(f"[MACRO-RISK] MEDIUM: {len(rows)}条中风险信号")
|
||||
# HIGH 信号会通过 no_agent 推送到 XMPP
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user