243 lines
7.8 KiB
Python
243 lines
7.8 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
mo_alphasift_bridge.py — AlphaSift 选股 → MoFin 自选池自动对接
|
|
|
|
流程:
|
|
1. 提交 AlphaSift 异步选股任务 → 轮询结果
|
|
2. 过滤(评分阈值 + 去重)
|
|
3. 写入 MoFin watchlist.json(含来源/日期/策略备注)
|
|
4. 调用 regenerate_all() 生成策略
|
|
5. price_monitor 自动接管
|
|
|
|
用法:
|
|
python3 mo_alphasift_bridge.py # 默认策略
|
|
python3 mo_alphasift_bridge.py --dry-run # 只看不写
|
|
python3 mo_alphasift_bridge.py --min-score 6 # 最低评分
|
|
python3 mo_alphasift_bridge.py --strategy list # 列出所有策略
|
|
|
|
cron: 0 10 * * 1-5 cd /home/hmo/MoFin && python3 mo_alphasift_bridge.py
|
|
"""
|
|
|
|
import sys, os, json, argparse, urllib.request, time
|
|
from datetime import datetime
|
|
from pathlib import Path
|
|
|
|
# ── 配置 ─────────────────────────────────────────────────────────────
|
|
|
|
DSA_API = "http://127.0.0.1:8001"
|
|
MOFIN_DATA = Path("/home/hmo/web-dashboard/data")
|
|
WATCHLIST_PATH = MOFIN_DATA / "watchlist.json"
|
|
PORTFOLIO_PATH = MOFIN_DATA / "portfolio.json"
|
|
|
|
DEFAULT_STRATEGY = "balanced_alpha"
|
|
DEFAULT_MARKET = "cn"
|
|
DEFAULT_MAX = 15
|
|
MIN_SCORE = 5
|
|
MAX_ADD = 5
|
|
POLL_INTERVAL = 5
|
|
POLL_TIMEOUT = 300
|
|
|
|
|
|
def load_json(path):
|
|
try:
|
|
return json.loads(path.read_text(encoding="utf-8"))
|
|
except:
|
|
return None
|
|
|
|
|
|
def save_json(path, data):
|
|
path.parent.mkdir(parents=True, exist_ok=True)
|
|
path.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
|
|
|
|
|
|
def api(endpoint, method="GET", body=None):
|
|
url = f"{DSA_API}{endpoint}"
|
|
data = json.dumps(body).encode() if body else None
|
|
req = urllib.request.Request(url, data=data, method=method,
|
|
headers={"Content-Type": "application/json"})
|
|
try:
|
|
with urllib.request.urlopen(req, timeout=30) as r:
|
|
return json.loads(r.read())
|
|
except Exception as e:
|
|
print(f" API 错误: {e}")
|
|
return None
|
|
|
|
|
|
def get_existing_codes():
|
|
codes = set()
|
|
for path in [WATCHLIST_PATH, PORTFOLIO_PATH]:
|
|
data = load_json(path)
|
|
if not data:
|
|
continue
|
|
key = "stocks" if "watchlist" in str(path) else "holdings"
|
|
for item in data.get(key, []):
|
|
c = str(item.get("code", "")).strip()
|
|
if c:
|
|
codes.add(c)
|
|
return codes
|
|
|
|
|
|
def run_screen(strategy, market, max_results, dry_run=False):
|
|
now = datetime.now()
|
|
date_str = now.strftime("%Y-%m-%d")
|
|
time_str = now.strftime("%Y-%m-%d %H:%M")
|
|
|
|
# 1. 提交异步任务
|
|
print(f"AlphaSift 选股: {strategy} (异步)", flush=True)
|
|
task = api("/api/v1/alphasift/screen/tasks", "POST", {
|
|
"strategy": strategy, "market": market, "max_results": max_results
|
|
})
|
|
if not task or not task.get("task_id"):
|
|
print(" FAIL: 提交任务失败")
|
|
return
|
|
|
|
task_id = task["task_id"]
|
|
print(f" 任务ID: {task_id[:12]}...", flush=True)
|
|
|
|
# 2. 轮询
|
|
waited = 0
|
|
result = None
|
|
while waited < POLL_TIMEOUT:
|
|
time.sleep(POLL_INTERVAL)
|
|
waited += POLL_INTERVAL
|
|
status = api(f"/api/v1/alphasift/screen/tasks/{task_id}")
|
|
if not status:
|
|
continue
|
|
s = status.get("status", "")
|
|
if s == "completed":
|
|
print(f" 完成 ({waited}s)")
|
|
result = status.get("result", {})
|
|
break
|
|
elif s == "failed":
|
|
print(f" FAIL: {status.get('error', '')}")
|
|
return
|
|
else:
|
|
pct = status.get("progress", 0)
|
|
print(f" ...{s} ({pct}%)", flush=True)
|
|
else:
|
|
print(f" FAIL: 超时 ({POLL_TIMEOUT}s)")
|
|
return
|
|
|
|
candidates = result.get("candidates", [])
|
|
if not candidates:
|
|
print(" 无候选股")
|
|
return
|
|
|
|
market_view = result.get("llm_market_view", "")
|
|
print(f" 返回 {len(candidates)} 只候选股")
|
|
if market_view:
|
|
print(f" 市场观点: {market_view[:100]}...")
|
|
|
|
# 3. 过滤 + 去重
|
|
existing = get_existing_codes()
|
|
new_stocks = []
|
|
skipped = 0
|
|
|
|
for c in candidates:
|
|
code = str(c.get("code", "")).strip()
|
|
score = c.get("score", 0) or c.get("llm_score", 0) or 0
|
|
name = c.get("name", "") or c.get("title", "") or code
|
|
reason = c.get("reason", "") or c.get("llm_thesis", "")
|
|
catalysts = c.get("llm_catalysts", "")
|
|
risks = c.get("llm_risks", "")
|
|
|
|
if score < MIN_SCORE:
|
|
skipped += 1
|
|
continue
|
|
if code in existing:
|
|
continue
|
|
|
|
notes_parts = [f"AlphaSift/{strategy} 评分{score}"]
|
|
if reason:
|
|
notes_parts.append(reason[:150])
|
|
if catalysts:
|
|
notes_parts.append(f"催化剂:{catalysts[:100]}")
|
|
|
|
new_stocks.append({
|
|
"code": code,
|
|
"name": name,
|
|
"price": c.get("price", 0),
|
|
"source": "alpha_sift",
|
|
"source_detail": {
|
|
"strategy": strategy,
|
|
"score": score,
|
|
"date": date_str,
|
|
"reason": reason[:300],
|
|
"catalysts": catalysts[:200] if catalysts else "",
|
|
"risks": risks[:200] if risks else "",
|
|
"market_view": market_view[:300] if market_view else "",
|
|
},
|
|
"notes": " | ".join(notes_parts),
|
|
"added_at": time_str,
|
|
"added_by": "AlphaSift",
|
|
"analysis": {},
|
|
})
|
|
existing.add(code)
|
|
|
|
print(f" 过滤: {len(new_stocks)} 新标的 (跳过{skipped}只评分不足)")
|
|
|
|
if not new_stocks:
|
|
print(" 无符合条件的新标的")
|
|
return
|
|
|
|
new_stocks = new_stocks[:MAX_ADD]
|
|
|
|
print(f"\n 新增 {len(new_stocks)} 只到自选池:")
|
|
for s in new_stocks:
|
|
print(f" {s['code']} {s['name']} (评分{s['source_detail']['score']})")
|
|
if s['source_detail'].get('reason'):
|
|
print(f" {s['source_detail']['reason'][:120]}")
|
|
|
|
if dry_run:
|
|
print("\n [DRY RUN] 未写入")
|
|
return
|
|
|
|
# 4. 写入
|
|
wl = load_json(WATCHLIST_PATH) or {"stocks": []}
|
|
wl["stocks"].extend(new_stocks)
|
|
wl["updated_at"] = time_str
|
|
save_json(WATCHLIST_PATH, wl)
|
|
print(f"\n 已写入 {WATCHLIST_PATH}")
|
|
|
|
# 5. 策略生成
|
|
print("\n 调用 regenerate_all() 生成策略...")
|
|
try:
|
|
sys.path.insert(0, str(MOFIN_DATA.parent))
|
|
from strategy_lifecycle import regenerate_all
|
|
r = regenerate_all(stdout=True)
|
|
if r:
|
|
print(f" 完成: {r.get('ok',0)}/{r.get('total',0)} 只策略已生成")
|
|
print(f" price_monitor 将在 2 分钟内自动开始监控")
|
|
except Exception as e:
|
|
print(f" WARN: regenerate_all 失败: {e}")
|
|
print(f" 股票已加入自选池,下次 cron 会自动处理")
|
|
|
|
|
|
def list_strategies():
|
|
r = api("/api/v1/alphasift/strategies")
|
|
if r and r.get("strategies"):
|
|
print("AlphaSift 策略:")
|
|
for s in r["strategies"]:
|
|
print(f" {s['id']:20s} {s.get('name','?'):15s} {s.get('description','')[:60]}")
|
|
|
|
|
|
def main():
|
|
global MIN_SCORE
|
|
parser = argparse.ArgumentParser(description="AlphaSift → MoFin")
|
|
parser.add_argument("--strategy", default=DEFAULT_STRATEGY)
|
|
parser.add_argument("--market", default=DEFAULT_MARKET)
|
|
parser.add_argument("--max", type=int, default=DEFAULT_MAX)
|
|
parser.add_argument("--min-score", type=int, default=MIN_SCORE)
|
|
parser.add_argument("--dry-run", action="store_true")
|
|
args = parser.parse_args()
|
|
MIN_SCORE = args.min_score
|
|
|
|
if args.strategy == "list":
|
|
list_strategies()
|
|
return
|
|
run_screen(args.strategy, args.market, args.max, args.dry_run)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|