#!/usr/bin/env python3
"""
mo_alphasift_bridge.py — AlphaSift 选股 → MoFin 自选池自动对接

流程：
1. 调用 DSA AlphaSift API → 获取候选股列表
2. 过滤（评分阈值 + 去重自选池/持仓）
3. 写入 MoFin watchlist.json
4. 调用 regenerate_all() 生成策略 → decisions.json
5. price_monitor 自动接管监控

用法：
  python3 mo_alphasift_bridge.py                    # 默认策略 balanced_alpha
  python3 mo_alphasift_bridge.py --strategy dual_low  # 指定策略
  python3 mo_alphasift_bridge.py --dry-run           # 只看不写
  python3 mo_alphasift_bridge.py --min-score 6       # 最低评分阈值

集成到 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       # 最低评分
MAX_ADD = 5         # 每次最多加几只


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 call_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=120) as r:
            return json.loads(r.read())
    except Exception as e:
        print(f"API 错误: {e}")
        return None


# ── 核心逻辑 ─────────────────────────────────────────────────────────

def run_screen(strategy, market, max_results, dry_run=False):
    """运行 AlphaSift 选股并写入 MoFin 自选池"""
    
    # 1. AlphaSift 选股
    print(f"🔍 AlphaSift 选股: 策略={strategy} 市场={market}", flush=True)
    result = call_api("/api/v1/alphasift/screen", "POST", {
        "strategy": strategy, "market": market, "max_results": max_results
    })
    
    if not result or not result.get("candidates"):
        print("  ❌ 无候选股或 AlphaSift 返回空")
        return
    
    candidates = result["candidates"]
    print(f"  AlphaSift 返回 {len(candidates)} 只候选股")
    if result.get("llm_market_view"):
        print(f"  市场观点: {result['llm_market_view'][:80]}...")
    
    # 2. 加载现有自选池和持仓，去重
    wl = load_json(WATCHLIST_PATH) or {"stocks": []}
    pf = load_json(PORTFOLIO_PATH) or {"holdings": []}
    
    existing_codes = set()
    for s in wl.get("stocks", []):
        existing_codes.add(str(s.get("code", "")).strip())
    for h in pf.get("holdings", []):
        existing_codes.add(str(h.get("code", "")).strip())
    
    # 3. 过滤：评分达标 + 不在现有自选/持仓中
    new_stocks = []
    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("llm_thesis", "")[:20] or code
        
        if score < MIN_SCORE:
            continue
        if code in existing_codes:
            print(f"  ⏭  {code} {name} (已在自选/持仓中)")
            continue
        
        entry = {
            "code": code,
            "name": name,
            "price": c.get("price", 0),
            "tag": f"alpha_sift_{strategy}",
            "source": "alpha_sift",
            "added_at": datetime.now().strftime("%Y-%m-%d %H:%M"),
            "alpha_score": score,
            "alpha_reason": (c.get("reason", "") or c.get("llm_thesis", ""))[:200],
            "analysis": {},
        }
        new_stocks.append(entry)
        existing_codes.add(code)
    
    if not new_stocks:
        print("  ℹ️  没有符合条件的新标的")
        return
    
    # 限制数量
    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['alpha_score']})")
    
    if dry_run:
        print("\n  [DRY RUN] 未实际写入")
        return
    
    # 4. 写入 watchlist.json
    wl["stocks"].extend(new_stocks)
    wl["updated_at"] = datetime.now().strftime("%Y-%m-%d %H:%M")
    save_json(WATCHLIST_PATH, wl)
    print(f"  已写入 {WATCHLIST_PATH}")
    
    # 5. 触发策略生成
    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
        result = regenerate_all(stdout=True)
        if result:
            print(f"  策略生成完成: total={result.get('total',0)} ok={result.get('ok',0)}")
    except Exception as e:
        print(f"  ⚠️ regenerate_all() 失败: {e}")
        print("  新股票已加入自选池，下次 cron 会自动生成策略")


# ── CLI ──────────────────────────────────────────────────────────────

def main():
    parser = argparse.ArgumentParser(description="AlphaSift → MoFin 自动对接")
    parser.add_argument("--strategy", default=DEFAULT_STRATEGY,
                        help=f"选股策略 (默认: {DEFAULT_STRATEGY})")
    parser.add_argument("--market", default=DEFAULT_MARKET,
                        help=f"市场 (默认: {DEFAULT_MARKET})")
    parser.add_argument("--max", type=int, default=DEFAULT_MAX,
                        help=f"AlphaSift 最多返回 (默认: {DEFAULT_MAX})")
    parser.add_argument("--min-score", type=int, default=MIN_SCORE,
                        help=f"最低评分 (默认: {MIN_SCORE})")
    parser.add_argument("--dry-run", action="store_true",
                        help="只看不写")
    
    args = parser.parse_args()
    
    # 列出可用策略
    if args.strategy == "list":
        r = call_api("/api/v1/alphasift/strategies")
        if r and r.get("strategies"):
            print("可用策略:")
            for s in r["strategies"]:
                print(f"  {s['id']}: {s.get('name','?')} - {s.get('description','')[:60]}")
        return
    
    run_screen(args.strategy, args.market, args.max, args.dry_run)


if __name__ == "__main__":
    main()