feat: mo_alphasift_bridge v2 — async mode + source tracking (date/strategy/notes)
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+138
-81
@@ -3,20 +3,19 @@
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mo_alphasift_bridge.py — AlphaSift 选股 → MoFin 自选池自动对接
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流程：
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1. 调用 DSA AlphaSift API → 获取候选股列表
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2. 过滤（评分阈值 + 去重自选池/持仓）
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3. 写入 MoFin watchlist.json
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4. 调用 regenerate_all() 生成策略 → decisions.json
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5. price_monitor 自动接管监控
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1. 提交 AlphaSift 异步选股任务 → 轮询结果
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2. 过滤（评分阈值 + 去重）
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3. 写入 MoFin watchlist.json（含来源/日期/策略备注）
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4. 调用 regenerate_all() 生成策略
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5. price_monitor 自动接管
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用法：
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python3 mo_alphasift_bridge.py # 默认策略 balanced_alpha
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python3 mo_alphasift_bridge.py --strategy dual_low # 指定策略
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python3 mo_alphasift_bridge.py # 默认策略
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python3 mo_alphasift_bridge.py --dry-run # 只看不写
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python3 mo_alphasift_bridge.py --min-score 6 # 最低评分阈值
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python3 mo_alphasift_bridge.py --min-score 6 # 最低评分
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python3 mo_alphasift_bridge.py --strategy list # 列出所有策略
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集成到 cron:
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0 10 * * 1-5 cd /home/hmo/MoFin && python3 mo_alphasift_bridge.py
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cron: 0 10 * * 1-5 cd /home/hmo/MoFin && python3 mo_alphasift_bridge.py
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"""
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import sys, os, json, argparse, urllib.request, time
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@@ -33,8 +32,10 @@ PORTFOLIO_PATH = MOFIN_DATA / "portfolio.json"
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DEFAULT_STRATEGY = "balanced_alpha"
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DEFAULT_MARKET = "cn"
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DEFAULT_MAX = 15
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MIN_SCORE = 5 # 最低评分
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MAX_ADD = 5 # 每次最多加几只
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MIN_SCORE = 5
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MAX_ADD = 5
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POLL_INTERVAL = 5
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POLL_TIMEOUT = 300
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def load_json(path):
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@@ -49,135 +50,191 @@ def save_json(path, data):
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path.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
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def call_api(endpoint, method="GET", body=None):
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def api(endpoint, method="GET", body=None):
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url = f"{DSA_API}{endpoint}"
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data = json.dumps(body).encode() if body else None
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req = urllib.request.Request(url, data=data, method=method,
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headers={"Content-Type": "application/json"})
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try:
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with urllib.request.urlopen(req, timeout=120) as r:
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with urllib.request.urlopen(req, timeout=30) as r:
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return json.loads(r.read())
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except Exception as e:
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print(f" API 错误: {e}")
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return None
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# ── 核心逻辑 ─────────────────────────────────────────────────────────
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def get_existing_codes():
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codes = set()
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for path in [WATCHLIST_PATH, PORTFOLIO_PATH]:
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data = load_json(path)
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if not data:
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continue
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key = "stocks" if "watchlist" in str(path) else "holdings"
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for item in data.get(key, []):
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c = str(item.get("code", "")).strip()
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if c:
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codes.add(c)
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return codes
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def run_screen(strategy, market, max_results, dry_run=False):
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"""运行 AlphaSift 选股并写入 MoFin 自选池"""
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now = datetime.now()
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date_str = now.strftime("%Y-%m-%d")
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time_str = now.strftime("%Y-%m-%d %H:%M")
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# 1. AlphaSift 选股
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print(f"🔍 AlphaSift 选股: 策略={strategy} 市场={market}", flush=True)
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result = call_api("/api/v1/alphasift/screen", "POST", {
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# 1. 提交异步任务
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print(f"AlphaSift 选股: {strategy} (异步)", flush=True)
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task = api("/api/v1/alphasift/screen/tasks", "POST", {
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"strategy": strategy, "market": market, "max_results": max_results
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})
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if not result or not result.get("candidates"):
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print(" ❌ 无候选股或 AlphaSift 返回空")
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if not task or not task.get("task_id"):
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print(" FAIL: 提交任务失败")
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return
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candidates = result["candidates"]
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print(f" AlphaSift 返回 {len(candidates)} 只候选股")
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if result.get("llm_market_view"):
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print(f" 市场观点: {result['llm_market_view'][:80]}...")
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task_id = task["task_id"]
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print(f" 任务ID: {task_id[:12]}...", flush=True)
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# 2. 加载现有自选池和持仓，去重
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wl = load_json(WATCHLIST_PATH) or {"stocks": []}
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pf = load_json(PORTFOLIO_PATH) or {"holdings": []}
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# 2. 轮询
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waited = 0
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result = None
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while waited < POLL_TIMEOUT:
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time.sleep(POLL_INTERVAL)
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waited += POLL_INTERVAL
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status = api(f"/api/v1/alphasift/screen/tasks/{task_id}")
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if not status:
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continue
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s = status.get("status", "")
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if s == "completed":
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print(f" 完成 ({waited}s)")
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result = status.get("result", {})
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break
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elif s == "failed":
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print(f" FAIL: {status.get('error', '')}")
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return
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else:
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pct = status.get("progress", 0)
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print(f" ...{s} ({pct}%)", flush=True)
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else:
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print(f" FAIL: 超时 ({POLL_TIMEOUT}s)")
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return
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existing_codes = set()
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for s in wl.get("stocks", []):
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existing_codes.add(str(s.get("code", "")).strip())
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for h in pf.get("holdings", []):
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existing_codes.add(str(h.get("code", "")).strip())
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candidates = result.get("candidates", [])
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if not candidates:
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print(" 无候选股")
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return
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# 3. 过滤：评分达标 + 不在现有自选/持仓中
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market_view = result.get("llm_market_view", "")
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print(f" 返回 {len(candidates)} 只候选股")
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if market_view:
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print(f" 市场观点: {market_view[:100]}...")
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# 3. 过滤 + 去重
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existing = get_existing_codes()
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new_stocks = []
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skipped = 0
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for c in candidates:
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code = str(c.get("code", "")).strip()
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score = c.get("score", 0) or c.get("llm_score", 0) or 0
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name = c.get("name", "") or c.get("llm_thesis", "")[:20] or code
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name = c.get("name", "") or c.get("title", "") or code
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reason = c.get("reason", "") or c.get("llm_thesis", "")
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catalysts = c.get("llm_catalysts", "")
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risks = c.get("llm_risks", "")
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if score < MIN_SCORE:
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skipped += 1
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continue
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if code in existing_codes:
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print(f" ⏭ {code} {name} (已在自选/持仓中)")
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if code in existing:
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continue
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entry = {
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notes_parts = [f"AlphaSift/{strategy} 评分{score}"]
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if reason:
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notes_parts.append(reason[:150])
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if catalysts:
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notes_parts.append(f"催化剂:{catalysts[:100]}")
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new_stocks.append({
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"code": code,
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"name": name,
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"price": c.get("price", 0),
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"tag": f"alpha_sift_{strategy}",
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"source": "alpha_sift",
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"added_at": datetime.now().strftime("%Y-%m-%d %H:%M"),
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"alpha_score": score,
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"alpha_reason": (c.get("reason", "") or c.get("llm_thesis", ""))[:200],
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"source_detail": {
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"strategy": strategy,
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"score": score,
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"date": date_str,
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"reason": reason[:300],
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"catalysts": catalysts[:200] if catalysts else "",
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"risks": risks[:200] if risks else "",
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"market_view": market_view[:300] if market_view else "",
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},
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"notes": " | ".join(notes_parts),
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"added_at": time_str,
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"added_by": "AlphaSift",
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"analysis": {},
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}
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new_stocks.append(entry)
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existing_codes.add(code)
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})
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existing.add(code)
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print(f" 过滤: {len(new_stocks)} 新标的 (跳过{skipped}只评分不足)")
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if not new_stocks:
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print(" ℹ️ 没有符合条件的新标的")
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print(" 无符合条件的新标的")
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return
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# 限制数量
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new_stocks = new_stocks[:MAX_ADD]
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print(f"\n ✅ 新增 {len(new_stocks)} 只到自选池:")
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print(f"\n 新增 {len(new_stocks)} 只到自选池:")
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for s in new_stocks:
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print(f" {s['code']} {s['name']} (评分{s['alpha_score']})")
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print(f" {s['code']} {s['name']} (评分{s['source_detail']['score']})")
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if s['source_detail'].get('reason'):
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print(f" {s['source_detail']['reason'][:120]}")
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if dry_run:
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print("\n [DRY RUN] 未实际写入")
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print("\n [DRY RUN] 未写入")
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return
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# 4. 写入 watchlist.json
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# 4. 写入
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wl = load_json(WATCHLIST_PATH) or {"stocks": []}
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wl["stocks"].extend(new_stocks)
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wl["updated_at"] = datetime.now().strftime("%Y-%m-%d %H:%M")
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wl["updated_at"] = time_str
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save_json(WATCHLIST_PATH, wl)
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print(f" 已写入 {WATCHLIST_PATH}")
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print(f"\n 已写入 {WATCHLIST_PATH}")
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# 5. 触发策略生成
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print("\n🔄 调用 regenerate_all() 生成策略...")
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# 5. 策略生成
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print("\n 调用 regenerate_all() 生成策略...")
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try:
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sys.path.insert(0, str(MOFIN_DATA.parent))
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from strategy_lifecycle import regenerate_all
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result = regenerate_all(stdout=True)
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if result:
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print(f" 策略生成完成: total={result.get('total',0)} ok={result.get('ok',0)}")
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r = regenerate_all(stdout=True)
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if r:
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print(f" 完成: {r.get('ok',0)}/{r.get('total',0)} 只策略已生成")
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print(f" price_monitor 将在 2 分钟内自动开始监控")
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except Exception as e:
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print(f" ⚠️ regenerate_all() 失败: {e}")
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print(" 新股票已加入自选池，下次 cron 会自动生成策略")
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print(f" WARN: regenerate_all 失败: {e}")
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print(f" 股票已加入自选池，下次 cron 会自动处理")
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# ── CLI ──────────────────────────────────────────────────────────────
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def list_strategies():
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r = api("/api/v1/alphasift/strategies")
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if r and r.get("strategies"):
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print("AlphaSift 策略:")
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for s in r["strategies"]:
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print(f" {s['id']:20s} {s.get('name','?'):15s} {s.get('description','')[:60]}")
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def main():
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parser = argparse.ArgumentParser(description="AlphaSift → MoFin 自动对接")
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parser.add_argument("--strategy", default=DEFAULT_STRATEGY,
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help=f"选股策略 (默认: {DEFAULT_STRATEGY})")
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parser.add_argument("--market", default=DEFAULT_MARKET,
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help=f"市场 (默认: {DEFAULT_MARKET})")
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parser.add_argument("--max", type=int, default=DEFAULT_MAX,
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help=f"AlphaSift 最多返回 (默认: {DEFAULT_MAX})")
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parser.add_argument("--min-score", type=int, default=MIN_SCORE,
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help=f"最低评分 (默认: {MIN_SCORE})")
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parser.add_argument("--dry-run", action="store_true",
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help="只看不写")
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global MIN_SCORE
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parser = argparse.ArgumentParser(description="AlphaSift → MoFin")
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parser.add_argument("--strategy", default=DEFAULT_STRATEGY)
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parser.add_argument("--market", default=DEFAULT_MARKET)
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parser.add_argument("--max", type=int, default=DEFAULT_MAX)
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parser.add_argument("--min-score", type=int, default=MIN_SCORE)
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parser.add_argument("--dry-run", action="store_true")
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args = parser.parse_args()
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MIN_SCORE = args.min_score
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# 列出可用策略
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if args.strategy == "list":
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r = call_api("/api/v1/alphasift/strategies")
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if r and r.get("strategies"):
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print("可用策略:")
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for s in r["strategies"]:
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print(f" {s['id']}: {s.get('name','?')} - {s.get('description','')[:60]}")
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list_strategies()
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return
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run_screen(args.strategy, args.market, args.max, args.dry_run)
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