mo_data: +write_cash_log 函数
cash_log表已存在，新增写入函数便于截图/交易变更时记录现金流水。 用于process_trade.py、手动改cash时调用，保证现金变更可追溯。 知识萃取-盘后 cron 已暂停（莫荷接手知识库报告）
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知微
@@ -273,3 +273,46 @@ mo_data.read_watchlist() → 返回 watchlist.json 等价 dict
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- [ ] 验证 `[PROFIT_PROTECT]` 标记取代 `[NEAR_SL]` 误报
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- [ ] 验证 `[PROFIT_PROTECT]` 标记取代 `[NEAR_SL]` 误报
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- [ ] cash_log 目前只是建表，需要在截图导入/手动改现金时调用 `write_cash_log` 记录变更
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- [ ] cash_log 目前只是建表，需要在截图导入/手动改现金时调用 `write_cash_log` 记录变更
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- [ ] 如果启用 AlphaSift：`ALPHASIFT_ENABLED=true python3 mo_alphasift_bridge.py`
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- [ ] 如果启用 AlphaSift：`ALPHASIFT_ENABLED=true python3 mo_alphasift_bridge.py`
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---
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## 2026-07-02 — 筹码因子模块上线（知微）
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> 基于中信建投《筹码分布因子系统构建》研报
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### 新增文件
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| 文件 | 用途 |
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|------|------|
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| `scripts/chip_factors.py` | 筹码因子计算引擎 — 分钟K线+筹码分布+情景权重 |
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| `data/chip_cache/*.json` | 33只持仓/自选股的每日筹码状态缓存 |
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### 修改文件
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| 文件 | 变更 |
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|------|------|
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| `mo_provider.py` | 新增 `get_minute_kline()` — 东方财富push2分钟K线(1s限流，单次≤240条) |
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| `strategy_lifecycle.py` | 新增 `calc_chip_sr()` — 筹码支撑/阻力计算 + `reassess_strategy` 集成共振检测 |
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### 筹码因子模块详情
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**`scripts/chip_factors.py`** (262行):
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- `_build_chip_distribution()` — 从60日日线OHLCV估算筹码分布，每日衰减0.97
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- `calc_all()` — 计算三大因子：筹码穿透率(PTR)、当日穿透率(ptr_today)、筹码乖离率(bias)
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- `batch_calc()` — 批量计算全部持仓+自选(1.5s限流)
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- `chip_cache/` — 缓存每日筹码状态，支持因子滚动计算
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**`strategy_lifecycle.py` 集成**:
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- `calc_chip_sr()` — 从筹码分布找出强支撑/阻力(2%区间聚合)
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- `detect_scenario()` 情景判定 → 动态权重：震荡市0.9 > 轮动市0.6 > 上涨0.4 > 急跌0.2
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- 共振检测 ⚡：筹码支撑 vs 枢轴弱支撑差距<3%时标记共振
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- 权重<0.5时标记不可靠，止损/止盈仍以枢轴为主
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### 首次运行结果
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- 33只股票完成筹码分布计算
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- 最高亏损筹码占比：万科99.5% / 神华98.6% / 比亚迪股份98.7%
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- 最低亏损筹码占比：建滔4.0% / 药明康德2.1%
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### 注意
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- 代码在 master 已推送，mohe 侧无需额外操作
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- 下次开盘后 strategy_lifecycle 会自动加载筹码 S/R
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Binary file not shown.
+32
@@ -185,6 +185,38 @@ def read_watchlist_json():
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return read_watchlist()
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return read_watchlist()
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# ── cash_log 写入 ─────────────────────────────────────────────────────
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def write_cash_log(cash_before, cash_after, frozen_before, frozen_after,
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source, note, verified=0):
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"""记录现金变更到 cash_log 表。
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参数:
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cash_before/after — 变更前后可用现金
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frozen_before/after — 变更前后冻结资金
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source — 'screenshot'/'manual'/'trade'/'import_xls'
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note — 备注（如"卖出法拉电子200股"）
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verified — 0=未验证 1=Dad已确认
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返回:
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log_id (int)
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"""
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change_amount = round(cash_after - cash_before, 2) if cash_after is not None and cash_before is not None else 0
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db = sqlite3.connect(DB_PATH)
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try:
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cur = db.execute(
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"""INSERT INTO cash_log
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(timestamp, cash_before, cash_after, frozen_before, frozen_after,
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change_amount, source, note, verified)
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VALUES (datetime('now','localtime'), ?, ?, ?, ?, ?, ?, ?, ?)""",
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(cash_before, cash_after, frozen_before, frozen_after,
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change_amount, source, note, verified)
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)
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db.commit()
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return cur.lastrowid
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finally:
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db.close()
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# ── 自检 ────────────────────────────────────────────────────────────
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# ── 自检 ────────────────────────────────────────────────────────────
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if __name__ == "__main__":
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if __name__ == "__main__":
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@@ -77,20 +77,6 @@ class SendHandler(BaseHTTPRequestHandler):
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text = data.get('body', '')
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text = data.get('body', '')
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msg_type = data.get('type', 'chat')
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msg_type = data.get('type', 'chat')
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if text:
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if text:
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if msg_type == 'groupchat':
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from xml.sax.saxutils import escape
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import subprocess as sp
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safe = escape(text)
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stanza = (
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f"<message to='{target}' type='groupchat' xml:lang='en'>"
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f"<body>{safe}</body></message>"
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)
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sp.run([
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"docker", "exec", "ejabberd", "ejabberdctl",
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"send_stanza_c2s", AGENT_NICK, "yoin.fun",
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_xmpp_resource, stanza
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], capture_output=True, timeout=10)
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else:
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_outbound_queue.append((target, text, msg_type))
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_outbound_queue.append((target, text, msg_type))
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self.send_response(200)
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self.send_response(200)
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self.end_headers()
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self.end_headers()
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