migrate: last 4 JSON files — live_prices, market, mtf_cache, capital_flow → DB

_watchdog_report.py

@@ -0,0 +1,35 @@
+import sys; sys.path.insert(0, '/home/hmo/MoFin')
+from mo_data import *
+
+# Portfolio
+pf = read_portfolio()
+ta = pf.get('total_assets',0)
+ca = pf.get('cash',0)
+pp = pf.get('position_pct',0)
+print(f"总资产: {ta:.0f} 现金: {ca:.0f} 仓位: {pp:.1f}%")
+for h in pf.get('holdings', []):
+    c = h.get('currency','CNY')
+    price = h['price']
+    cost = h['cost']
+    profit_pct = (price/cost - 1)*100 if cost and cost else 0
+    ps = f"{price:.2f}{' HKD' if c=='HKD' else ''}"
+    pp_h = h.get('position_pct')
+    if pp_h is None: pp_h = 0
+    print(f"  {h['code']} {h['name']} 价{ps} 仓{pp_h:.1f}% 盈{profit_pct:.1f}%")
+
+# Watchlist
+print()
+wl = read_watchlist()
+for s in wl.get('stocks',[]):
+    try:
+        c = s.get('currency','CNY')
+        price = s.get('price')
+        if price is None: price = 0
+        ps = f"{price:.2f}{' HKD' if c=='HKD' else ''}"
+        el = s.get('entry_low')
+        eh = s.get('entry_high')
+        enl = f"{el:.2f}" if el is not None else '?'
+        enh = f"{eh:.2f}" if eh is not None else '?'
+        print(f"  自选 {s['code']} {s.get('name','')} 价{ps} 入{enl}~{enh}")
+    except Exception as e:
+        print(f"  ERROR {s.get('code','?')}: {e}")

data/candidate_pool.json

@@ -1,6 +1,6 @@
 {
-  "last_updated": "2026-07-03 11:32",
+  "last_updated": "2026-07-03 13:42",
-  "total_candidates": 5,
+  "total_candidates": 11,
   "sectors_analyzed_today": [
     "半导体",
     "金属新材料",
@@ -503,6 +503,198 @@
       "drop_reason": null,
       "trend_warning": false,
       "trend_note": ""
+    },
+    {
+      "code": "300124",
+      "name": "汇川技术",
+      "sector": "自动化设备",
+      "xiaoguo_score": 8.5,
+      "xiaoguo_reason": "工控龙头，PLC/伺服/机器人核心部件全覆盖，受益设备更新与新能源自动化需求，业绩确定性强，机构持仓集中。",
+      "xiaoguo_strategy": {
+        "entry_range": "58.00-62.00元",
+        "stop_loss": "54.00元",
+        "target": "72.00-78.00元"
+      },
+      "verified_price": 72.94,
+      "verified_change": 6.64,
+      "added_at": "2026-07-03 13:37",
+      "last_updated": "2026-07-03 13:37",
+      "num_observations": 1,
+      "score_history": [
+        {
+          "date": "2026-07-03 13:37",
+          "score": 8.5
+        }
+      ],
+      "zhiwei_star": null,
+      "zhiwei_reviewed": false,
+      "zhiwei_reviewed_at": null,
+      "promoted": false,
+      "promoted_at": null,
+      "dropped": false,
+      "drop_reason": null,
+      "trend_warning": false,
+      "trend_note": ""
+    },
+    {
+      "code": "002747",
+      "name": "埃斯顿",
+      "sector": "自动化设备",
+      "xiaoguo_score": 7.5,
+      "xiaoguo_reason": "国产工业机器人第一梯队，核心零部件自研率高，政策扶持明确，但短期毛利率承压，适合波段操作。",
+      "xiaoguo_strategy": {
+        "entry_range": "18.00-20.00元",
+        "stop_loss": "16.50元",
+        "target": "24.00-26.00元"
+      },
+      "verified_price": 44.77,
+      "verified_change": 10.0,
+      "added_at": "2026-07-03 13:37",
+      "last_updated": "2026-07-03 13:37",
+      "num_observations": 1,
+      "score_history": [
+        {
+          "date": "2026-07-03 13:37",
+          "score": 7.5
+        }
+      ],
+      "zhiwei_star": null,
+      "zhiwei_reviewed": false,
+      "zhiwei_reviewed_at": null,
+      "promoted": false,
+      "promoted_at": null,
+      "dropped": false,
+      "drop_reason": null,
+      "trend_warning": false,
+      "trend_note": ""
+    },
+    {
+      "code": "300607",
+      "name": "拓斯达",
+      "sector": "自动化设备",
+      "xiaoguo_score": 7.0,
+      "xiaoguo_reason": "自动化产线集成+机器人双轮驱动，市值适中弹性大，AI视觉与协作机器人布局进展快，但业绩波动性较高。",
+      "xiaoguo_strategy": {
+        "entry_range": "12.00-13.50元",
+        "stop_loss": "11.00元",
+        "target": "16.00-18.00元"
+      },
+      "verified_price": 52.92,
+      "verified_change": 13.46,
+      "added_at": "2026-07-03 13:37",
+      "last_updated": "2026-07-03 13:37",
+      "num_observations": 1,
+      "score_history": [
+        {
+          "date": "2026-07-03 13:37",
+          "score": 7.0
+        }
+      ],
+      "zhiwei_star": null,
+      "zhiwei_reviewed": false,
+      "zhiwei_reviewed_at": null,
+      "promoted": false,
+      "promoted_at": null,
+      "dropped": false,
+      "drop_reason": null,
+      "trend_warning": false,
+      "trend_note": ""
+    },
+    {
+      "code": "601689",
+      "name": "拓普集团",
+      "sector": "汽车零部件",
+      "xiaoguo_score": 8.5,
+      "xiaoguo_reason": "特斯拉/华为核心供应商，智能底盘+轻量化双轮驱动，Q2业绩预期强劲，资金持续加仓，技术面突破年线后回踩确认支撑。",
+      "xiaoguo_strategy": {
+        "entry_range": "58.5-60.2",
+        "stop_loss": "56.0",
+        "target": "68.0-72.0"
+      },
+      "verified_price": 62.43,
+      "verified_change": 10.01,
+      "added_at": "2026-07-03 13:40",
+      "last_updated": "2026-07-03 13:40",
+      "num_observations": 1,
+      "score_history": [
+        {
+          "date": "2026-07-03 13:40",
+          "score": 8.5
+        }
+      ],
+      "zhiwei_star": null,
+      "zhiwei_reviewed": false,
+      "zhiwei_reviewed_at": null,
+      "promoted": false,
+      "promoted_at": null,
+      "dropped": false,
+      "drop_reason": null,
+      "trend_warning": false,
+      "trend_note": ""
+    },
+    {
+      "code": "002126",
+      "name": "银轮股份",
+      "sector": "汽车零部件",
+      "xiaoguo_score": 8.0,
+      "xiaoguo_reason": "热管理龙头，绑定比亚迪/理想/海外车企，订单饱满，估值合理，趋势稳健，机构持仓集中，适合中线波段。",
+      "xiaoguo_strategy": {
+        "entry_range": "24.8-25.5",
+        "stop_loss": "23.5",
+        "target": "29.0-31.0"
+      },
+      "verified_price": 53.39,
+      "verified_change": 5.76,
+      "added_at": "2026-07-03 13:40",
+      "last_updated": "2026-07-03 13:40",
+      "num_observations": 1,
+      "score_history": [
+        {
+          "date": "2026-07-03 13:40",
+          "score": 8.0
+        }
+      ],
+      "zhiwei_star": null,
+      "zhiwei_reviewed": false,
+      "zhiwei_reviewed_at": null,
+      "promoted": false,
+      "promoted_at": null,
+      "dropped": false,
+      "drop_reason": null,
+      "trend_warning": false,
+      "trend_note": ""
+    },
+    {
+      "code": "603596",
+      "name": "伯特利",
+      "sector": "汽车零部件",
+      "xiaoguo_score": 8.2,
+      "xiaoguo_reason": "线控制动市占率领先，智能驾驶渗透率提升直接受益，研发壁垒高，技术面放量突破平台，资金介入明显。",
+      "xiaoguo_strategy": {
+        "entry_range": "42.0-43.5",
+        "stop_loss": "40.0",
+        "target": "48.0-52.0"
+      },
+      "verified_price": 27.65,
+      "verified_change": 9.98,
+      "added_at": "2026-07-03 13:40",
+      "last_updated": "2026-07-03 13:40",
+      "num_observations": 1,
+      "score_history": [
+        {
+          "date": "2026-07-03 13:40",
+          "score": 8.2
+        }
+      ],
+      "zhiwei_star": null,
+      "zhiwei_reviewed": false,
+      "zhiwei_reviewed_at": null,
+      "promoted": false,
+      "promoted_at": null,
+      "dropped": false,
+      "drop_reason": null,
+      "trend_warning": false,
+      "trend_note": ""
     }
   ]
 }

data/multi_tf_cache.json

@@ -960,6 +960,14 @@
         "high": 151.69,
         "low": 141.26,
         "volume": 94902364.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 144.89,
+        "close": 143.0,
+        "high": 146.45,
+        "low": 140.4,
+        "volume": 56102965.0
       }
     ],
     "weekly": [
@@ -1254,7 +1262,7 @@
         "volume": 147766189.0
       }
     ],
-    "updated_at": 1783051747.536662
+    "updated_at": 1783056811.510267
   },
   "688795": {
     "daily": [
@@ -2217,6 +2225,14 @@
         "high": 687.04,
         "low": 639.4,
         "volume": 3085878.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 643.88,
+        "close": 649.03,
+        "high": 664.48,
+        "low": 633.01,
+        "volume": 1568495.0
       }
     ],
     "weekly": [
@@ -2479,7 +2495,7 @@
         "volume": 4788252.0
       }
     ],
-    "updated_at": 1783051740.058768
+    "updated_at": 1783056712.9785304
   },
   "000657": {
     "daily": [
@@ -3442,6 +3458,14 @@
         "high": 101.5,
         "low": 90.68,
         "volume": 1054773.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 95.0,
+        "close": 92.06,
+        "high": 96.53,
+        "low": 87.88,
+        "volume": 721833.0
       }
     ],
     "weekly": [
@@ -3736,7 +3760,7 @@
         "volume": 1051508.0
       }
     ],
-    "updated_at": 1783051278.4453125
+    "updated_at": 1783056502.3469434
   },
   "000700": {
     "daily": [
@@ -4699,6 +4723,14 @@
         "high": 16.87,
         "low": 15.59,
         "volume": 1137587.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 16.08,
+        "close": 17.7,
+        "high": 17.88,
+        "low": 16.08,
+        "volume": 1515920.0
       }
     ],
     "weekly": [
@@ -4993,7 +5025,7 @@
         "volume": 1265397.0
       }
     ],
-    "updated_at": 1783051627.982171
+    "updated_at": 1783056719.8422928
   },
   "000711": {
     "daily": [
@@ -5956,6 +5988,14 @@
         "high": 5.01,
         "low": 4.87,
         "volume": 443973.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 5.18,
+        "close": 5.26,
+        "high": 5.26,
+        "low": 5.1,
+        "volume": 1131235.0
       }
     ],
     "weekly": [
@@ -6250,7 +6290,7 @@
         "volume": 496248.0
       }
     ],
-    "updated_at": 1783051282.8847363
+    "updated_at": 1783056503.0905344
   },
   "001309": {
     "daily": [
@@ -7213,6 +7253,14 @@
         "high": 872.83,
         "low": 806.0,
         "volume": 160378.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 804.75,
+        "close": 888.1,
+        "high": 892.1,
+        "low": 795.0,
+        "volume": 144171.0
       }
     ],
     "weekly": [
@@ -7507,7 +7555,7 @@
         "volume": 216663.0
       }
     ],
-    "updated_at": 1783051286.5401492
+    "updated_at": 1783056668.8085573
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   "002594": {
     "daily": [
@@ -8470,6 +8518,14 @@
         "high": 85.67,
         "low": 81.9,
         "volume": 825046.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 83.73,
+        "close": 86.66,
+        "high": 87.28,
+        "low": 83.6,
+        "volume": 477402.0
       }
     ],
     "weekly": [
@@ -8764,7 +8820,7 @@
         "volume": 934285.0
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-    "updated_at": 1783051286.9981902
+    "updated_at": 1783056675.2141986
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   "00700": {
     "daily": [
@@ -9727,6 +9783,14 @@
         "high": 447.0,
         "low": 429.4,
         "volume": 40905100.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 433.0,
+        "close": 432.6,
+        "high": 445.8,
+        "low": 432.4,
+        "volume": 15135668.0
       }
     ],
     "weekly": [
@@ -10029,7 +10093,7 @@
         "volume": 13032847.0
       }
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-    "updated_at": 1783051633.4890287
+    "updated_at": 1783056724.989126
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   "00968": {
     "daily": [
@@ -12257,6 +12321,14 @@
         "high": 84.2,
         "low": 78.55,
         "volume": 178219425.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 80.0,
+        "close": 78.95,
+        "high": 81.45,
+        "low": 77.35,
+        "volume": 71251123.0
       }
     ],
     "weekly": [
@@ -12559,7 +12631,7 @@
         "volume": 60114819.0
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-    "updated_at": 1783051638.5061805
+    "updated_at": 1783056730.0097694
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   "01070": {
     "daily": [
@@ -14787,6 +14859,14 @@
         "high": 40.4,
         "low": 39.16,
         "volume": 16452660.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 39.7,
+        "close": 39.9,
+        "high": 40.5,
+        "low": 39.62,
+        "volume": 6092471.0
       }
     ],
     "weekly": [
@@ -15089,7 +15169,7 @@
         "volume": 2870057.0
       }
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-    "updated_at": 1783051643.521601
+    "updated_at": 1783056735.0304337
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   "01211": {
     "daily": [
@@ -16052,6 +16132,14 @@
         "high": 79.6,
         "low": 74.95,
         "volume": 54549471.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 81.2,
+        "close": 82.85,
+        "high": 83.35,
+        "low": 80.0,
+        "volume": 25755799.0
       }
     ],
     "weekly": [
@@ -16354,7 +16442,7 @@
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-    "updated_at": 1783051648.5394585
+    "updated_at": 1783056740.0491588
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   "01478": {
     "daily": [
@@ -17317,6 +17405,14 @@
         "high": 7.08,
         "low": 6.72,
         "volume": 6257000.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 6.72,
+        "close": 7.04,
+        "high": 7.1,
+        "low": 6.72,
+        "volume": 2981000.0
       }
     ],
     "weekly": [
@@ -17619,7 +17715,7 @@
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-    "updated_at": 1783051653.5516405
+    "updated_at": 1783056745.0709894
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   "01888": {
     "daily": [
@@ -18582,6 +18678,14 @@
         "high": 90.1,
         "low": 79.85,
         "volume": 92637274.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 81.0,
+        "close": 85.6,
+        "high": 88.9,
+        "low": 80.6,
+        "volume": 57017840.0
       }
     ],
     "weekly": [
@@ -18884,7 +18988,7 @@
         "volume": 29941901.0
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-    "updated_at": 1783051658.5684023
+    "updated_at": 1783056750.0898428
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   "02202": {
     "daily": [
@@ -19847,6 +19951,14 @@
         "high": 2.27,
         "low": 2.18,
         "volume": 39512590.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 2.25,
+        "close": 2.31,
+        "high": 2.35,
+        "low": 2.23,
+        "volume": 18235400.0
       }
     ],
     "weekly": [
@@ -20149,7 +20261,7 @@
         "volume": 19786580.0
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-    "updated_at": 1783051663.581557
+    "updated_at": 1783056755.496929
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   "02318": {
     "daily": [
@@ -27437,6 +27549,14 @@
         "high": 229.2,
         "low": 198.0,
         "volume": 40078361.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 191.2,
+        "close": 207.2,
+        "high": 210.6,
+        "low": 190.0,
+        "volume": 14255822.0
       }
     ],
     "weekly": [
@@ -27739,7 +27859,7 @@
         "volume": 15066251.0
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-    "updated_at": 1783051668.878092
+    "updated_at": 1783056760.5189984
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   "09868": {
     "daily": [
@@ -31232,6 +31352,14 @@
         "high": 14.6,
         "low": 14.1,
         "volume": 155998.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 14.18,
+        "close": 14.4,
+        "high": 14.53,
+        "low": 14.16,
+        "volume": 102393.0
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     "weekly": [
@@ -31526,7 +31654,7 @@
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-    "updated_at": 1783051674.5847087
+    "updated_at": 1783056765.5414958
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     "daily": [
@@ -32489,6 +32617,14 @@
         "high": 71.79,
         "low": 67.31,
         "volume": 703358.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 67.5,
+        "close": 74.14,
+        "high": 74.23,
+        "low": 67.4,
+        "volume": 691416.0
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     "weekly": [
@@ -32783,7 +32919,7 @@
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-    "updated_at": 1783051344.573262
+    "updated_at": 1783056692.3502543
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   "300308": {
     "daily": [
@@ -33746,6 +33882,14 @@
         "high": 1198.0,
         "low": 1127.4,
         "volume": 317620.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 1130.0,
+        "close": 1158.88,
+        "high": 1188.01,
+        "low": 1124.0,
+        "volume": 230014.0
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     "weekly": [
@@ -34040,7 +34184,7 @@
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-    "updated_at": 1783051680.1109805
+    "updated_at": 1783056770.5614996
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   "300548": {
     "daily": [
@@ -35003,6 +35147,14 @@
         "high": 245.0,
         "low": 220.0,
         "volume": 174041.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 220.0,
+        "close": 228.99,
+        "high": 231.55,
+        "low": 218.99,
+        "volume": 102806.0
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     "weekly": [
@@ -35297,7 +35449,7 @@
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-    "updated_at": 1783051685.6375031
+    "updated_at": 1783056775.5768287
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   "300750": {
     "daily": [
@@ -36260,6 +36412,14 @@
         "high": 390.99,
         "low": 380.39,
         "volume": 340754.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 381.96,
+        "close": 381.17,
+        "high": 387.95,
+        "low": 380.55,
+        "volume": 157731.0
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     ],
     "weekly": [
@@ -36554,7 +36714,7 @@
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-    "updated_at": 1783051690.893728
+    "updated_at": 1783056780.5942247
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   "301308": {
     "daily": [
@@ -37517,6 +37677,14 @@
         "high": 636.99,
         "low": 592.0,
         "volume": 208005.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 589.0,
+        "close": 634.0,
+        "high": 646.85,
+        "low": 574.1,
+        "volume": 153435.0
       }
     ],
     "weekly": [
@@ -37811,7 +37979,7 @@
         "volume": 296230.0
       }
     ],
-    "updated_at": 1783051380.6922731
+    "updated_at": 1783056696.8459098
   },
   "518880": {
     "daily": [
@@ -38774,6 +38942,14 @@
         "high": 8.484,
         "low": 8.397,
         "volume": 5149790.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 8.71,
+        "close": 8.68,
+        "high": 8.73,
+        "low": 8.68,
+        "volume": 2689807.0
       }
     ],
     "weekly": [
@@ -39068,7 +39244,7 @@
         "volume": 3915247.0
       }
     ],
-    "updated_at": 1783051695.915503
+    "updated_at": 1783056785.6140218
   },
   "600519": {
     "daily": [
@@ -40031,6 +40207,14 @@
         "high": 1215.52,
         "low": 1190.51,
         "volume": 50870.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 1205.24,
+        "close": 1189.52,
+        "high": 1210.14,
+        "low": 1188.0,
+        "volume": 23088.0
       }
     ],
     "weekly": [
@@ -40325,7 +40509,7 @@
         "volume": 64803.0
       }
     ],
-    "updated_at": 1783051561.7579694
+    "updated_at": 1783056699.260756
   },
   "600563": {
     "daily": [
@@ -41288,6 +41472,14 @@
         "high": 173.3,
         "low": 164.3,
         "volume": 112859.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 160.27,
+        "close": 159.59,
+        "high": 163.68,
+        "low": 153.52,
+        "volume": 75944.0
       }
     ],
     "weekly": [
@@ -41582,7 +41774,7 @@
         "volume": 180947.0
       }
     ],
-    "updated_at": 1783051700.9725504
+    "updated_at": 1783056791.4344049
   },
   "601318": {
     "daily": [
@@ -42545,6 +42737,14 @@
         "high": 50.2,
         "low": 48.8,
         "volume": 920130.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 49.5,
+        "close": 48.43,
+        "high": 49.78,
+        "low": 48.41,
+        "volume": 556535.0
       }
     ],
     "weekly": [
@@ -42839,7 +43039,7 @@
         "volume": 1746202.0
       }
     ],
-    "updated_at": 1783051575.149798
+    "updated_at": 1783056700.660319
   },
   "601899": {
     "daily": [
@@ -43802,6 +44002,14 @@
         "high": 26.96,
         "low": 25.52,
         "volume": 5067417.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 27.5,
+        "close": 27.93,
+        "high": 28.3,
+        "low": 27.41,
+        "volume": 4183914.0
       }
     ],
     "weekly": [
@@ -44096,7 +44304,7 @@
         "volume": 4780454.0
       }
     ],
-    "updated_at": 1783051705.9927075
+    "updated_at": 1783056796.4605315
   },
   "688411": {
     "daily": [
@@ -45059,6 +45267,14 @@
         "high": 272.99,
         "low": 254.8,
         "volume": 6368531.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 255.8,
+        "close": 255.99,
+        "high": 261.48,
+        "low": 251.0,
+        "volume": 2572727.0
       }
     ],
     "weekly": [
@@ -45353,7 +45569,7 @@
         "volume": 13672788.0
       }
     ],
-    "updated_at": 1783051711.208435
+    "updated_at": 1783056801.4764674
   },
   "688630": {
     "daily": [
@@ -46316,6 +46532,14 @@
         "high": 499.95,
         "low": 464.8,
         "volume": 5841815.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 467.98,
+        "close": 497.0,
+        "high": 502.0,
+        "low": 444.55,
+        "volume": 4259432.0
       }
     ],
     "weekly": [
@@ -46610,7 +46834,7 @@
         "volume": 9660790.0
       }
     ],
-    "updated_at": 1783051587.7339969
+    "updated_at": 1783056704.6600807
   },
   "688639": {
     "daily": [
@@ -47573,6 +47797,14 @@
         "high": 17.4,
         "low": 15.98,
         "volume": 9065955.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 17.06,
+        "close": 16.71,
+        "high": 17.2,
+        "low": 16.52,
+        "volume": 4669797.0
       }
     ],
     "weekly": [
@@ -47867,7 +48099,7 @@
         "volume": 13996588.0
       }
     ],
-    "updated_at": 1783051733.2346125
+    "updated_at": 1783056806.4868052
   },
   "688802": {
     "daily": [
@@ -48830,6 +49062,14 @@
         "high": 784.0,
         "low": 721.0,
         "volume": 2036024.0
+      },
+      {
+        "date": "2026-07-03",
+        "open": 731.34,
+        "close": 741.27,
+        "high": 757.88,
+        "low": 713.0,
+        "volume": 1323959.0
       }
     ],
     "weekly": [
@@ -49092,6 +49332,6 @@
         "volume": 3202146.0
       }
     ],
-    "updated_at": 1783051743.6900556
+    "updated_at": 1783056714.5052435
   }
 }

data/portfolio.json

@@ -5,9 +5,9 @@
       "name": "中际旭创",
       "shares": 100,
       "cost": 1316.53,
-      "price": 1157.97,
+      "price": 1145.0,
-      "market_value": 115797.0,
+      "market_value": 114101.0,
-      "change_pct": 1.31,
+      "change_pct": 0.17,
       "currency": "CNY",
       "position_pct": 15.27,
       "_currency": "CNY"
@@ -18,32 +18,32 @@
       "shares": 500,
       "cost": 228.65,
       "price": 178.26,
-      "market_value": 102700.0,
+      "market_value": 89910.0,
       "change_pct": 3.859,
-      "currency": "HKD",
+      "currency": "CNY",
       "position_pct": 13.47,
-      "_currency": "HKD"
+      "_currency": "CNY"
     },
     {
       "code": "01478",
       "name": "丘钛科技",
       "shares": 11000,
       "cost": 11.68,
-      "price": 6.11,
+      "price": 6.1,
-      "market_value": 77550.0,
+      "market_value": 67210.0,
-      "change_pct": 4.911,
+      "change_pct": 4.762,
-      "currency": "HKD",
+      "currency": "CNY",
       "position_pct": 7.97,
-      "_currency": "HKD"
+      "_currency": "CNY"
     },
     {
       "code": "601899",
       "name": "紫金矿业",
       "shares": 2400,
       "cost": 39.89,
-      "price": 28.04,
+      "price": 27.8,
-      "market_value": 67296.0,
+      "market_value": 66864.0,
-      "change_pct": 6.62,
+      "change_pct": 5.7,
       "currency": "CNY",
       "position_pct": 7.34,
       "_currency": "CNY"
@@ -53,9 +53,9 @@
       "name": "海博思创",
       "shares": 200,
       "cost": 266.95,
-      "price": 257.52,
+      "price": 254.75,
-      "market_value": 51504.0,
+      "market_value": 50842.0,
-      "change_pct": 0.71,
+      "change_pct": -0.38,
       "currency": "CNY",
       "position_pct": 6.31,
       "_currency": "CNY"
@@ -65,9 +65,9 @@
       "name": "中芯国际",
       "shares": 300,
       "cost": 126.07,
-      "price": 143.65,
+      "price": 142.97,
-      "market_value": 43095.0,
+      "market_value": 42600.0,
-      "change_pct": -0.31,
+      "change_pct": -0.78,
       "currency": "CNY",
       "position_pct": 5.44,
       "_currency": "CNY"
@@ -78,20 +78,20 @@
       "shares": 500,
       "cost": 76.5,
       "price": 74.17,
-      "market_value": 42600.0,
+      "market_value": 37325.0,
       "change_pct": 2.088,
-      "currency": "HKD",
+      "currency": "CNY",
       "position_pct": 5.28,
-      "_currency": "HKD"
+      "_currency": "CNY"
     },
     {
       "code": "688639",
       "name": "华恒生物",
       "shares": 2800,
       "cost": 21.51,
-      "price": 16.69,
+      "price": 16.72,
-      "market_value": 46732.0,
+      "market_value": 46900.0,
-      "change_pct": -1.53,
+      "change_pct": -1.36,
       "currency": "CNY",
       "position_pct": 5.25,
       "_currency": "CNY"
@@ -101,9 +101,9 @@
       "name": "宁德时代",
       "shares": 100,
       "cost": 401.78,
-      "price": 384.16,
+      "price": 380.24,
-      "market_value": 38416.0,
+      "market_value": 38032.0,
-      "change_pct": 0.47,
+      "change_pct": -0.55,
       "currency": "CNY",
       "position_pct": 4.64,
       "_currency": "CNY"
@@ -113,57 +113,57 @@
       "name": "比亚迪股份",
       "shares": 600,
       "cost": 90.92,
-      "price": 71.66,
+      "price": 71.83,
-      "market_value": 49560.0,
+      "market_value": 43044.0,
-      "change_pct": 5.556,
+      "change_pct": 5.811,
-      "currency": "HKD",
+      "currency": "CNY",
       "position_pct": 4.62,
-      "_currency": "HKD"
+      "_currency": "CNY"
     },
     {
       "code": "02202",
       "name": "万科企业",
       "shares": 19700,
       "cost": 4.05,
-      "price": 2.02,
+      "price": 1.99,
-      "market_value": 45704.0,
+      "market_value": 39203.0,
-      "change_pct": 4.484,
+      "change_pct": 2.69,
-      "currency": "HKD",
+      "currency": "CNY",
       "position_pct": 4.6,
-      "_currency": "HKD"
+      "_currency": "CNY"
     },
     {
       "code": "00700",
       "name": "腾讯",
       "shares": 100,
       "cost": null,
-      "price": 379.05,
+      "price": 376.8,
-      "market_value": 43700.0,
+      "market_value": 37541.0,
-      "change_pct": 1.627,
+      "change_pct": 1.023,
-      "currency": "HKD",
+      "currency": "CNY",
       "position_pct": null,
-      "_currency": "HKD"
+      "_currency": "CNY"
     },
     {
       "code": "00981",
       "name": "中芯国际",
       "shares": 500,
       "cost": 65.84,
-      "price": 69.1,
+      "price": 68.41,
-      "market_value": 39825.0,
+      "market_value": 34440.0,
-      "change_pct": -0.871,
+      "change_pct": -1.866,
-      "currency": "HKD",
+      "currency": "CNY",
       "position_pct": 4.2,
-      "_currency": "HKD"
+      "_currency": "CNY"
     },
     {
       "code": "300548",
       "name": "长芯博创",
       "shares": 100,
       "cost": 231.46,
-      "price": 227.0,
+      "price": 226.5,
-      "market_value": 22700.0,
+      "market_value": 22599.0,
-      "change_pct": 2.25,
+      "change_pct": 2.03,
       "currency": "CNY",
       "position_pct": 3.2,
       "_currency": "CNY"
@@ -173,9 +173,9 @@
       "name": "黄金ETF华安",
       "shares": 2400,
       "cost": 12.19,
-      "price": 8.69,
+      "price": 8.67,
-      "market_value": 20856.0,
+      "market_value": 20832.0,
-      "change_pct": 2.49,
+      "change_pct": 2.32,
       "currency": "CNY",
       "position_pct": 2.45,
       "_currency": "CNY"
@@ -185,9 +185,9 @@
       "name": "中科电气",
       "shares": 1400,
       "cost": 22.29,
-      "price": 14.3,
+      "price": 14.38,
-      "market_value": 20020.0,
+      "market_value": 20062.0,
-      "change_pct": 0.92,
+      "change_pct": 1.48,
       "currency": "CNY",
       "position_pct": 2.42,
       "_currency": "CNY"
@@ -197,9 +197,9 @@
       "name": "模塑科技",
       "shares": 1400,
       "cost": 14.83,
-      "price": 17.37,
+      "price": 17.62,
-      "market_value": 24318.0,
+      "market_value": 25088.0,
-      "change_pct": 2.96,
+      "change_pct": 4.45,
       "currency": "CNY",
       "position_pct": 2.41,
       "_currency": "CNY"
@@ -209,9 +209,9 @@
       "name": "法拉电子",
       "shares": 100,
       "cost": 147.18,
-      "price": 161.71,
+      "price": 160.0,
-      "market_value": 16171.0,
+      "market_value": 15900.0,
-      "change_pct": -1.58,
+      "change_pct": -2.62,
       "currency": "CNY",
       "position_pct": 2.3,
       "_currency": "CNY"
@@ -221,20 +221,20 @@
       "name": "中国神华",
       "shares": 500,
       "cost": 39.79,
-      "price": 34.84,
+      "price": 34.59,
-      "market_value": 20090.0,
+      "market_value": 17305.0,
-      "change_pct": 1.465,
+      "change_pct": 0.758,
-      "currency": "HKD",
+      "currency": "CNY",
       "position_pct": 2.14,
-      "_currency": "HKD"
+      "_currency": "CNY"
     }
   ],
-  "total_assets": 864781.03,
+  "total_assets": 860913.13,
-  "total_mv": 784305.03,
+  "total_mv": 780437.13,
   "stock_value": null,
   "cash": 80476.0,
   "frozen_cash": 0.0,
-  "position_pct": 90.69,
+  "position_pct": 90.65,
   "currency": "CNY",
-  "updated_at": "2026-07-03 12:10"
+  "updated_at": "2026-07-03 13:42"
 }

data/price_events.json

@@ -9109,6 +9109,26 @@
       "event_label": "止盈区间",
       "timestamp": "2026-07-03T11:54:31.001389",
       "date": "2026-07-03"
+    },
+    {
+      "code": "000700",
+      "name": "模塑科技",
+      "event_type": "entry_zone",
+      "price": 17.92,
+      "trigger_value": "15.5~18.08",
+      "event_label": "买入区间",
+      "timestamp": "2026-07-03T13:28:17.259162",
+      "date": "2026-07-03"
+    },
+    {
+      "code": "000700",
+      "name": "模塑科技",
+      "event_type": "entry_zone",
+      "price": 17.88,
+      "trigger_value": "15.5~18.08",
+      "event_label": "买入区间",
+      "timestamp": "2026-07-03T13:30:30.458142",
+      "date": "2026-07-03"
     }
   ]
 }

data/price_history.json

@@ -25,8 +25,8 @@
     {
       "date": "2026-07-03",
       "high": 1215.52,
-      "low": 1190.5,
+      "low": 1188.0,
-      "close": 1191.31
+      "close": 1188.7
     }
   ],
   "02202": [
@@ -61,8 +61,8 @@
     {
       "date": "2026-07-03",
       "high": 50.2,
-      "low": 48.6,
+      "low": 48.4,
-      "close": 48.7
+      "close": 48.44
     }
   ],
   "02359": [
@@ -118,7 +118,7 @@
       "date": "2026-07-03",
       "high": 502.0,
       "low": 444.55,
-      "close": 495.95
+      "close": 494.57
     }
   ],
   "06160": [
@@ -154,7 +154,7 @@
       "date": "2026-07-03",
       "high": 687.04,
       "low": 633.01,
-      "close": 654.0
+      "close": 646.83
     }
   ],
   "09868": [
@@ -194,9 +194,9 @@
     },
     {
       "date": "2026-07-03",
-      "high": 753.88,
+      "high": 757.88,
       "low": 713.0,
-      "close": 744.0
+      "close": 733.9
     }
   ],
   "300124": [
@@ -208,9 +208,9 @@
     },
     {
       "date": "2026-07-03",
-      "high": 72.38,
+      "high": 74.63,
       "low": 67.31,
-      "close": 72.29
+      "close": 73.13
     }
   ],
   "000657": [
@@ -224,7 +224,7 @@
       "date": "2026-07-03",
       "high": 101.5,
       "low": 87.88,
-      "close": 91.88
+      "close": 91.78
     }
   ],
   "000711": [
@@ -250,9 +250,9 @@
     },
     {
       "date": "2026-07-03",
-      "high": 882.5,
+      "high": 892.1,
       "low": 795.0,
-      "close": 874.23
+      "close": 887.87
     }
   ],
   "002594": [
@@ -266,7 +266,7 @@
       "date": "2026-07-03",
       "high": 87.28,
       "low": 81.9,
-      "close": 86.56
+      "close": 86.45
     }
   ],
   "00700": [
@@ -332,9 +332,9 @@
   "301308": [
     {
       "date": "2026-07-03",
-      "high": 631.56,
+      "high": 646.85,
       "low": 574.1,
-      "close": 620.0
+      "close": 635.0
     }
   ]
 }

data_freshness.py

@@ -21,13 +21,14 @@ import json, os
 from datetime import datetime, timedelta
 from mo_data import read_portfolio, read_decisions, read_watchlist
 
+
+# live_prices.json 已废弃，所有数据走 DB
 LIVE_PRICES_PATH = "/home/hmo/web-dashboard/data/live_prices.json"
-PORTFOLIO_PATH = "/home/hmo/web-dashboard/data/portfolio.json"
 
 
 def is_market_hours():
     now = datetime.now()
-    if now.weekday() >= 5:  # 周六日
+    if now.weekday() >= 5:
         return False, "weekend"
     t = now.hour * 60 + now.minute
     if 9*60+30 <= t <= 15*60:
@@ -38,42 +39,23 @@ def is_market_hours():
 def check_fresh():
     """返回 (ok: bool, msg: str)"""
     now = datetime.now()
-    
-    # 先看是不是交易日
     in_market, period = is_market_hours()
-    
     max_age_min = 5 if in_market else 120
 
-    # 主指标：live_prices.json
+    # 主指标：DB portfolio_summary.updated_at
-    if os.path.exists(LIVE_PRICES_PATH):
     try:
-            lp = json.load(open(LIVE_PRICES_PATH))
+        pf = read_portfolio()
-            lp_time = lp.get("updated_at", "")
-            if not lp_time:
-                return False, "live_prices.json updated_at 为空"
-            lp_dt = datetime.fromisoformat(lp_time)
-            age = (now - lp_dt).total_seconds() / 60
-            if age > max_age_min:
-                return False, f"live_prices.json 已 {age:.0f} 分钟未更新（阈值 {max_age_min} 分钟）"
-            return True, f"数据新鲜（{age:.0f} 分钟前）"
-        except Exception as e:
-            return False, f"live_prices.json 读取失败: {e}"
-    else:
-        # fallback: portfolio.json
-        if os.path.exists(PORTFOLIO_PATH):
-            try:
-                pf = mo_data.read_portfolio()
         pf_time = pf.get("updated_at", "")
-                if not pf_time:
+        if pf_time:
-                    return False, "portfolio.json updated_at 为空"
             pf_dt = datetime.fromisoformat(pf_time)
             age = (now - pf_dt).total_seconds() / 60
             if age > max_age_min:
-                    return False, f"portfolio.json 已 {age:.0f} 分钟未更新（阈值 {max_age_min} 分钟）"
+                return False, f"数据已 {age:.0f} 分钟未更新（阈值 {max_age_min} 分钟）"
-                return True, f"数据新鲜（portfolio.json {age:.0f} 分钟前）"
+            return True, f"数据新鲜（{age:.0f} 分钟前）"
     except Exception as e:
-                return False, f"portfolio.json 读取失败: {e}"
+        return False, f"DB 读取失败: {e}"
-        return False, "live_prices.json 和 portfolio.json 均不存在"
+
+    return False, "无法获取数据新鲜度"
 
 
 if __name__ == "__main__":

market_watch.py

@@ -203,10 +203,8 @@ def main():
     }
 
     DATA_DIR.mkdir(parents=True, exist_ok=True)
-    with open(DATA_DIR / "market.json", "w", encoding="utf-8") as f:
-        json.dump(market_data, f, ensure_ascii=False, indent=2)
 
-    # ── SQLite 双写 ──
+    # ── SQLite 写入（替代 market.json）──
     conn = get_conn()
     init_all_tables(conn)
     ok, msg, sid = write_market_snapshot(conn, market_data)

mofin_db.py

@@ -387,6 +387,28 @@ def init_all_tables(conn: sqlite3.Connection):
             last_scanned_at TEXT,
             found_count     INTEGER DEFAULT 0
         );
+
+        -- 实时价格快照（替代 live_prices.json）
+        CREATE TABLE IF NOT EXISTS live_prices (
+            code            TEXT PRIMARY KEY,
+            price           REAL,
+            change_pct      REAL,
+            updated_at      TEXT DEFAULT (datetime('now','localtime'))
+        );
+
+        -- 多周期缓存（替代 multi_tf_cache.json）
+        CREATE TABLE IF NOT EXISTS mtf_cache (
+            code            TEXT PRIMARY KEY,
+            cache_json      TEXT,
+            updated_at      TEXT DEFAULT (datetime('now','localtime'))
+        );
+
+        -- 资金流缓存（替代 capital_flow_cache.json）
+        CREATE TABLE IF NOT EXISTS capital_flow_cache (
+            id              INTEGER PRIMARY KEY AUTOINCREMENT,
+            cache_json      TEXT,
+            updated_at      TEXT DEFAULT (datetime('now','localtime'))
+        );
     """)
     conn.commit()
 
@@ -1120,3 +1142,48 @@ def query_cash_log(conn, limit: int = 20) -> list[dict]:
         "SELECT * FROM cash_log ORDER BY id DESC LIMIT ?", (limit,)
     ).fetchall()
     return [dict(r) for r in rows]
+
+
+# ═══ live_prices / mtf_cache / capital_flow_cache 写函数 ═══
+
+def write_live_prices(conn, prices: dict):
+    """写入实时价格快照（替代 live_prices.json）"""
+    import json
+    for code, info in prices.items():
+        conn.execute(
+            "INSERT OR REPLACE INTO live_prices (code, price, change_pct, updated_at) VALUES (?,?,?,datetime('now','localtime'))",
+            (code, info.get('price'), info.get('change_pct'))
+        )
+
+def read_live_prices(conn) -> dict:
+    rows = conn.execute("SELECT code, price, change_pct FROM live_prices").fetchall()
+    return {r['code']: {'price': r['price'], 'change_pct': r['change_pct']} for r in rows}
+
+
+def write_mtf_cache(conn, code: str, data: dict):
+    """写入多周期缓存（替代 multi_tf_cache.json 单条）"""
+    import json
+    conn.execute(
+        "INSERT OR REPLACE INTO mtf_cache (code, cache_json, updated_at) VALUES (?,?,datetime('now','localtime'))",
+        (code, json.dumps(data, ensure_ascii=False))
+    )
+
+def read_mtf_cache(conn, code: str) -> dict:
+    import json
+    r = conn.execute("SELECT cache_json FROM mtf_cache WHERE code=?", (code,)).fetchone()
+    return json.loads(r['cache_json']) if r else {}
+
+
+def write_capital_flow_cache(conn, data: dict):
+    """写入资金流缓存（替代 capital_flow_cache.json）"""
+    import json
+    conn.execute("DELETE FROM capital_flow_cache")
+    conn.execute(
+        "INSERT INTO capital_flow_cache (cache_json, updated_at) VALUES (?,datetime('now','localtime'))",
+        (json.dumps(data, ensure_ascii=False),)
+    )
+
+def read_capital_flow_cache(conn) -> dict:
+    import json
+    r = conn.execute("SELECT cache_json FROM capital_flow_cache ORDER BY id DESC LIMIT 1").fetchone()
+    return json.loads(r['cache_json']) if r else {}

multi_timeframe.py

@@ -19,7 +19,7 @@ from typing import Optional
 
 DATA_DIR = "/home/hmo/web-dashboard/data"
 HISTORY_PATH = os.path.join(DATA_DIR, "price_history.json")
-MTF_CACHE_PATH = os.path.join(DATA_DIR, "multi_tf_cache.json")  # 多周期缓存独立存储
+# multi_tf_cache.json 已迁移到 DB (mtf_cache 表)
 
 # 腾讯API K线端点
 KLINE_URL = "http://web.ifzq.gtimg.cn/appstock/app/fqkline/get?param={market}{code},{period},,,{count},qfq"
@@ -80,40 +80,47 @@ def _user_agent() -> dict:
 # 多周期缓存TTL（秒）：日K线1小时，周/月K线1天
 _KLINE_CACHE_TTL = {"day": 3600, "week": 86400, "month": 86400}
 
-# 模块级缓存：避免每次fetch_kline都重新读/写大文件
+# 模块级缓存：避免每次 fetch_kline 都重新读 DB
-_MTF_CACHE_DATA = None  # {code: {daily:[], weekly:[], monthly:[], updated_at: float, fundamentals:{}}}
+_MTF_CACHE_DATA = None
-_MTF_CACHE_MTIME = 0    # 文件最后修改时间
+_MTF_CACHE_DIRTY = False
 
 
 def _load_mtf_cache():
-    """加载多周期缓存（带模块级缓存，避免频繁读盘）"""
+    """从 DB 加载多周期缓存"""
-    global _MTF_CACHE_DATA, _MTF_CACHE_MTIME
+    global _MTF_CACHE_DATA
-    import time
+    if _MTF_CACHE_DATA is not None:
+        return _MTF_CACHE_DATA
     try:
-        current_mtime = os.path.getmtime(MTF_CACHE_PATH)
+        import sqlite3
-        if _MTF_CACHE_DATA is not None and current_mtime == _MTF_CACHE_MTIME:
+        db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
-            return _MTF_CACHE_DATA
+        rows = db.execute("SELECT code, cache_json FROM mtf_cache").fetchall()
-        with open(MTF_CACHE_PATH) as f:
-            _MTF_CACHE_DATA = json.load(f)
-        _MTF_CACHE_MTIME = current_mtime
-        return _MTF_CACHE_DATA
-    except (FileNotFoundError, json.JSONDecodeError, OSError):
         _MTF_CACHE_DATA = {}
-        _MTF_CACHE_MTIME = 0
+        for code, json_str in rows:
-        return {}
+            try:
+                _MTF_CACHE_DATA[code] = json.loads(json_str)
+            except:
+                pass
+        db.close()
+    except Exception:
+        _MTF_CACHE_DATA = {}
+    return _MTF_CACHE_DATA
 
 
 def _save_mtf_cache():
-    """将模块级缓存写回磁盘"""
+    """将模块级缓存写回 DB"""
-    global _MTF_CACHE_DATA, _MTF_CACHE_MTIME
+    global _MTF_CACHE_DATA
     if _MTF_CACHE_DATA is None:
         return
     try:
-        os.makedirs(os.path.dirname(MTF_CACHE_PATH), exist_ok=True)
+        import sqlite3
-        with open(MTF_CACHE_PATH, "w") as f:
+        db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
-            json.dump(_MTF_CACHE_DATA, f, ensure_ascii=False, indent=2)
+        for code, data in _MTF_CACHE_DATA.items():
-        import time
+            db.execute(
-        _MTF_CACHE_MTIME = os.path.getmtime(MTF_CACHE_PATH) if os.path.exists(MTF_CACHE_PATH) else time.time()
+                "INSERT OR REPLACE INTO mtf_cache (code, cache_json, updated_at) VALUES (?,?,datetime('now','localtime'))",
+                (code, json.dumps(data, ensure_ascii=False))
+            )
+        db.commit()
+        db.close()
     except Exception:
         pass
 
@@ -582,13 +589,8 @@ def _generate_strategy_adjustment(analysis: dict) -> dict:
 
 
 def _load_local_history(code: str, period: str) -> list:
-    """从本地多周期缓存读取历史数据，不修改 price_history.json"""
+    """从 DB 多周期缓存读取历史数据"""
-    try:
+    data = _load_mtf_cache()
-        with open(MTF_CACHE_PATH) as f:
-            data = json.load(f)
-    except (FileNotFoundError, json.JSONDecodeError):
-        return []
-
     stock = data.get(code, {})
     return stock.get(period, [])
 

price_monitor.py

@@ -12,7 +12,7 @@ from datetime import datetime
 
 # ── MoFin unified model ──────────────────────────────────────────────
 from mo_models import is_hk_stock, get_hk_rate, calc_total_assets, calc_total_mv, calc_position_pct
-from mofin_db import get_conn, write_holdings_batch, write_portfolio_summary, write_price_event, write_watchlist_stock, write_holding_strategy
+from mofin_db import get_conn, write_holdings_batch, write_portfolio_summary, write_price_event, write_watchlist_stock, write_live_prices, read_capital_flow_cache, write_holding_strategy
 from mo_data import read_portfolio, read_decisions, read_watchlist
 
 BREACH_PATH = "/home/hmo/.hermes/zone_breach.json"
@@ -231,14 +231,16 @@ def refresh_data_prices():
     prices.update(hk_prices)
     updated = 0
 
-    # 保存全量实时价快照（供报告管道消费，确保分析用最新数据）
+    # 保存全量实时价快照到 DB（替代 live_prices.json）
     try:
-        live = {"updated_at": datetime.now().isoformat(), "prices": {}}
+        live = {}
         for code in all_codes:
             if code in prices:
                 p, c, chg = prices[code]
-                live["prices"][code] = {"price": p, "change_pct": chg}
+                live[code] = {"price": p, "change_pct": chg}
-        json.dump(live, open("/home/hmo/web-dashboard/data/live_prices.json", "w"), indent=2)
+        conn = get_conn()
+        write_live_prices(conn, live)
+        conn.close()
     except Exception:
         pass
 
@@ -663,7 +665,7 @@ def run_once(round_label=""):
 
     # === 3.5 资金流异常检测（2026-06-27 新增）===
     try:
-        cf = json.load(open("/home/hmo/web-dashboard/data/capital_flow_cache.json"))
+        cf = read_capital_flow_cache(get_conn())
         # 检查所有 active decision 中的资金流异常
         for d in active:
             code = d["code"]

scripts/capital_flow_collector.py

@@ -12,6 +12,7 @@ from urllib.request import urlopen, Request
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from threading import Semaphore
 from mo_data import read_portfolio, read_decisions, read_watchlist
+from mofin_db import get_conn, write_capital_flow_cache
 
 DATA_DIR = "/home/hmo/web-dashboard/data"
 DECISIONS_PATH = f"{DATA_DIR}/decisions.json"
@@ -175,7 +176,10 @@ def main():
         "updated_at": datetime.now().strftime("%Y-%m-%d %H:%M"),
         "stocks": all_flows,
     }
-    json.dump(cache, open(CACHE_PATH, "w"), indent=2, ensure_ascii=False)
+    # 写 DB（替代 capital_flow_cache.json）
+    conn = get_conn()
+    write_capital_flow_cache(conn, cache)
+    conn.close()
     print(f"[capital_flow] {len(all_flows)}/{len(code_list)}只更新完成")
 
 if __name__ == "__main__":

scripts/check_imports.py

@@ -0,0 +1,33 @@
+import sys, traceback
+sys.path.insert(0, '/home/hmo/MoFin')
+
+errors = []
+for mod, name in [
+    ('mo_data', 'read_portfolio'),
+    ('mo_data', 'read_decisions'),
+    ('mo_data', 'read_watchlist'),
+    ('mofin_db', 'get_conn'),
+    ('mofin_db', 'write_holdings_batch'),
+    ('mofin_db', 'write_portfolio_summary'),
+    ('mofin_db', 'write_watchlist_stock'),
+    ('mofin_db', 'write_holding_strategy'),
+    ('mo_models', 'is_hk_stock'),
+    ('mo_models', 'get_hk_rate'),
+]:
+    try:
+        m = __import__(mod, fromlist=[name])
+        getattr(m, name)
+        print(f"OK: {mod}.{name}")
+    except Exception as e:
+        print(f"FAIL: {mod}.{name} -> {e}")
+        errors.append(str(e))
+
+print(f"\n=== price_monitor.py import test ===")
+try:
+    import price_monitor
+    print("price_monitor imported OK")
+except Exception as e:
+    print(f"FAIL: {traceback.format_exc()}")
+
+if errors:
+    print(f"\n{len(errors)} import errors!")

scripts/check_prices.py

@@ -0,0 +1,15 @@
+import sqlite3
+db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
+
+# Check when portfolio was last updated
+r = db.execute("SELECT updated_at, total_assets, total_mv, cash FROM portfolio_summary WHERE id=1").fetchone()
+print(f"Portfolio last updated: {r[0]}")
+print(f"total_assets={r[1]} total_mv={r[2]} cash={r[3]}")
+
+# Check hold prices
+print("\nAll holdings:")
+for r in db.execute("SELECT code, name, price, change_pct, cost, shares FROM holdings WHERE is_active=1 ORDER BY code"):
+    mv = (r[2] or 0) * (r[5] or 0)
+    print(f"  {r[0]} {r[1]}: price={r[2]} chg={r[3]} cost={r[4]} shares={r[5]} mv={mv}")
+
+db.close()

scripts/clean_watchlist.py

@@ -1,7 +1,11 @@
 #!/usr/bin/env python3
 """Remove held stocks from watchlist"""
 
-import json, os
+import json, os, sys
+
+# 确保 MoFin 根目录在模块搜索路径中（兼容 cron 环境）
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
 from mo_data import read_portfolio, read_decisions, read_watchlist
 from mofin_db import get_conn, write_watchlist_stock, write_holding_strategy
 

scripts/diagnose_assets.py

@@ -0,0 +1,35 @@
+"""Diagnose: check HK stock costs, prices, total assets calculation"""
+import sys
+sys.path.insert(0, '/home/hmo/MoFin')
+from mo_models import calc_total_assets, calc_total_mv, is_hk_stock, to_cny, get_hk_rate
+from mo_data import read_portfolio
+import json
+
+pf = read_portfolio()
+holdings = pf.get('holdings', [])
+rate = get_hk_rate()
+
+print(f"HK_RATE: {rate}")
+print(f"total_assets (from DB): {pf.get('total_assets')}")
+print(f"total_mv (from DB): {pf.get('total_mv')}")
+print(f"cash: {pf.get('cash')}")
+print(f"frozen_cash: {pf.get('frozen_cash')}")
+print(f"position_pct: {pf.get('position_pct')}")
+
+total_mv_calc = calc_total_mv(holdings)
+total_assets_calc = calc_total_assets(pf)
+print(f"\ncalc_total_mv: {total_mv_calc}")
+print(f"calc_total_assets: {total_assets_calc}")
+
+print(f"\n=== HK stocks ===")
+for h in holdings:
+    code = h.get('code', '')
+    if is_hk_stock(str(code)):
+        cost = h.get('cost', 0) or 0
+        price = h.get('price', 0) or 0
+        shares = h.get('shares', 0) or 0
+        mv = price * shares
+        cost_calc = cost * shares
+        pnl = (price - cost) * shares if cost > 0 else 0
+        pnl_pct = (price - cost) / cost * 100 if cost > 0 else 0
+        print(f"  {code} {h.get('name')}: cost={cost} price={price} shares={shares} mv={mv} pnl={pnl:.1f} ({pnl_pct:+.1f}%)")

scripts/quick_verify.py

@@ -0,0 +1,25 @@
+"""Quick verification after JSON→DB migration"""
+import sys
+sys.path.insert(0, '/home/hmo/MoFin')
+
+from mo_data import read_portfolio, read_decisions, read_watchlist
+
+ok = 0
+err = 0
+
+for name, fn in [("portfolio", read_portfolio), ("decisions", read_decisions), ("watchlist", read_watchlist)]:
+    try:
+        r = fn()
+        if name == "portfolio":
+            n = len(r.get('holdings', []))
+        elif name == "decisions":
+            n = len(r.get('decisions', []))
+        else:
+            n = len(r.get('stocks', []))
+        print(f"  {name}: {n} records OK")
+        ok += 1
+    except Exception as e:
+        print(f"  {name}: ERROR -> {e}")
+        err += 1
+
+print(f"\n{ok}/3 passed, {err} errors")

scripts/test_api.py

@@ -0,0 +1,36 @@
+"""Test Eastmoney API response time for HK stocks"""
+import urllib.request, json, time
+
+codes = ['00700', '01888', '00981']
+UA = 'Mozilla/5.0'
+
+for code in codes:
+    url = f"https://push2.eastmoney.com/api/qt/stock/get?secid=116.{code}&fields=f43,f170&fltt=2"
+    start = time.time()
+    try:
+        req = urllib.request.Request(url, headers={"User-Agent": UA})
+        with urllib.request.urlopen(req, timeout=30) as r:
+            resp = json.loads(r.read().decode("utf-8"))
+            elapsed = time.time() - start
+            price = resp.get('data', {}).get('f43', '?')
+            print(f"{code}: {elapsed:.1f}s, price={price}, rc={resp.get('rc')}")
+    except Exception as e:
+        elapsed = time.time() - start
+        print(f"{code}: {elapsed:.1f}s, ERROR: {type(e).__name__}: {e}")
+
+# Also test Tencent fallback
+print("\nTencent fallback:")
+url = "http://qt.gtimg.cn/q=hk00700,hk01888,hk00981"
+start = time.time()
+try:
+    req = urllib.request.Request(url, headers={"User-Agent": UA})
+    with urllib.request.urlopen(req, timeout=10) as r:
+        text = r.read().decode("gbk")
+        elapsed = time.time() - start
+        print(f"Tencent: {elapsed:.1f}s, {len(text)} bytes")
+        # Parse first line
+        line = text.strip().split('\n')[0]
+        print(f"  sample: {line[:80]}...")
+except Exception as e:
+    elapsed = time.time() - start
+    print(f"Tencent: {elapsed:.1f}s, ERROR: {e}")

scripts/test_interval.py

@@ -0,0 +1,22 @@
+"""Test if steady 5s interval avoids rate limit"""
+import urllib.request, json, time
+
+UA = 'Mozilla/5.0'
+codes = ['00700', '01888', '00981']
+
+for i, code in enumerate(codes):
+    url = f"https://push2.eastmoney.com/api/qt/stock/get?secid=116.{code}&fields=f43,f170&fltt=2"
+    start = time.time()
+    try:
+        req = urllib.request.Request(url, headers={"User-Agent": UA})
+        with urllib.request.urlopen(req, timeout=5) as r:
+            resp = json.loads(r.read().decode("utf-8"))
+            elapsed = time.time() - start
+            price = resp.get('data', {}).get('f43', '?')
+            print(f"#{i+1} {code}: OK in {elapsed:.1f}s, price={price}")
+    except Exception as e:
+        elapsed = time.time() - start
+        print(f"#{i+1} {code}: FAIL in {elapsed:.1f}s — {type(e).__name__}")
+        break
+    if i < len(codes) - 1:
+        time.sleep(5)

scripts/test_ratelimit.py

@@ -0,0 +1,49 @@
+"""Test Eastmoney rate limit — find safe interval between requests"""
+import urllib.request, json, time
+
+UA = 'Mozilla/5.0'
+CODE = '00700'
+url = f"https://push2.eastmoney.com/api/qt/stock/get?secid=116.{CODE}&fields=f43,f170&fltt=2"
+
+def try_fetch():
+    start = time.time()
+    try:
+        req = urllib.request.Request(url, headers={"User-Agent": UA})
+        with urllib.request.urlopen(req, timeout=5) as r:
+            resp = json.loads(r.read().decode("utf-8"))
+            elapsed = time.time() - start
+            return True, elapsed, resp.get('data', {}).get('f43', '?'), ''
+    except Exception as e:
+        elapsed = time.time() - start
+        return False, elapsed, 0, str(e)[:50]
+
+# Test 1: single request
+ok, t, price, err = try_fetch()
+print(f"Single: {'OK' if ok else 'FAIL'} in {t:.2f}s  price={price} {err}")
+
+if ok:
+    # If it works, test minimal interval
+    for delay in [0.5, 1, 2, 3, 5]:
+        time.sleep(delay)
+        ok2, t2, p2, e2 = try_fetch()
+        print(f"After {delay:.1f}s: {'OK' if ok2 else 'FAIL'} in {t2:.2f}s  price={p2} {e2}")
+        if not ok2:
+            print(f"  -> Rate limited! Need > {delay}s between requests")
+else:
+    # Currently blocked, wait and retry
+    print("Currently blocked. Waiting 10s then retry...")
+    time.sleep(10)
+    ok, t, price, err = try_fetch()
+    print(f"After 10s: {'OK' if ok else 'FAIL'} in {t:.2f}s  price={price} {err}")
+    if ok:
+        time.sleep(2)
+        ok2, t2, p2, e2 = try_fetch()
+        print(f"After +2s: {'OK' if ok2 else 'FAIL'} in {t2:.2f}s  price={p2} {e2}")
+    else:
+        for w in [20, 30, 60]:
+            print(f"Waiting {w}s...")
+            time.sleep(w)
+            ok, t, price, err = try_fetch()
+            print(f"After {w}s: {'OK' if ok else 'FAIL'} in {t:.2f}s  price={price} {err}")
+            if ok:
+                break

scripts/verify_pnl.py

@@ -0,0 +1,38 @@
+"""Verify total assets and P&L calculation"""
+import sqlite3, sys
+sys.path.insert(0, '/home/hmo/MoFin')
+from mo_models import calc_total_assets, calc_total_mv
+
+db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
+r = db.execute("SELECT * FROM portfolio_summary WHERE id=1").fetchone()
+keys = [d[0] for d in db.execute("SELECT * FROM portfolio_summary LIMIT 0").description]
+summary = dict(zip(keys, r))
+
+print(f"total_assets (stored): {summary.get('total_assets')}")
+print(f"total_mv (stored): {summary.get('total_mv')}")
+print(f"total_pnl (stored): {summary.get('total_pnl')}")
+print(f"cash: {summary.get('cash')}")
+print(f"frozen_cash: {summary.get('frozen_cash')}")
+
+holdings = []
+for r in db.execute("SELECT code, name, cost, price, shares FROM holdings WHERE is_active=1"):
+    holdings.append({'code': r[0], 'name': r[1], 'cost': r[2] or 0, 'price': r[3] or 0, 'shares': r[4] or 0})
+
+mv = sum(h['price'] * h['shares'] for h in holdings)
+total_cost = sum(h['cost'] * h['shares'] for h in holdings)
+pnl = mv - total_cost
+ta = mv + (summary.get('cash') or 0) + (summary.get('frozen_cash') or 0)
+
+print(f"\nCalculated:")
+print(f"total_mv = {mv:.2f}")
+print(f"total_cost = {total_cost:.2f}")
+print(f"total_pnl = {pnl:.2f}")
+print(f"total_assets = {ta:.2f}")
+
+# Check for HK stocks with cost=0 (never converted)
+print("\nStocks with cost=0 or None:")
+for h in holdings:
+    if h['cost'] <= 0 and h['shares'] > 0:
+        print(f"  {h['code']} {h['name']}: cost={h['cost']} shares={h['shares']} price={h['price']}")
+
+db.close()

scripts/xiaoguo_signal_consumer.py

@@ -13,6 +13,10 @@ no_agent模式：有发现→输出，无→静默
 import json, os, sqlite3, sys, time, urllib.request
 from pathlib import Path
 from datetime import datetime
+
+# 确保 MoFin 根目录在模块搜索路径中（兼容 cron 环境）
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
 from mo_data import read_watchlist
 from mofin_db import write_watchlist_stock
 
@@ -34,8 +38,13 @@ def clean_proxy():
 def fetch_quote(code):
     """拉行情。DB 优先，腾讯 fallback"""
     # DB 优先
-    try: from mofin_db import get_price_from_db; p, chg = get_price_from_db(code); return {"name":"", "code":code, "price":p, "change_pct":chg or 0} if p else None
+    try:
-    except: pass
+        from mofin_db import get_price_from_db
+        p, chg = get_price_from_db(code)
+        if p:
+            return {"name":"", "code":code, "price":p, "change_pct":chg or 0}
+    except:
+        pass
     # Fallback: 腾讯
     try:
         prefix = "sh" if code.startswith(('60','68','51','56','50')) else "sz" if code.startswith(('00','30','15')) else "hk"