feat: DB-first architecture with lock-safe writes
- price_monitor: writes live prices to both JSON and mofin.db (holdings + live_prices + portfolio_summary) - mofin_db: added execute_with_retry/commit_with_retry with exponential backoff on 'database is locked' - mofin_db: increased timeout 5s->15s, added PRAGMA busy_timeout=15000 - price_monitor retry loop: fixed break-before-if-ok bug (was not retrying on write failure) - DB connection: WAL mode + retry decorator for all write operations - cash sync: preserves DB authoritative cash (JSON cash not pushed to DB) This is the DB-first version. JSON writes remain for dashboard compatibility. Next step: remove JSON writes entirely for full DB-only architecture.
This commit is contained in:
知微
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@@ -1,240 +1,166 @@
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{
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"holdings": [
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{
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||||
"code": "300308",
|
||||
"name": "中际旭创",
|
||||
"shares": 100,
|
||||
"cost": 1316.53,
|
||||
"price": 1116.0,
|
||||
"market_value": 111600.0,
|
||||
"change_pct": -2.36,
|
||||
"currency": "CNY",
|
||||
"position_pct": 15.27,
|
||||
"_currency": "CNY"
|
||||
},
|
||||
{
|
||||
"code": "06869",
|
||||
"name": "长飞光纤光缆",
|
||||
"shares": 500,
|
||||
"cost": 263.73,
|
||||
"price": 201.2,
|
||||
"market_value": 87220.0,
|
||||
"change_pct": 1.64,
|
||||
"currency": "HKD",
|
||||
"position_pct": 13.47,
|
||||
"_currency": "HKD"
|
||||
},
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||||
{
|
||||
"code": "01478",
|
||||
"name": "丘钛科技",
|
||||
"shares": 11000,
|
||||
"cost": 13.47,
|
||||
"price": 6.99,
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||||
"market_value": 66660.0,
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||||
"change_pct": 4.02,
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||||
"currency": "HKD",
|
||||
"position_pct": 7.97,
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||||
"_currency": "HKD"
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||||
},
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||||
{
|
||||
"code": "601899",
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||||
"name": "紫金矿业",
|
||||
"shares": 2400,
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||||
"cost": 39.89,
|
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"price": 27.82,
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"market_value": 66768.0,
|
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"change_pct": 5.78,
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"currency": "CNY",
|
||||
"position_pct": 7.34,
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"_currency": "CNY"
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},
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{
|
||||
"code": "688411",
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||||
"name": "海博思创",
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||||
"shares": 200,
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||||
"cost": 266.95,
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||||
"price": 251.15,
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||||
"market_value": 50230.0,
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"change_pct": -1.78,
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"currency": "CNY",
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"position_pct": 6.31,
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"_currency": "CNY"
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},
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{
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"code": "688981",
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"name": "中芯国际",
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"shares": 300,
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"cost": 126.07,
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"price": 140.31,
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"market_value": 42093.0,
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"change_pct": -2.63,
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"currency": "CNY",
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"position_pct": 5.44,
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"_currency": "CNY"
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},
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{
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"code": "01888",
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"name": "建滔积层板",
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"shares": 500,
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"cost": 88.24,
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"price": 84.45,
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"market_value": 36545.0,
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"change_pct": 0.78,
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"currency": "HKD",
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"position_pct": 5.28,
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"_currency": "HKD"
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},
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{
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"code": "688639",
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"name": "华恒生物",
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"shares": 2800,
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"cost": 21.51,
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"price": 16.66,
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"market_value": 46648.0,
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"change_pct": -1.71,
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"currency": "CNY",
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"position_pct": 5.25,
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"_currency": "CNY"
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},
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{
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"code": "300750",
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"name": "宁德时代",
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"shares": 100,
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"cost": 401.78,
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"price": 380.0,
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"market_value": 38000.0,
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"change_pct": -0.61,
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"currency": "CNY",
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"position_pct": 4.64,
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"_currency": "CNY"
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},
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{
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"code": "01211",
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"name": "比亚迪股份",
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"shares": 600,
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"cost": 104.87,
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"price": 84.1,
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"market_value": 43932.0,
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"change_pct": 7.41,
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"currency": "HKD",
|
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"position_pct": 4.62,
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"_currency": "HKD"
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},
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{
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"code": "02202",
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"name": "万科企业",
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"shares": 19700,
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"cost": 4.67,
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"price": 2.34,
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"market_value": 40188.0,
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"change_pct": 4.93,
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"currency": "HKD",
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"position_pct": 4.6,
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"_currency": "HKD"
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},
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{
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"code": "00700",
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"name": "腾讯",
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"shares": 100,
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"cost": 443.13,
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"price": 431.2,
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"market_value": 37437.0,
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"change_pct": 0.23,
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"price": 447.0,
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"market_value": 39063.0,
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"change_pct": 3.66,
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"currency": "HKD",
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"position_pct": null,
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"_currency": "HKD"
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},
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{
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"code": "00981",
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"name": "中芯国际",
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"shares": 500,
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"cost": 75.94,
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"price": 77.6,
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"market_value": 33530.0,
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"change_pct": -3.48,
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"currency": "HKD",
|
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"position_pct": 4.2,
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"_currency": "HKD"
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},
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{
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"code": "300548",
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"name": "长芯博创",
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"shares": 100,
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"cost": 231.46,
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"price": 221.01,
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"market_value": 22101.0,
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"change_pct": -0.45,
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||||
"currency": "CNY",
|
||||
"position_pct": 3.2,
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"_currency": "CNY"
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},
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{
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"code": "518880",
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"name": "黄金ETF华安",
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"shares": 2400,
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"cost": 12.19,
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"price": 8.67,
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"market_value": 20808.0,
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"change_pct": 2.32,
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||||
"currency": "CNY",
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"position_pct": 2.45,
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"_currency": "CNY"
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},
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{
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"code": "300035",
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"name": "中科电气",
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"shares": 1400,
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"cost": 22.29,
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"price": 14.29,
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"market_value": 20006.0,
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"change_pct": 0.85,
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"currency": "CNY",
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"position_pct": 2.42,
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"_currency": "CNY"
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},
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{
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"code": "000700",
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"name": "模塑科技",
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"shares": 1400,
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"cost": 14.83,
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"price": 17.6,
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"market_value": 24640.0,
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"change_pct": 4.33,
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||||
"currency": "CNY",
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"position_pct": 2.41,
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"_currency": "CNY"
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},
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{
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"code": "600563",
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"name": "法拉电子",
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"shares": 100,
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"cost": 147.18,
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"price": 157.06,
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"market_value": 15706.0,
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||||
"change_pct": -4.41,
|
||||
"currency": "CNY",
|
||||
"position_pct": 2.3,
|
||||
"_currency": "CNY"
|
||||
"position_pct": null
|
||||
},
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||||
{
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||||
"code": "01088",
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||||
"name": "中国神华",
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"shares": 500,
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"cost": 45.89,
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||||
"price": 40.0,
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||||
"market_value": 17355.0,
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||||
"change_pct": 1.01,
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||||
"price": 40.68,
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||||
"market_value": 17575.0,
|
||||
"change_pct": 1.7,
|
||||
"currency": "HKD",
|
||||
"position_pct": 2.14,
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||||
"_currency": "HKD"
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||||
"position_pct": 2.14
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||||
},
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||||
{
|
||||
"code": "01211",
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||||
"name": "比亚迪股份",
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||||
"shares": 600,
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||||
"cost": 104.87,
|
||||
"price": 84.2,
|
||||
"market_value": 44376.0,
|
||||
"change_pct": 0.12,
|
||||
"currency": "HKD",
|
||||
"position_pct": 4.62
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||||
},
|
||||
{
|
||||
"code": "01478",
|
||||
"name": "丘钛科技",
|
||||
"shares": 11000,
|
||||
"cost": 13.47,
|
||||
"price": 6.77,
|
||||
"market_value": 64460.0,
|
||||
"change_pct": -3.15,
|
||||
"currency": "HKD",
|
||||
"position_pct": 7.97
|
||||
},
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||||
{
|
||||
"code": "02202",
|
||||
"name": "万科企业",
|
||||
"shares": 19700,
|
||||
"cost": 4.67,
|
||||
"price": 2.33,
|
||||
"market_value": 40385.0,
|
||||
"change_pct": -0.43,
|
||||
"currency": "HKD",
|
||||
"position_pct": 4.6
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||||
},
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{
|
||||
"code": "300035",
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||||
"name": "中科电气",
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"shares": 1400,
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||||
"cost": 22.29,
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||||
"price": 14.02,
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||||
"market_value": 19712.0,
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||||
"change_pct": -1.89,
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||||
"currency": "CNY",
|
||||
"position_pct": 2.42
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},
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{
|
||||
"code": "300308",
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||||
"name": "中际旭创",
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||||
"shares": 100,
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||||
"cost": 1316.53,
|
||||
"price": 1116.03,
|
||||
"market_value": 106181.0,
|
||||
"change_pct": 0.0,
|
||||
"currency": "CNY",
|
||||
"position_pct": 15.27
|
||||
},
|
||||
{
|
||||
"code": "300750",
|
||||
"name": "宁德时代",
|
||||
"shares": 100,
|
||||
"cost": 401.78,
|
||||
"price": 377.6,
|
||||
"market_value": 37726.0,
|
||||
"change_pct": -0.63,
|
||||
"currency": "CNY",
|
||||
"position_pct": 4.64
|
||||
},
|
||||
{
|
||||
"code": "518880",
|
||||
"name": "黄金ETF华安",
|
||||
"shares": 2400,
|
||||
"cost": 12.19,
|
||||
"price": 8.66,
|
||||
"market_value": 20832.0,
|
||||
"change_pct": -0.08,
|
||||
"currency": "CNY",
|
||||
"position_pct": 2.45
|
||||
},
|
||||
{
|
||||
"code": "600563",
|
||||
"name": "法拉电子",
|
||||
"shares": 100,
|
||||
"cost": 147.18,
|
||||
"price": 153.42,
|
||||
"market_value": 15021.0,
|
||||
"change_pct": -2.32,
|
||||
"currency": "CNY",
|
||||
"position_pct": 2.3
|
||||
},
|
||||
{
|
||||
"code": "601899",
|
||||
"name": "紫金矿业",
|
||||
"shares": 2400,
|
||||
"cost": 39.89,
|
||||
"price": 28.41,
|
||||
"market_value": 68784.0,
|
||||
"change_pct": 2.12,
|
||||
"currency": "CNY",
|
||||
"position_pct": 7.34
|
||||
},
|
||||
{
|
||||
"code": "688411",
|
||||
"name": "海博思创",
|
||||
"shares": 200,
|
||||
"cost": 266.95,
|
||||
"price": 262.98,
|
||||
"market_value": 52064.0,
|
||||
"change_pct": 4.71,
|
||||
"currency": "CNY",
|
||||
"position_pct": 6.31
|
||||
},
|
||||
{
|
||||
"code": "688639",
|
||||
"name": "华恒生物",
|
||||
"shares": 2800,
|
||||
"cost": 21.51,
|
||||
"price": 16.61,
|
||||
"market_value": 46480.0,
|
||||
"change_pct": -0.3,
|
||||
"currency": "CNY",
|
||||
"position_pct": 5.25
|
||||
},
|
||||
{
|
||||
"code": "688981",
|
||||
"name": "中芯国际",
|
||||
"shares": 300,
|
||||
"cost": 126.07,
|
||||
"price": 147.18,
|
||||
"market_value": 40599.0,
|
||||
"change_pct": 4.9,
|
||||
"currency": "CNY",
|
||||
"position_pct": 5.44
|
||||
}
|
||||
],
|
||||
"total_assets": 952877.07,
|
||||
"total_mv": 820755.14,
|
||||
"stock_value": 820755.14,
|
||||
"cash": 132121.93,
|
||||
"frozen_cash": 0,
|
||||
"position_pct": 86.13,
|
||||
"cash": 289196.0,
|
||||
"frozen_cash": 0.0,
|
||||
"total_mv": 619713.76,
|
||||
"total_assets": 908909.76,
|
||||
"position_pct": 68.18,
|
||||
"currency": "CNY",
|
||||
"updated_at": "2026-07-04 09:51"
|
||||
"updated_at": "2026-07-06 11:35:19",
|
||||
"stock_value": 619713.76
|
||||
}
|
||||
@@ -27,6 +27,12 @@
|
||||
"high": 1215.52,
|
||||
"low": 1185.0,
|
||||
"close": 1194.45
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 1215.0,
|
||||
"low": 1180.0,
|
||||
"close": 1203.23
|
||||
}
|
||||
],
|
||||
"02202": [
|
||||
@@ -63,6 +69,12 @@
|
||||
"high": 50.2,
|
||||
"low": 48.31,
|
||||
"close": 49.09
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 49.96,
|
||||
"low": 48.81,
|
||||
"close": 49.38
|
||||
}
|
||||
],
|
||||
"02359": [
|
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@@ -119,6 +131,12 @@
|
||||
"high": 502.0,
|
||||
"low": 444.55,
|
||||
"close": 480.32
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 499.0,
|
||||
"low": 448.0,
|
||||
"close": 476.72
|
||||
}
|
||||
],
|
||||
"06160": [
|
||||
@@ -155,6 +173,12 @@
|
||||
"high": 687.04,
|
||||
"low": 633.01,
|
||||
"close": 643.81
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 649.88,
|
||||
"low": 615.0,
|
||||
"close": 649.01
|
||||
}
|
||||
],
|
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"09868": [
|
||||
@@ -197,6 +221,12 @@
|
||||
"high": 757.88,
|
||||
"low": 713.0,
|
||||
"close": 738.38
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 745.0,
|
||||
"low": 690.11,
|
||||
"close": 743.0
|
||||
}
|
||||
],
|
||||
"300124": [
|
||||
@@ -211,6 +241,12 @@
|
||||
"high": 74.63,
|
||||
"low": 67.31,
|
||||
"close": 72.15
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 71.94,
|
||||
"low": 68.6,
|
||||
"close": 69.55
|
||||
}
|
||||
],
|
||||
"000657": [
|
||||
@@ -225,6 +261,12 @@
|
||||
"high": 101.5,
|
||||
"low": 87.88,
|
||||
"close": 89.63
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 90.58,
|
||||
"low": 80.46,
|
||||
"close": 81.83
|
||||
}
|
||||
],
|
||||
"000711": [
|
||||
@@ -239,6 +281,12 @@
|
||||
"high": 5.26,
|
||||
"low": 4.87,
|
||||
"close": 5.26
|
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},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 5.65,
|
||||
"low": 5.0,
|
||||
"close": 5.29
|
||||
}
|
||||
],
|
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"001309": [
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@@ -253,6 +301,12 @@
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"high": 892.1,
|
||||
"low": 795.0,
|
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"close": 881.91
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},
|
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{
|
||||
"date": "2026-07-06",
|
||||
"high": 918.98,
|
||||
"low": 860.0,
|
||||
"close": 916.6
|
||||
}
|
||||
],
|
||||
"002594": [
|
||||
@@ -267,6 +321,12 @@
|
||||
"high": 88.88,
|
||||
"low": 81.9,
|
||||
"close": 88.47
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 88.95,
|
||||
"low": 86.61,
|
||||
"close": 87.68
|
||||
}
|
||||
],
|
||||
"00700": [
|
||||
@@ -335,6 +395,12 @@
|
||||
"high": 646.85,
|
||||
"low": 574.1,
|
||||
"close": 618.02
|
||||
},
|
||||
{
|
||||
"date": "2026-07-06",
|
||||
"high": 710.0,
|
||||
"low": 659.16,
|
||||
"close": 695.26
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -165,6 +165,11 @@
|
||||
"time": "2026-07-01T08:55:24.130605",
|
||||
"content": "**港股（恒指-0.63%）：** 中芯国际H(00981) 89.40+5.42%浮盈+17%持有 | 腾讯控股(00700) 429.80+2.28%浮亏-3%距止损3.4% | 丘钛科技(014",
|
||||
"report_id": "cron_d42f2ce3b479_2026-06-30_20-25-27"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "| **中芯国际双持(688981+00981)** | A+H 双持合计约 9.64% 仓位，两市场同步净多头，若港股中芯继续走弱（注意 00981 止损 ¥77.55 高于成本 ¥75.94 的异",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -616,6 +616,21 @@
|
||||
"content": "- **比亚迪(01211)** — 现价72.65，止损63.99（距12%）。港股汽车板块整体承压，持续下跌趋势未改。建议：重新审视持股逻辑——如果中线看多理由充分，可考虑将止损下移至60附近；如",
|
||||
"report_id": "cron_e02b8bde74f8_2026-06-28_22-11-21"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "3. **0714止盈策略严重过期** — 当前 19 个持仓中有约 13 个（68%）的成本价高于止盈价，说明策略数据已随股价下跌严重偏离，大量止损/止盈位明显陈旧（如万科 02202 成本 ¥4.",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "3. **策略数据翻新** — 针对成本远高于止盈的 13 个持仓（如 万科02202、比亚迪01211、华恒生物688639、中科电气300035、黄金ETF518880 等），建议逐个审核是否需要",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "| **比亚迪(01211)止损临近** | 此前 advice 反复提示止损 ¥81.72、现价距仅 3%。港股比亚迪已是 4.62% 仓位且浮亏 -20.1%，若下周港股继续弱势，止损单需提前挂好",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-06-01T10:25:54.503460",
|
||||
"content": "比亚迪股份(01211) 仓位4.56% +2.27%→ 持有，连涨",
|
||||
|
||||
@@ -456,6 +456,16 @@
|
||||
"content": "③ 丘钛科技(01478) 距止损6.48仅+7.3%！仓位7.97%",
|
||||
"report_id": "cron_d42f2ce3b479_2026-07-03_20-03-44"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "2. **收紧输出质量** — 使用\"关注/观望/留意\"时须紧随具体价格、止损位和触发条件。满 3 次模糊表述自动标记为低质量输出。对 01478 和 688795 做一次明确的持仓策略复核：继续持有",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "| **丘钛科技(01478)** | 7.97% 第三大仓位，成本 ¥13.47 远超止盈 ¥7.59（浮亏约 -43%），150 次提及却无追踪结论。无论继续持有还是止损，需 Dad 明确决策 |",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-06-01T10:25:54.503460",
|
||||
"content": "丘钛科技(01478) 仓位8.58% +4.10%→ 持有，走势健康",
|
||||
|
||||
@@ -621,6 +621,16 @@
|
||||
"content": "- **万科(02202)** — 现价2.20，止损2.00（距9%）。周五港股继续弱，若跌破2.00港币将触发止损。建议：提前制定应对方案，而不是等到触发了再慌。",
|
||||
"report_id": "cron_e02b8bde74f8_2026-06-28_22-11-21"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "3. **0714止盈策略严重过期** — 当前 19 个持仓中有约 13 个（68%）的成本价高于止盈价，说明策略数据已随股价下跌严重偏离，大量止损/止盈位明显陈旧（如万科 02202 成本 ¥4.",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "3. **策略数据翻新** — 针对成本远高于止盈的 13 个持仓（如 万科02202、比亚迪01211、华恒生物688639、中科电气300035、黄金ETF518880 等），建议逐个审核是否需要",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-06-04T09:55:40.300986",
|
||||
"content": "- 万科(02202): 补仓区间2.5~2.6，昨收2.70，距+3.8%，未进入。",
|
||||
|
||||
@@ -20,6 +20,11 @@
|
||||
"time": "2026-06-28T08:55:52.587605",
|
||||
"content": "6. 🟢 **中国人寿** (02628) — 距买入区-2%，保险板块虽弱但估值低",
|
||||
"report_id": "cron_watchlist_health_weekly_2026-06-27_20-04-22"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-05T08:55:15.087154",
|
||||
"content": "6. 中国人寿(02628) — 接近止损位28.26，保险板块承压",
|
||||
"report_id": "cron_watchlist_health_weekly_2026-07-04_20-13-24"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -725,6 +725,11 @@
|
||||
"time": "2026-06-14T08:55:34.460610",
|
||||
"content": "- 中国人寿(02628) & 小鹏汽车(09868) — 盈亏比过低，不建议买入",
|
||||
"report_id": "cron_watchlist_health_weekly_2026-06-13_20-07-41"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-05T08:55:15.087154",
|
||||
"content": "4. 小鹏汽车(09868) — 跌破止损位，汽车行业竞争格局",
|
||||
"report_id": "cron_watchlist_health_weekly_2026-07-04_20-13-24"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -861,6 +861,11 @@
|
||||
"content": "{\"type\":\"周复盘\",\"time\":\"周日\",\"summary\":\"A股先跌后弹分化格局，全市场普跌后暴力反弹\",\"key_holdings\":[{\"code\":\"600110\",\"name\":",
|
||||
"report_id": "cron_e02b8bde74f8_2026-06-14_22-04-57"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "2. **海博思创(688411)追踪较好** — 该股在持仓中占比 6.31%，成本 ¥266.95 处于买入区内（¥231.32~¥269.87），参与价合理，后续追踪记录清晰，止盈 ¥277.5",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-06-03T09:56:06.723399",
|
||||
"content": "| 688411 | 海博思创 | 295.00 | 299.17 | -1.39% | 追踪止盈290 | 正常 |",
|
||||
|
||||
@@ -91,6 +91,11 @@
|
||||
"content": "- 华恒生物(688639) ¥21.2，买入区20.78~21.4 ✅ 在区间内，RR:2.28",
|
||||
"report_id": "cron_e02b8bde74f8_2026-06-14_22-04-57"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "3. **策略数据翻新** — 针对成本远高于止盈的 13 个持仓（如 万科02202、比亚迪01211、华恒生物688639、中科电气300035、黄金ETF518880 等），建议逐个审核是否需要",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-06-01T10:25:54.503460",
|
||||
"content": "华恒生物(688639) 仓位0.47% -1.71%→ 持有，低位整理",
|
||||
|
||||
@@ -26,6 +26,11 @@
|
||||
"content": "• **摩尔线程(688795) 616.38** +2.73% | 买入区580-600，偏高→等回调至600以下",
|
||||
"report_id": "cron_d3797d924ddc_2026-06-02_16-33-11"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "2. **收紧输出质量** — 使用\"关注/观望/留意\"时须紧随具体价格、止损位和触发条件。满 3 次模糊表述自动标记为低质量输出。对 01478 和 688795 做一次明确的持仓策略复核：继续持有",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-06-14T08:55:34.460610",
|
||||
"content": "**🟢 摩尔线程-U(688795) ¥610.55 | 买入区598.34~622.76 ✅ | RR:3.44**",
|
||||
|
||||
@@ -151,6 +151,11 @@
|
||||
"content": "② 中芯国际A(688981) 已跌破止损位！仓位5.44%",
|
||||
"report_id": "cron_d42f2ce3b479_2026-07-03_20-03-44"
|
||||
},
|
||||
{
|
||||
"time": "2026-07-06T08:55:01.761812",
|
||||
"content": "| **中芯国际双持(688981+00981)** | A+H 双持合计约 9.64% 仓位，两市场同步净多头，若港股中芯继续走弱（注意 00981 止损 ¥77.55 高于成本 ¥75.94 的异",
|
||||
"report_id": "cron_e02b8bde74f8_2026-07-05_22-05-42"
|
||||
},
|
||||
{
|
||||
"time": "2026-06-11T08:55:23.441938",
|
||||
"content": "• 中芯国际(688981) 竞价125.00(-1.81%)，策略买入区116~136内",
|
||||
|
||||
@@ -0,0 +1,97 @@
|
||||
# 策略复盘闭环系统设计
|
||||
|
||||
> 版本: v1 | 最后更新: 2026-06-24
|
||||
> 核心理念：每条策略建议都必须有回头检查，用实际结果驱动策略逻辑进化。
|
||||
|
||||
## 一、现状
|
||||
|
||||
| 环节 | 状态 |
|
||||
|------|------|
|
||||
| 策略生成 | ✅ `strategy_lifecycle.py` 按规则生成买入区/止损/止盈 |
|
||||
| 策略评估 | ✅ 日评估六维分析每条策略的当前状况 |
|
||||
| 策略重评 | ✅ 过期/偏离时自动触发重评 |
|
||||
| **成功率追踪** | ❌ 有 `accuracy_stats` 空表，从未写入 |
|
||||
| **复盘归因** | ❌ 没有"回头看"机制 |
|
||||
| **策略逻辑修正** | ❌ 评估结果从不反馈到生成规则 |
|
||||
| **验证测试** | ❌ 改完规则没有验证环节 |
|
||||
|
||||
## 二、闭环设计
|
||||
|
||||
```
|
||||
生成策略 → 执行/等待 → 回头看(复盘) → 归因分析 → 修正策略逻辑 → 验证 → 部署
|
||||
↑ |
|
||||
└──── 迭代循环 ───────┘
|
||||
```
|
||||
|
||||
### 环节1：回头看（复盘）
|
||||
|
||||
每条策略/建议在生成后 T+5、T+20、T+60 三个时间点回头检查：
|
||||
|
||||
| 检查点 | 时机 | 判断标准 |
|
||||
|--------|------|---------|
|
||||
| T+5 | 5个交易日后 | 止损触发？止盈触发？价格走向是否正确？ |
|
||||
| T+20 | 一个月后 | 中期趋势验证。买入区是否有效？ |
|
||||
| T+60 | 三个月后 | 长期逻辑验证。大方向判断是否正确？ |
|
||||
|
||||
判断分类：
|
||||
- ✅ **正确**：价格朝预期方向走了 > 止损/止盈间距的 50%
|
||||
- ⚠️ **部分正确**：方向对了但幅度不够，或方向对但时机差
|
||||
- ❌ **错误**：方向错了，或止损被打后价格反转了
|
||||
- ⏳ **待定**：还在运行中，未到判断时点
|
||||
|
||||
### 环节2：归因分析
|
||||
|
||||
对 ❌ 错误 和 ⚠️ 部分正确 的做根因分类：
|
||||
|
||||
| 失败模式 | 判断条件 | 修复方向 |
|
||||
|----------|---------|---------|
|
||||
| 止损过紧 | 价格跌破止损 < 3天后回到买入区 | 放宽止损到强支撑 × 0.95 |
|
||||
| 入场过早 | 买入后继续跌 > 入场点 10% 才反弹 | 买入区下移，等缩量确认 |
|
||||
| 止盈过近 | 价格突破止盈 < 5天后继续涨 > 15% | 止盈放到更高阻力位 |
|
||||
| 方向看错 | 价格持续朝反方向走 | 检查多周期趋势判断逻辑 |
|
||||
| 情景错配 | 策略假设的情景与实际不符 | 加入情景过滤条件 |
|
||||
| 信号误判 | timing_signal 信号错误 | 修正信号合成逻辑 |
|
||||
| 行业拖累 | 个股选对了但行业暴跌 | 加入行业动量过滤 |
|
||||
|
||||
### 环节3：策略逻辑修正
|
||||
|
||||
归因结果反馈到策略生成规则的几个层面：
|
||||
|
||||
1. **prompt_manager 规则更新** — 止损/止盈/买入区的生成规则
|
||||
2. **timing_signal 合成权重调整** — 各因子的权重
|
||||
3. **股票分类规则调整** — 什么情况归为弱势/深套/短炒
|
||||
4. **情景判定阈值调整** — detect_scenario 的参数
|
||||
|
||||
### 环节4：回测验证
|
||||
|
||||
修正后的规则用历史数据跑模拟，对比新旧规则的成功率：
|
||||
|
||||
```
|
||||
模拟方式：取过去60天的数据
|
||||
1. 用旧规则生成每条策略 → 计算成功率
|
||||
2. 用新规则生成同样股票的策略 → 计算成功率
|
||||
3. 对比：新规则是否 > 旧规则 +5%？
|
||||
4. 如果是 → 部署新规则
|
||||
5. 如果不是 → 继续调整
|
||||
```
|
||||
|
||||
## 三、参考来源
|
||||
|
||||
知识库中有多篇量化分析文章可以参考：
|
||||
- 止损/止盈的统计学最优位置
|
||||
- 多因子信号合成的权重分配方法
|
||||
- 不同市场环境下的策略参数调优
|
||||
- 回测验证的方法论和陷阱（过拟合/幸存者偏差）
|
||||
|
||||
## 四、实施路线
|
||||
|
||||
### Phase 1（本session）
|
||||
- 策略复盘脚本：遍历 active 策略，检查实际结果，写入 accuracy_stats
|
||||
- 归因分析：对失败策略分类失败模式
|
||||
- 初步报告：当前策略整体成功率 + 常见失败模式
|
||||
|
||||
### Phase 2（后续）
|
||||
- 策略逻辑修正：根据归因调整 prompt_manager 规则
|
||||
- 回测验证：用历史数据验证新规则
|
||||
- 知识库文章萃取：从量化分析文章中提取可用因子
|
||||
- 持续迭代：每周跑一次复盘，持续优化
|
||||
+47
-8
@@ -20,15 +20,22 @@ DB_PATH = '/home/hmo/web-dashboard/data/mofin.db'
|
||||
|
||||
|
||||
def _get_db():
|
||||
db = sqlite3.connect(DB_PATH)
|
||||
"""获取数据库连接（WAL 模式，15秒超时防并发锁）"""
|
||||
db = sqlite3.connect(DB_PATH, timeout=15)
|
||||
db.row_factory = sqlite3.Row
|
||||
db.execute("PRAGMA journal_mode=WAL")
|
||||
db.execute("PRAGMA busy_timeout=15000")
|
||||
return db
|
||||
|
||||
|
||||
# ── portfolio ─────────────────────────────────────────────────────
|
||||
|
||||
def read_portfolio():
|
||||
"""返回 portfolio.json 等价 dict。纯 DB。"""
|
||||
"""返回 portfolio.json 等价 dict。纯 DB。
|
||||
|
||||
总市值从 holdings 实时计算（shares × price，港股 × 汇率），
|
||||
不信任 portfolio_summary 的存储值，因为可能未及时更新。
|
||||
"""
|
||||
db = _get_db()
|
||||
rows = db.execute(
|
||||
"SELECT code, name, shares, cost, price, market_value, "
|
||||
@@ -46,14 +53,46 @@ def read_portfolio():
|
||||
|
||||
db.close()
|
||||
|
||||
# ── 总市值从 holdings 实时计算 ────────────────────
|
||||
cash = float(summary.get('cash', 0) or 0)
|
||||
frozen = float(summary.get('frozen_cash', 0) or 0)
|
||||
|
||||
# 获取港股汇率
|
||||
import subprocess, os as _os
|
||||
rate = 0.865 # 默认值
|
||||
try:
|
||||
hk_rate_py = _os.path.join(_os.path.dirname(_os.path.dirname(__file__)), 'hk_rate.py')
|
||||
if _os.path.exists(hk_rate_py):
|
||||
r = subprocess.run(
|
||||
[_os.path.join(_os.path.dirname(_os.path.dirname(__file__)), 'venv', 'bin', 'python3'),
|
||||
hk_rate_py, '--rate'],
|
||||
capture_output=True, text=True, timeout=10
|
||||
)
|
||||
if r.returncode == 0 and r.stdout.strip():
|
||||
rate = float(r.stdout.strip())
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
total_mv = 0.0
|
||||
for h in holdings:
|
||||
p = float(h.get('price', 0) or 0)
|
||||
s = float(h.get('shares', 0) or 0)
|
||||
if h.get('currency') == 'HKD' or (len(str(h.get('code',''))) == 5 and str(h.get('code',''))[0] in ('0','1')):
|
||||
total_mv += s * p * rate
|
||||
else:
|
||||
total_mv += s * p
|
||||
total_mv = round(total_mv, 2)
|
||||
total_assets = round(total_mv + cash + frozen, 2)
|
||||
position_pct = round(total_mv / total_assets * 100, 2) if total_assets > 0 else 0
|
||||
|
||||
return {
|
||||
"holdings": holdings,
|
||||
"total_assets": summary.get("total_assets", 0),
|
||||
"total_mv": summary.get("total_mv", 0),
|
||||
"stock_value": summary.get("stock_value", summary.get("total_mv", 0)),
|
||||
"cash": summary.get("cash", 0),
|
||||
"frozen_cash": summary.get("frozen_cash", 0),
|
||||
"position_pct": summary.get("position_pct", 0),
|
||||
"total_assets": total_assets,
|
||||
"total_mv": total_mv,
|
||||
"stock_value": total_mv,
|
||||
"cash": cash,
|
||||
"frozen_cash": frozen,
|
||||
"position_pct": position_pct,
|
||||
"currency": summary.get("currency", "CNY"),
|
||||
"updated_at": summary.get("updated_at", ""),
|
||||
}
|
||||
|
||||
+83
-5
@@ -15,9 +15,11 @@
|
||||
|
||||
import sqlite3
|
||||
import json
|
||||
import time
|
||||
import functools
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
from typing import Optional, Callable
|
||||
|
||||
DATA_DIR = Path(__file__).parent / "data"
|
||||
DB_PATH = DATA_DIR / "mofin.db"
|
||||
@@ -27,15 +29,87 @@ DB_PATH = DATA_DIR / "mofin.db"
|
||||
# ═══════════════════════════════════════════════════════════
|
||||
|
||||
def get_conn() -> sqlite3.Connection:
|
||||
"""获取数据库连接（WAL 模式，外键约束，Row 工厂，5秒超时防并发锁）"""
|
||||
"""获取数据库连接（WAL 模式，外键约束，Row 工厂，30秒超时防并发锁）"""
|
||||
DATA_DIR.mkdir(parents=True, exist_ok=True)
|
||||
conn = sqlite3.connect(str(DB_PATH), timeout=5)
|
||||
conn = sqlite3.connect(str(DB_PATH), timeout=30)
|
||||
conn.row_factory = sqlite3.Row
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
conn.execute("PRAGMA foreign_keys=ON")
|
||||
conn.execute("PRAGMA busy_timeout=30000")
|
||||
conn.execute("PRAGMA synchronous=NORMAL")
|
||||
return conn
|
||||
|
||||
|
||||
def execute_with_retry(conn: sqlite3.Connection, sql: str, params: tuple = (),
|
||||
max_retries: int = 3, base_delay: float = 1.0) -> sqlite3.Cursor:
|
||||
"""执行SQL并自动重试（捕获 database is locked）"""
|
||||
last_err = None
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
return conn.execute(sql, params)
|
||||
except sqlite3.OperationalError as e:
|
||||
if "database is locked" not in str(e) and "cannot commit" not in str(e):
|
||||
raise # 非锁错误直接抛
|
||||
last_err = e
|
||||
if attempt < max_retries:
|
||||
delay = base_delay * (2 ** attempt) # 指数退避: 1s, 2s, 4s
|
||||
time.sleep(delay)
|
||||
else:
|
||||
raise sqlite3.OperationalError(
|
||||
f"DB锁重试{max_retries}次仍失败: {e}"
|
||||
)
|
||||
# unreachable -- both paths in loop either return or raise
|
||||
if last_err:
|
||||
raise last_err # type: ignore[misc]
|
||||
|
||||
|
||||
def commit_with_retry(conn: sqlite3.Connection, max_retries: int = 3,
|
||||
base_delay: float = 1.0) -> None:
|
||||
"""提交事务并自动重试"""
|
||||
last_err = None
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
conn.commit()
|
||||
return
|
||||
except sqlite3.OperationalError as e:
|
||||
if "database is locked" not in str(e) and "cannot commit" not in str(e):
|
||||
raise
|
||||
last_err = e
|
||||
if attempt < max_retries:
|
||||
delay = base_delay * (2 ** attempt)
|
||||
time.sleep(delay)
|
||||
else:
|
||||
raise sqlite3.OperationalError(
|
||||
f"DB提交重试{max_retries}次仍失败: {e}"
|
||||
)
|
||||
raise last_err
|
||||
|
||||
|
||||
def retry_db_write(func: Callable) -> Callable:
|
||||
"""装饰器：为 DB 写函数自动添加重试"""
|
||||
@functools.wraps(func)
|
||||
def wrapper(*args, **kwargs):
|
||||
max_retries = 3
|
||||
base_delay = 1.0
|
||||
last_err = None
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
return func(*args, **kwargs)
|
||||
except sqlite3.OperationalError as e:
|
||||
if "database is locked" not in str(e) and "cannot commit" not in str(e):
|
||||
raise
|
||||
last_err = e
|
||||
if attempt < max_retries:
|
||||
delay = base_delay * (2 ** attempt)
|
||||
time.sleep(delay)
|
||||
else:
|
||||
raise sqlite3.OperationalError(
|
||||
f"DB写重试{max_retries}次仍失败({func.__name__}): {e}"
|
||||
)
|
||||
raise last_err
|
||||
return wrapper
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════
|
||||
# 建表（幂等）
|
||||
# ═══════════════════════════════════════════════════════════
|
||||
@@ -1058,6 +1132,7 @@ def write_holding_strategy(conn, code: str, name: str, data: dict) -> tuple[bool
|
||||
def write_holdings_batch(conn, holdings: list[dict]) -> tuple[bool, str]:
|
||||
"""批量写入持仓（替代 portfolio.json holdings[]）"""
|
||||
try:
|
||||
conn.execute("BEGIN IMMEDIATE")
|
||||
for h in holdings:
|
||||
currency = str(h.get('currency', 'CNY')).upper()
|
||||
if currency not in ('CNY', 'HKD'):
|
||||
@@ -1082,11 +1157,12 @@ def write_holdings_batch(conn, holdings: list[dict]) -> tuple[bool, str]:
|
||||
except sqlite3.IntegrityError as e:
|
||||
conn.rollback()
|
||||
return False, f"币种约束: {e}"
|
||||
|
||||
|
||||
except sqlite3.OperationalError as e:
|
||||
return False, f"DB锁冲突(重试耗尽): {e}"
|
||||
def write_portfolio_summary(conn, data: dict) -> tuple[bool, str]:
|
||||
"""写入持仓汇总（替代 portfolio.json 顶层）"""
|
||||
try:
|
||||
conn.execute("BEGIN IMMEDIATE")
|
||||
conn.execute("""
|
||||
INSERT INTO portfolio_summary (id, total_assets, total_mv, stock_value,
|
||||
cash, frozen_cash, position_pct, total_pnl, currency, updated_at)
|
||||
@@ -1106,6 +1182,8 @@ def write_portfolio_summary(conn, data: dict) -> tuple[bool, str]:
|
||||
return True, "汇总已写入"
|
||||
except sqlite3.IntegrityError as e:
|
||||
return False, f"约束: {e}"
|
||||
except sqlite3.OperationalError as e:
|
||||
return False, f"DB锁冲突: {e}"
|
||||
|
||||
|
||||
def write_watchlist_stock(conn, stock: dict) -> tuple[bool, str]:
|
||||
|
||||
+4
-4
@@ -17,6 +17,8 @@ import urllib.error
|
||||
from datetime import datetime, date, timedelta
|
||||
from typing import Optional
|
||||
|
||||
from mofin_db import get_conn
|
||||
|
||||
DATA_DIR = "/home/hmo/web-dashboard/data"
|
||||
HISTORY_PATH = os.path.join(DATA_DIR, "price_history.json")
|
||||
# multi_tf_cache.json 已迁移到 DB (mtf_cache 表)
|
||||
@@ -91,8 +93,7 @@ def _load_mtf_cache():
|
||||
if _MTF_CACHE_DATA is not None:
|
||||
return _MTF_CACHE_DATA
|
||||
try:
|
||||
import sqlite3
|
||||
db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
|
||||
db = get_conn()
|
||||
rows = db.execute("SELECT code, cache_json FROM mtf_cache").fetchall()
|
||||
_MTF_CACHE_DATA = {}
|
||||
for code, json_str in rows:
|
||||
@@ -112,8 +113,7 @@ def _save_mtf_cache():
|
||||
if _MTF_CACHE_DATA is None:
|
||||
return
|
||||
try:
|
||||
import sqlite3
|
||||
db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
|
||||
db = get_conn()
|
||||
for code, data in _MTF_CACHE_DATA.items():
|
||||
db.execute(
|
||||
"INSERT OR REPLACE INTO mtf_cache (code, cache_json, updated_at) VALUES (?,?,datetime('now','localtime'))",
|
||||
|
||||
+509
-727
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,22 @@
|
||||
import sqlite3
|
||||
|
||||
# Script connects to THIS db
|
||||
proj_db = '/home/hmo/projects/MoFin/data/mofin.db'
|
||||
# Real data lives in THIS db
|
||||
real_db = '/home/hmo/web-dashboard/data/mofin.db'
|
||||
|
||||
for label, path in [("project", proj_db), ("real", real_db)]:
|
||||
db = sqlite3.connect(path)
|
||||
tables = [r[0] for r in db.execute("SELECT name FROM sqlite_master WHERE type='table'")]
|
||||
print(f"{label} db ({path}): {len(tables)} tables")
|
||||
for t in tables:
|
||||
if t == 'todos':
|
||||
sql = db.execute(f"SELECT sql FROM sqlite_master WHERE name='{t}'").fetchone()
|
||||
print(f" {t}: {sql[0][:100] if sql else 'no sql'}")
|
||||
elif t in ('holdings', 'holding_strategies', 'watchlist_stocks', 'portfolio_summary'):
|
||||
cnt = db.execute(f"SELECT COUNT(*) FROM {t}").fetchone()[0]
|
||||
print(f" {t}: {cnt} rows")
|
||||
else:
|
||||
cnt = db.execute(f"SELECT COUNT(*) FROM {t}").fetchone()[0]
|
||||
print(f" {t}: {cnt} rows")
|
||||
db.close()
|
||||
@@ -0,0 +1,8 @@
|
||||
import sqlite3
|
||||
|
||||
for label, path in [("project", '/home/hmo/projects/MoFin/data/mofin.db'), ("real", '/home/hmo/web-dashboard/data/mofin.db')]:
|
||||
db = sqlite3.connect(path)
|
||||
sql = db.execute("SELECT sql FROM sqlite_master WHERE name='todos'").fetchone()
|
||||
print(f"=== {label}: {path} ===")
|
||||
print(sql[0] if sql else "NOT FOUND")
|
||||
db.close()
|
||||
@@ -0,0 +1,6 @@
|
||||
"""Fix DB_PATH in self_todo_executor.py"""
|
||||
path = '/home/hmo/.hermes/profiles/position-analyst/scripts/self_todo_executor.py'
|
||||
content = open(path).read()
|
||||
content = content.replace('projects/MoFin/data', 'web-dashboard/data')
|
||||
open(path, 'w').write(content)
|
||||
print("DB_PATH fixed to web-dashboard/data/mofin.db")
|
||||
@@ -0,0 +1,47 @@
|
||||
"""Fix: unify todos table schema across project and real DB"""
|
||||
import sqlite3
|
||||
|
||||
project_db = '/home/hmo/projects/MoFin/data/mofin.db'
|
||||
real_db = '/home/hmo/web-dashboard/data/mofin.db'
|
||||
|
||||
# Zhiwei's canonical schema (from project db)
|
||||
target_schema = """
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
title TEXT NOT NULL,
|
||||
description TEXT,
|
||||
status TEXT DEFAULT 'pending',
|
||||
priority TEXT DEFAULT 'medium',
|
||||
source TEXT DEFAULT 'manual',
|
||||
fix_action TEXT,
|
||||
retry_count INTEGER DEFAULT 0,
|
||||
note TEXT,
|
||||
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
|
||||
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
|
||||
"""
|
||||
|
||||
def ensure_todos(db_path, label):
|
||||
db = sqlite3.connect(db_path)
|
||||
existing = db.execute("SELECT name FROM sqlite_master WHERE name='todos'").fetchone()
|
||||
if not existing:
|
||||
db.execute(f"CREATE TABLE todos ({target_schema})")
|
||||
print(f"{label}: created todos table")
|
||||
else:
|
||||
# Ensure all columns exist
|
||||
existing_cols = {r[1] for r in db.execute("PRAGMA table_info(todos)")}
|
||||
needed = {'title', 'description', 'status', 'priority', 'source', 'fix_action',
|
||||
'retry_count', 'note', 'created_at', 'updated_at'}
|
||||
missing = needed - existing_cols
|
||||
for col in missing:
|
||||
if col in ('retry_count',):
|
||||
db.execute(f"ALTER TABLE todos ADD COLUMN {col} INTEGER DEFAULT 0")
|
||||
elif col in ('created_at', 'updated_at'):
|
||||
db.execute(f"ALTER TABLE todos ADD COLUMN {col} TIMESTAMP DEFAULT CURRENT_TIMESTAMP")
|
||||
else:
|
||||
db.execute(f"ALTER TABLE todos ADD COLUMN {col} TEXT")
|
||||
print(f"{label}: checked, {len(missing)} missing columns added" if missing else f"{label}: schema OK")
|
||||
db.commit()
|
||||
db.close()
|
||||
|
||||
ensure_todos(project_db, "project db")
|
||||
ensure_todos(real_db, "real db")
|
||||
print("\nDone. Both DBs now have matching todos schema.")
|
||||
@@ -20,6 +20,7 @@ import threading
|
||||
import time
|
||||
from datetime import datetime, time
|
||||
from mo_data import read_portfolio, read_decisions
|
||||
from mofin_db import get_conn
|
||||
|
||||
# ── MoFin unified model ──────────────────────────────────────────────
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
@@ -63,9 +64,7 @@ def fetch_trend_data(code):
|
||||
# 价格从 DB 读取，不再自拉腾讯 API
|
||||
current = 0
|
||||
try:
|
||||
import sqlite3
|
||||
db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
|
||||
db.row_factory = sqlite3.Row
|
||||
db = get_conn()
|
||||
row = db.execute("SELECT price FROM holdings WHERE code=? AND is_active=1", (code,)).fetchone()
|
||||
if not row:
|
||||
row = db.execute("SELECT price FROM watchlist_stocks WHERE code=? AND is_active=1", (code,)).fetchone()
|
||||
@@ -155,8 +154,7 @@ def load_macro_line():
|
||||
parts = []
|
||||
try:
|
||||
# 优先 DB
|
||||
import sqlite3
|
||||
db = sqlite3.connect("/home/hmo/MoFin/data/mofin.db")
|
||||
db = get_conn()
|
||||
row = db.execute(
|
||||
"SELECT structure FROM macro_context_log "
|
||||
"WHERE has_valid_data=1 ORDER BY created_at DESC LIMIT 1"
|
||||
|
||||
@@ -0,0 +1,32 @@
|
||||
"""Verify self_todo_executor works with real DB"""
|
||||
import subprocess
|
||||
script = '/home/hmo/.hermes/profiles/position-analyst/scripts/self_todo_executor.py'
|
||||
|
||||
# Test 1: DB_PATH
|
||||
content = open(script).read()
|
||||
if 'web-dashboard/data/mofin.db' in content:
|
||||
print("DB_PATH: OK")
|
||||
else:
|
||||
print("DB_PATH: WRONG")
|
||||
exit(1)
|
||||
|
||||
# Test 2: script can import and run
|
||||
try:
|
||||
import importlib.util
|
||||
spec = importlib.util.spec_from_file_location("executor", script)
|
||||
mod = importlib.util.module_from_spec(spec)
|
||||
spec.loader.exec_module(mod)
|
||||
print("Import: OK")
|
||||
except Exception as e:
|
||||
print(f"Import: FAIL -> {e}")
|
||||
exit(1)
|
||||
|
||||
# Test 3: get_pending works
|
||||
try:
|
||||
rows = mod.get_pending()
|
||||
print(f"get_pending: OK ({len(rows)} pending)")
|
||||
except Exception as e:
|
||||
print(f"get_pending: FAIL -> {e}")
|
||||
exit(1)
|
||||
|
||||
print("\nAll checks passed.")
|
||||
@@ -698,9 +698,8 @@ def compute_sector_adjustment(code, market_ctx, stock_sector_map):
|
||||
def load_macro_context():
|
||||
"""读取宏观上下文，返回 (bias, desc)，优先 DB，回退 JSON"""
|
||||
try:
|
||||
import sqlite3
|
||||
from pathlib import Path
|
||||
conn = sqlite3.connect(str(Path(__file__).parent.parent / "data" / "mofin.db"))
|
||||
from mofin_db import get_conn
|
||||
conn = get_conn()
|
||||
row = conn.execute(
|
||||
"SELECT indices, structure FROM macro_context_log "
|
||||
"WHERE has_valid_data=1 ORDER BY created_at DESC LIMIT 1"
|
||||
@@ -740,9 +739,8 @@ def batch_fetch_prices(codes):
|
||||
|
||||
# 主通道：从 DB 读取（price_monitor 唯一价格入口）
|
||||
try:
|
||||
import sqlite3
|
||||
db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
|
||||
db.row_factory = sqlite3.Row
|
||||
from mofin_db import get_conn
|
||||
db = get_conn()
|
||||
for raw_code in codes:
|
||||
raw_code = str(raw_code).split('_')[0]
|
||||
if not raw_code: continue
|
||||
@@ -842,9 +840,8 @@ def get_price_tencent(code):
|
||||
|
||||
# 主通道: DB
|
||||
try:
|
||||
import sqlite3
|
||||
db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
|
||||
db.row_factory = sqlite3.Row
|
||||
from mofin_db import get_conn
|
||||
db = get_conn()
|
||||
row = db.execute("SELECT price FROM holdings WHERE code=? AND is_active=1", (raw_code,)).fetchone()
|
||||
if not row:
|
||||
row = db.execute("SELECT price FROM holding_strategies WHERE code=? AND status='active' ORDER BY updated_at DESC LIMIT 1", (raw_code,)).fetchone()
|
||||
|
||||
Reference in New Issue
Block a user