修复: 建表脚本/redis RESP3/参数缓存穿透/回放认领时间守卫
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@ -10,8 +10,8 @@
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| # | 数据项 | 需要的字段 | 期望更新时延 | 用途 | 答复 |
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|---|---|---|---|---|---|
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| A1 | 持仓快照 `trading_position` | 股票代码（点式）、持仓数量、**可用数量（T+1 可卖）**、成本价（如有）、冻结数量（如有） | 盘中 ≤ 5 分钟 | 账本对账基准。当前 PMS 只确认过 `stock_code` 列可用，**请提供该表完整字段定义（DDL）**，尤其确认是否已有"可用数量"列——若无，PMS 自行按 T+1 规则推算 | |
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| A2 | 委托与成交 `trading_order` | 委托号、股票代码、方向、委托价、委托量、状态（**完整状态枚举文档**）、成交量、成交均价、委托/成交时间、来源标识 | 状态变更后 ≤ 1 分钟 | 成交回放入账（批次/成本）、指令执行确认。**请提供完整 DDL 与状态流转说明**（现掌握的 submitted/filled/completed/pending/failed 为推断口径，需正式确认） | |
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| A1 | 持仓快照 `trading_position` | 股票代码（点式）、持仓数量、**可用数量（T+1 可卖）**、成本价（如有）、冻结数量（如有） | 盘中 ≤ 5 分钟 | 账本对账基准。当前 PMS 只确认过 `stock_code` 列可用，**请提供该表完整字段定义（DDL）**，尤其确认是否已有"可用数量"列——若无，PMS 自行按 T+1 规则推算 | **PMS 侧实机探明（2026-07-27，待下游确认语义）**：该表 14 列，含 `stock_code / stock_name / total_quantity / available_quantity / frozen_quantity / cost_price / market_price / market_value / profit_loss`。**可用数量列已存在**（`available_quantity`），本项数据需求实质已满足，PMS 已按此列对接。仍请确认：①`available_quantity` 是否即 T+1 可卖口径 ②更新时延 ③`stock_code` 格式（点式/前缀式） |
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| A2 | 委托与成交 `trading_order` | 委托号、股票代码、方向、委托价、委托量、状态（**完整状态枚举文档**）、成交量、成交均价、委托/成交时间、来源标识 | 状态变更后 ≤ 1 分钟 | 成交回放入账（批次/成本）、指令执行确认。**请提供完整 DDL 与状态流转说明**（现掌握的 submitted/filled/completed/pending/failed 为推断口径，需正式确认） | **PMS 侧实机探明**：该表 20 列，已见 `order_id / strategy_id / stock_code / stock_name / order_side / order_quantity / order_price / target_price / order_status` 等。**仍缺两项，是本清单里最卡 PMS 的**：①状态枚举的正式定义 ②**成交来源标识**（哪条委托对应 PMS 的哪条指令）。在来源标识到位前，PMS 只能按「同股同向 + 下发早于成交 + FIFO」贪心认领，认领不上即判外部成交并告警——人工与 PMS 同时下单时会误判 |
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| A3 | 账户资金快照（**新增需求**） | 总资产、可用资金、冻结资金、当日卖出可用资金（T+0 回笼） | 盘中 ≤ 5 分钟；日终必须 | 总规模校准与买入前资金校验。形式不限：新表 / 现有表 / HTTP 接口均可，请给出可行方案 | |
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| A4 | 成交回报明细（可选） | 若 A2 已含逐笔或聚合成交（成交量/均价），本项可免；否则请提供逐笔成交表 | 同 A2 | 部分成交场景的精确入账 | |
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| A5 | 上游买入计划 `trading_buy_plan` | PMS 将作为该表的承接方（替代原决策系统 ENTRY_GATE 的角色）。请确认：①下游当前是否仍轮询 `is_active=6` 自动挂单？②切换后是否可以**停止**该轮询（统一走 B1 通道），或保留作为过渡（方案 X） | — | 旧通道处置（见 C2） | |
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@ -67,6 +67,6 @@ CREATE TABLE pms_order_request (
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| # | 文档 | 说明 | 答复 |
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|---|---|---|---|
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| D1 | `trading_position` / `trading_order` / `trading_buy_plan` 完整 DDL | 含索引与状态枚举正式定义 | |
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| D1 | `trading_position` / `trading_order` / `trading_buy_plan` 完整 DDL | 含索引与状态枚举正式定义 | **列名已由 PMS 实机探明**（`docker compose run --rm pms-web python scripts/check_db.py` 的 [3] 段会打印三表完整列定义，可直接贴进本表）：trading_position 14 列 / trading_order 20 列 / trading_buy_plan 25 列。**仍需下游正式提供的是语义而非列名**：状态枚举取值与流转、各数量列口径、索引 |
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| D2 | 下游执行行为说明 | 委托拆单逻辑（如有）、涨跌停处理、集合竞价时段行为 | |
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| D3 | 现有信号消费点清单 | 下游当前消费决策系统信号的全部位置（用于 C2 停用核对，防遗漏） | |
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@ -42,6 +42,7 @@ scripts/
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test_core_units.py 仓位与安全垫核心逻辑 14 例
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test_batch2_units.py 命令 / 方案 / 回放对账 纯逻辑 35 例
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test_wiring.py 装配自检: 服务层→核心→落表 全链路 (内存桩) 18 例
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init_db.py 建表 (应用 ddl_pms_v1.sql, 幂等, 默认演练)
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check_db.py 实机连通性与表结构自检 (需真实 .env)
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```
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@ -63,7 +64,9 @@ docker compose build # 默认走清华 PyPI 镜像; 可 --
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# 构建验证 (不连库, 秒级): 应输出 ALL SUITES PASS
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docker compose run --rm pms-web python scripts/run_tests.py
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# 实机自检 (连库, 需 .env): 三库连通 + pms_* 十表 + 下游表结构 + 行情 Redis
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# 建表 (幂等; 不加 --yes 只演练打印)
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docker compose run --rm pms-web python scripts/init_db.py --yes
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# 实机自检 (连库, 需 .env): 库连通 + pms_* 十表 + 下游表完整列定义 + 行情 Redis
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docker compose run --rm pms-web python scripts/check_db.py
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docker compose up -d # 管理页面
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@ -79,6 +82,8 @@ git pull && docker compose build && docker compose up -d
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基础镜像 `python:3.11-slim` 拉取慢时，先给服务器 Docker 配置 registry 镜像加速。日志落 `./logs`（已挂载卷）；容器时区 Asia/Shanghai。管理页面的前端资源（Vue3 / ElementPlus / axios）走 unpkg CDN，浏览器需能访问外网；若内网隔离，把页面头部三行 `<script>/<link>` 换成本地文件即可（页面本身无构建步骤）。
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**依赖版本坑**：`redis` 必须锁在 5.x。redis-py 6.x 默认按 RESP3 握手（先发 `HELLO 3`），而 208/150 两台 Redis 是 6.0 以前的版本，会回 `unknown command HELLO`，行情与 Celery 总线一起断。`requirements.txt` 已锁版本，代码侧另有 `protocol=2` 双保险；升级依赖时别把这条放开。
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## 调度总表（`--profile sched` 生效，设计 §10）
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| 调度 | 时间 | 任务 | 本批状态 |
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@ -4,23 +4,26 @@
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==============================================================================
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这三张表**归下游系统维护**, PMS 只读 (设计 §9)。
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列名不确定性 (重要):
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QMT_INTERFACE_REQUIREMENTS A1/A2/D1 仍在协商 —— 目前只确认 trading_position.stock_code
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与 trading_order 的 order_* 系列列。因此本模块**不硬编码持仓数量列名**, 而是先取一行
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探测列名 (候选列表按常见命名排优先级), 并把探测结果回传给上层, 在页面与日报显式展示
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「本次对账用的是哪一列」。协商答复到位后, 把 PMS_DS_QTY_COL 参数写死即可停用探测。
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列名口径 (2026-07-27 实机 SHOW COLUMNS 确认, 见 check_db.py 输出):
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trading_position: id, stock_code, stock_name, total_quantity, available_quantity,
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frozen_quantity, cost_price, market_price, market_value, profit_loss, ...
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→ **可用数量列 available_quantity 下游已提供**, QMT 需求清单 A1 的核心疑问就此落地,
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PMS 无需自行按 T+1 推算下游可卖量 (账本侧仍按 T+1 自行维护, 对账时以下游为准)。
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探测机制保留: 候选表把已确认列名排在首位, 万一下游改名或换表也能自动兜住, 探测结果经
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「运维 → 导出下游表结构」可见, 也是回填 D1 的现成材料。
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"""
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from __future__ import annotations
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from app.db.session import fetch_all, fetch_one
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# 数量/可用量列名候选 (探测顺序即优先级)
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QTY_CANDIDATES = ["current_qty", "total_qty", "position_qty", "hold_qty", "stock_qty",
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"volume", "quantity", "qty", "position_volume", "hold_volume"]
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AVAIL_CANDIDATES = ["available_qty", "avail_qty", "can_use_volume", "available_volume",
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"sellable_qty", "enable_amount", "can_sell_qty"]
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# 数量/可用量列名候选 (探测顺序即优先级; 首项为实机确认的真实列名)
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QTY_CANDIDATES = ["total_quantity", "current_qty", "total_qty", "position_qty", "hold_qty",
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"stock_qty", "volume", "quantity", "qty", "position_volume", "hold_volume"]
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AVAIL_CANDIDATES = ["available_quantity", "available_qty", "avail_qty", "can_use_volume",
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"available_volume", "sellable_qty", "enable_amount", "can_sell_qty"]
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COST_CANDIDATES = ["cost_price", "avg_cost", "open_price", "position_cost", "cost"]
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FROZEN_CANDIDATES = ["frozen_qty", "frozen_volume", "freeze_qty"]
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FROZEN_CANDIDATES = ["frozen_quantity", "frozen_qty", "frozen_volume", "freeze_qty"]
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PRICE_CANDIDATES = ["market_price", "last_price", "current_price", "price"]
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FILLED_STATUSES = ("completed", "filled")
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@ -76,6 +79,7 @@ def fetch_positions() -> dict:
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avail_col = _pick(keys, AVAIL_CANDIDATES)
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cost_col = _pick(keys, COST_CANDIDATES)
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frozen_col = _pick(keys, FROZEN_CANDIDATES)
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price_col = _pick(keys, PRICE_CANDIDATES)
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code_col = _pick(keys, ["stock_code", "ts_code", "code", "security_code"]) or "stock_code"
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out = []
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@ -89,10 +93,11 @@ def fetch_positions() -> dict:
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"avail_qty": _int(r.get(avail_col)) if avail_col else None,
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"cost": _float(r.get(cost_col)) if cost_col else None,
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"frozen": _int(r.get(frozen_col)) if frozen_col else None,
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"price": _float(r.get(price_col)) if price_col else None,
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})
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return {"rows": out, "raw_count": len(rows),
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"columns": {"code": code_col, "qty": qty_col, "avail": avail_col,
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"cost": cost_col, "frozen": frozen_col}}
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"cost": cost_col, "frozen": frozen_col, "price": price_col}}
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def _int(v):
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@ -81,12 +81,22 @@ def replay_fills(*, limit: int = 500) -> dict:
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def _open_instructions() -> list:
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"""在途指令 (回放认领的候选池)。
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dispatched_at 取「下发时点 → 建单时点」, **不用 updated_at**:
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updated_at 每次部分成交回写都会往前跳, 拿它当下发时点会让同一条指令的后续成交
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被时间守卫挡在门外, 误判成外部成交。建单时点是天然的下界, 宁松勿紧。
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"""
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rows = pms_repo.list_instructions(statuses=list(LIVE_INSTR), limit=500)
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return [{"instruction_id": r["instruction_id"], "ts_code": r["ts_code"],
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out = []
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for r in rows:
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prog = r.get("progress") or {}
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out.append({"instruction_id": r["instruction_id"], "ts_code": r["ts_code"],
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"side": r.get("side"), "qty": int(r.get("qty") or 0),
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"exec_qty": int(r.get("exec_qty") or 0), "action": r.get("action"),
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"dispatched_at": str(r.get("updated_at") or r.get("created_at") or "")}
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for r in rows]
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"dispatched_at": str(prog.get("dispatched_at")
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or r.get("created_at") or "")})
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return out
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def _apply_action(act: dict):
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@ -29,17 +29,27 @@ QUOTE_KEY = "tushare:rt_min:1MIN:{code}"
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def _r():
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"""行情 Redis 客户端。
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强制 RESP2 (protocol=2): 目标 Redis 是 6.0 以前的版本, 不认 RESP3 的 HELLO 命令,
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而 redis-py 6.x 默认按 RESP3 握手, 会直接报 "unknown command `HELLO`" 全盘取不到价。
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requirements.txt 已把 redis 锁在 5.x, 这里再显式声明一道 (老版本 redis-py 不认这个
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参数, 用 TypeError 兜回去)。
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"""
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global _redis
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if _redis is not None:
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return _redis
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with _lock:
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if _redis is None:
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import redis
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_redis = redis.Redis(
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host=settings.SIGNAL_REDIS_HOST, port=settings.SIGNAL_REDIS_PORT,
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kw = dict(host=settings.SIGNAL_REDIS_HOST, port=settings.SIGNAL_REDIS_PORT,
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password=settings.SIGNAL_REDIS_PASSWORD or None,
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db=settings.SIGNAL_REDIS_DB_QUOTES, decode_responses=True,
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socket_timeout=settings.SIGNAL_REDIS_SOCKET_TIMEOUT)
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try:
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_redis = redis.Redis(protocol=2, **kw)
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except TypeError:
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_redis = redis.Redis(**kw)
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return _redis
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"PMS_REPLAY_INTERVAL_MIN": "成交回放间隔 (分钟)", "PMS_RECON_ALARM_DAYS": "连续不一致升级天数",
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}
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_cache = {"at": 0.0, "data": {}, "error": None}
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# loaded 标记必不可少: 不能用「data 是否为空」判断缓存是否有效 ——
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# 参数表为空 (还没在页面改过参数) 或读表失败时 data 都是 {}, 那样每次 get() 都会穿透去连库,
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# 健康时是白白打表, 故障时是刷屏重试。实测 check_db 一次跑出 50 条重复告警即此故。
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_cache = {"at": 0.0, "data": {}, "error": None, "loaded": False}
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_lock = threading.Lock()
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def refresh(force: bool = False) -> dict:
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"""拉一次表值 (带 TTL 缓存)。连库失败不抛异常 —— 退回文件初值并记 error。"""
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now = time.time()
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if not force and now - _cache["at"] < CACHE_TTL and _cache["data"]:
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if not force and _cache["loaded"] and now - _cache["at"] < CACHE_TTL:
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return _cache["data"]
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with _lock:
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try:
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rows = pms_repo.all_params()
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_cache.update({"data": rows, "at": now, "error": None})
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_cache.update({"data": rows, "at": now, "error": None, "loaded": True})
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except Exception as e:
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_cache.update({"at": now, "error": f"{type(e).__name__}: {e}"})
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msg = f"{type(e).__name__}: {e}"
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changed = _cache.get("error") != msg
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# 失败也要更新时间戳并置 loaded, 否则下一次 get() 立刻又去连库
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_cache.update({"at": now, "error": msg, "loaded": True})
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if changed: # 同一个错误只吼一次, 恢复或换错才再吼
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logger.warning("参数表读取失败, 退回 settings 初值: %s", e)
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return _cache["data"]
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@ -197,7 +204,7 @@ def set_param(key: str, value, updated_by: str = "user") -> dict:
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pms_repo.set_param(key, v, updated_by)
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except Exception as e:
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return {"ok": False, "error": f"写入失败: {type(e).__name__}: {e}"}
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_cache["at"] = 0.0
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_cache["loaded"] = False
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refresh(force=True)
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return {"ok": True, "key": key, "value": v}
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@ -24,7 +24,10 @@ class Settings(BaseSettings):
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# 153 代理: pms_* 全部表 + trading_position / trading_order / trading_buy_plan /
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# strategy_daily_results (决策系统结论) —— 严格单表访问, 代理禁多表联查
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SOURCE_DB_EXT_DSN: str = "mysql+pymysql://user:pass@192.168.16.150:3306/factordb_mysql"
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# 因子分表 gp_stock_factor_pro_* (自算参考位/MA/ATR/量比)
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# 因子库直连。**PMS 当前不使用**: 因子分表 gp_stock_factor_pro_YYYYMM 经
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# ShardingSphere 动态分配物理落点, 直连单台会在分片变动的月份漏表, 必须走
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# PROXY_DB_URL 逐表单查 (沿用 bionic_trader 的踩坑结论)。保留本键仅为与 bionic
|
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# 的 .env 对齐, 连不通不影响任何功能。
|
||||
DB_MYSQL_URL: str = "mysql+pymysql://user:pass@192.168.18.199:3306/db_gp_cj"
|
||||
# 大盘指数 zs_day_data (页面区制提示用, 非约束)
|
||||
|
||||
|
|
|
|||
|
|
@ -2,7 +2,10 @@ pydantic>=2.5
|
|||
pydantic-settings>=2.1
|
||||
SQLAlchemy>=2.0
|
||||
PyMySQL>=1.1
|
||||
redis>=5.0
|
||||
# redis-py 6.x 默认按 RESP3 握手 (先发 HELLO 3), 而 208/150 两台 Redis 是 6.0 以前的版本,
|
||||
# 会回 "unknown command HELLO" 导致行情与 Celery 总线全断 —— 锁在 5.x (默认 RESP2)。
|
||||
# 代码侧另有 protocol=2 双保险 (app/services/market.py)。
|
||||
redis>=5.0,<6.0
|
||||
celery>=5.3
|
||||
fastapi>=0.110
|
||||
uvicorn>=0.27
|
||||
|
|
|
|||
|
|
@ -43,8 +43,8 @@ def main():
|
|||
from app.db import session as dbs
|
||||
|
||||
print("\n[1] 数据库连通性")
|
||||
for name, label in (("proxy", "153 代理 (pms_* / trading_*)"),
|
||||
("factor", "因子分表库"), ("index", "大盘指数库")):
|
||||
for name, label in (("proxy", "153 代理 (pms_* / trading_* / 因子分表)"),
|
||||
("index", "大盘指数库")):
|
||||
r = dbs.ping(name)
|
||||
if r["ok"]:
|
||||
line("OK", f"{label}")
|
||||
|
|
@ -52,31 +52,51 @@ def main():
|
|||
fail(f"{label} 连接失败: {r['error']}")
|
||||
else:
|
||||
warn(f"{label} 连接失败 (非致命): {r['error']}")
|
||||
rf = dbs.ping("factor")
|
||||
line("OK" if rf["ok"] else "INFO",
|
||||
"因子库直连 (SOURCE_DB_EXT_DSN) —— PMS 当前**不使用**: 因子分表经 "
|
||||
"ShardingSphere 动态分片, 必须走 153 代理读 (沿用 bionic 结论), "
|
||||
f"故此项连不通不影响任何功能。当前: {'通' if rf['ok'] else rf['error'].splitlines()[0]}")
|
||||
|
||||
print("\n[2] PMS 自有表")
|
||||
missing_tables = []
|
||||
for t in PMS_TABLES:
|
||||
try:
|
||||
r = dbs.fetch_one(f"SELECT COUNT(*) AS n FROM {t}")
|
||||
line("OK", f"{t:<20} {r['n']} 行")
|
||||
except Exception as e:
|
||||
msg = str(e)
|
||||
if "does not exist" in msg or "doesn't exist" in msg:
|
||||
missing_tables.append(t)
|
||||
fail(f"{t} 不存在")
|
||||
else:
|
||||
fail(f"{t} 不可用: {type(e).__name__}: {e}")
|
||||
if missing_tables:
|
||||
line("", "→ 建表: docker compose run --rm pms-web python scripts/init_db.py --yes")
|
||||
|
||||
print("\n[3] 下游只读表")
|
||||
print("\n[3] 下游只读表 (完整列定义, 可直接回填 QMT 需求清单 D1)")
|
||||
from app.repo import downstream_repo
|
||||
for t in DOWNSTREAM:
|
||||
try:
|
||||
cols = downstream_repo.describe(t)
|
||||
line("OK", f"{t:<20} {len(cols)} 列: "
|
||||
f"{', '.join(str(c.get('Field')) for c in cols[:10])}"
|
||||
f"{' ...' if len(cols) > 10 else ''}")
|
||||
line("OK", f"{t} —— {len(cols)} 列")
|
||||
for c in cols:
|
||||
line("", f" {str(c.get('Field')):<26} {str(c.get('Type')):<18} "
|
||||
f"{'NULL' if str(c.get('Null')).upper() == 'YES' else 'NOT NULL':<9}"
|
||||
f"{str(c.get('Comment') or '')[:40]}")
|
||||
except Exception as e:
|
||||
warn(f"{t} 读取失败: {type(e).__name__}: {e}")
|
||||
try:
|
||||
ds = downstream_repo.fetch_positions()
|
||||
line("OK" if ds["columns"].get("qty") else "WARN",
|
||||
f"持仓列探测: {ds['columns']} (共 {ds['raw_count']} 行)")
|
||||
if ds["raw_count"] and not ds["columns"].get("qty"):
|
||||
warn("未识别出持仓数量列 —— 请按 QMT 需求清单 A1/D1 取得 DDL 后补 QTY_CANDIDATES")
|
||||
warn(f"未识别出持仓数量列 {ds['columns']} —— 把真实列名补进 "
|
||||
f"downstream_repo.QTY_CANDIDATES")
|
||||
else:
|
||||
line("OK", f"持仓列映射: {ds['columns']} (共 {ds['raw_count']} 行)")
|
||||
sample = ds["rows"][:3]
|
||||
for s in sample:
|
||||
line("", f" {s['ts_code']:<12} 持仓 {s['qty']} 可用 {s['avail_qty']} "
|
||||
f"成本 {s['cost']} 现价 {s['price']}")
|
||||
except Exception as e:
|
||||
warn(f"持仓快照读取失败: {e}")
|
||||
|
||||
|
|
@ -89,12 +109,19 @@ def main():
|
|||
pos = [p["ts_code"] for p in pms_repo.list_positions(only_open=True)][:3]
|
||||
except Exception:
|
||||
pass
|
||||
if not pos:
|
||||
try:
|
||||
pos = [r["ts_code"] for r in downstream_repo.fetch_positions()["rows"][:3]]
|
||||
except Exception:
|
||||
pos = []
|
||||
probe = pos or ["600000.SH"]
|
||||
got = {c: market.get_price(c) for c in probe}
|
||||
if any(v for v in got.values()):
|
||||
line("OK", f"实时价样本: {got}")
|
||||
else:
|
||||
warn(f"取不到实时价样本 {got} (非交易时段属正常)")
|
||||
warn(f"取不到实时价样本 {got} (非交易时段属正常; 若报 unknown command HELLO, "
|
||||
f"说明 redis-py 版本过新走了 RESP3, 重新 build 镜像即可 —— "
|
||||
f"requirements 已锁 redis<6)")
|
||||
except Exception as e:
|
||||
warn(f"Redis 行情不可用: {type(e).__name__}: {e}")
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,145 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
建表脚本: 把 ddl_pms_v1.sql 应用到 153 代理侧
|
||||
===============================================
|
||||
运行:
|
||||
docker compose run --rm pms-web python scripts/init_db.py # 演练, 只打印不执行
|
||||
docker compose run --rm pms-web python scripts/init_db.py --yes # 实际建表
|
||||
docker compose run --rm pms-web python scripts/init_db.py --yes --only pms_command,pms_plan
|
||||
|
||||
说明:
|
||||
* 全部语句为 `CREATE TABLE IF NOT EXISTS`, 重复执行安全 (已存在的表不会被改动)。
|
||||
* 直接用引擎执行, 绕过 db.session 的单表守卫 —— DDL 本身就只涉及一张表,
|
||||
但语句里的中文注释可能撞上守卫的关键字启发式, 没必要让它误伤。
|
||||
* ShardingSphere-Proxy 对 DDL 的支持视配置而定。若某条语句被代理拒绝,
|
||||
脚本会把完整语句打出来, 直接拿去物理库 (my_quant_db) 执行即可, 其余语句不受影响。
|
||||
"""
|
||||
import argparse
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
|
||||
DDL_FILE = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
|
||||
"ddl_pms_v1.sql")
|
||||
|
||||
|
||||
def split_sql(text: str) -> list:
|
||||
"""按分号切语句, 但**跳过字符串字面量里的分号**。
|
||||
|
||||
DDL 的列注释里有 `COMMENT '参数命令: EFFECTIVE/SUPERSEDED; 任务命令: PENDING/...'`,
|
||||
直接 split(";") 会把一条 CREATE TABLE 劈成三段残句 —— 必须带引号状态机。
|
||||
"""
|
||||
out, buf, in_str, i = [], [], False, 0
|
||||
while i < len(text):
|
||||
ch = text[i]
|
||||
if in_str:
|
||||
if ch == "\\" and i + 1 < len(text): # 反斜杠转义
|
||||
buf.append(text[i:i + 2])
|
||||
i += 2
|
||||
continue
|
||||
if ch == "'":
|
||||
if i + 1 < len(text) and text[i + 1] == "'": # '' 转义
|
||||
buf.append("''")
|
||||
i += 2
|
||||
continue
|
||||
in_str = False
|
||||
buf.append(ch)
|
||||
elif ch == "'":
|
||||
in_str = True
|
||||
buf.append(ch)
|
||||
elif ch == ";":
|
||||
out.append("".join(buf))
|
||||
buf = []
|
||||
else:
|
||||
buf.append(ch)
|
||||
i += 1
|
||||
out.append("".join(buf))
|
||||
return out
|
||||
|
||||
|
||||
def parse_statements(sql_text: str) -> list:
|
||||
"""去掉整行 `--` 注释后切语句。返回 [(表名, 语句)]; 非 CREATE TABLE 的残句会被标 '?'。"""
|
||||
body = "\n".join(ln for ln in sql_text.splitlines() if not ln.strip().startswith("--"))
|
||||
out = []
|
||||
for stmt in split_sql(body):
|
||||
s = stmt.strip()
|
||||
if not s:
|
||||
continue
|
||||
m = re.search(r"CREATE\s+TABLE\s+(?:IF\s+NOT\s+EXISTS\s+)?`?([A-Za-z0-9_]+)`?", s, re.I)
|
||||
out.append((m.group(1) if m else "?", s))
|
||||
return out
|
||||
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser()
|
||||
ap.add_argument("--yes", action="store_true", help="确认执行 (缺省只演练)")
|
||||
ap.add_argument("--only", default="", help="只处理指定表, 逗号分隔")
|
||||
args = ap.parse_args()
|
||||
|
||||
if not os.path.exists(DDL_FILE):
|
||||
print(f"FAIL 找不到 DDL 文件: {DDL_FILE}")
|
||||
sys.exit(1)
|
||||
with open(DDL_FILE, encoding="utf-8") as f:
|
||||
stmts = parse_statements(f.read())
|
||||
only = {x.strip() for x in args.only.split(",") if x.strip()}
|
||||
if only:
|
||||
stmts = [(t, s) for t, s in stmts if t in only]
|
||||
if not stmts:
|
||||
print("FAIL 没有可执行的语句 (检查 --only 是否写对)")
|
||||
sys.exit(1)
|
||||
broken = [s for t, s in stmts if t == "?"]
|
||||
if broken:
|
||||
print(f"FAIL 解析出 {len(broken)} 条非 CREATE TABLE 残句, 说明 DDL 切分有误, "
|
||||
f"已中止 (不执行任何语句)。首条残句:\n{broken[0][:200]}")
|
||||
sys.exit(1)
|
||||
|
||||
print(f"DDL 文件: {DDL_FILE}")
|
||||
print(f"待建表 {len(stmts)} 张: {', '.join(t for t, _ in stmts)}")
|
||||
if not args.yes:
|
||||
print("\n[演练模式] 未执行任何语句。确认无误后加 --yes 重跑:")
|
||||
print(" docker compose run --rm pms-web python scripts/init_db.py --yes")
|
||||
return
|
||||
|
||||
# 连库依赖放到演练之后再导入: 演练模式只做语句切分校验, 无依赖环境也能跑
|
||||
from sqlalchemy import text
|
||||
from app.db.session import get_engine
|
||||
|
||||
eng = get_engine("proxy")
|
||||
okc, failed = 0, []
|
||||
print()
|
||||
for tbl, stmt in stmts:
|
||||
try:
|
||||
with eng.begin() as c:
|
||||
c.execute(text(stmt))
|
||||
print(f" OK {tbl}")
|
||||
okc += 1
|
||||
except Exception as e:
|
||||
print(f" FAIL {tbl}: {type(e).__name__}: {e}")
|
||||
failed.append((tbl, stmt, str(e)))
|
||||
|
||||
print("\n[验证] 逐表 COUNT(*)")
|
||||
missing = []
|
||||
for tbl, _ in stmts:
|
||||
try:
|
||||
with eng.connect() as c:
|
||||
n = c.execute(text(f"SELECT COUNT(*) FROM {tbl}")).scalar()
|
||||
print(f" OK {tbl:<20} {n} 行")
|
||||
except Exception as e:
|
||||
print(f" FAIL {tbl:<20} {type(e).__name__}: {e}")
|
||||
missing.append(tbl)
|
||||
|
||||
print("\n" + "-" * 62)
|
||||
if failed:
|
||||
print(f"以下 {len(failed)} 张表建失败, 完整语句如下 —— 可直接拿到物理库执行:")
|
||||
for tbl, stmt, err in failed:
|
||||
print(f"\n### {tbl} ({err.splitlines()[0]})\n{stmt};")
|
||||
if missing:
|
||||
print(f"\nFAILED: {len(missing)} 张表仍不可用: {', '.join(missing)}")
|
||||
sys.exit(1)
|
||||
print(f"ALL OK: {okc} 张表就绪, 接着跑 python scripts/check_db.py 做完整自检")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
|
@ -332,7 +332,7 @@ def install_fakes(prices=None, positions=None, params=None):
|
|||
downstream_repo.fetch_positions = lambda: {"rows": [], "columns": {"qty": None},
|
||||
"raw_count": 0}
|
||||
downstream_repo.fetch_refs = lambda c: None
|
||||
param_store._cache.update({"at": 0.0, "data": {}, "error": None})
|
||||
param_store._cache.update({"at": 0.0, "data": {}, "error": None, "loaded": False})
|
||||
portfolio.save_neg_streak({})
|
||||
return fake
|
||||
|
||||
|
|
@ -583,6 +583,12 @@ def _():
|
|||
fake.insert_instruction(instruction_id="INS_A", origin_type="plan", origin_id="P1",
|
||||
ts_code="600000.SH", action="OPEN", side="buy", qty=6000,
|
||||
limit_price=10.0, status="DISPATCHED")
|
||||
# 建单时点必须显式钉死: 用 datetime.now() 会让本用例的通过与否取决于跑测试的钟点
|
||||
# (时间守卫要求 下发 ≤ 成交), 17:12 跑就会误判成外部成交 —— 实机上已踩到。
|
||||
fake.instructions["INS_A"]["created_at"] = "2026-07-27 09:30:00"
|
||||
# updated_at 故意置在成交之后: 认领必须看建单时点, 不能看 updated_at
|
||||
# (否则部分成交回写一次 updated_at, 后续成交就会被自己挡住)
|
||||
fake.instructions["INS_A"]["updated_at"] = "2026-07-27 23:59:59"
|
||||
fills = [{"order_id": 101, "ts_code": "600000.SH", "side": "buy", "qty": 6000,
|
||||
"price": 10.0, "done_time": "2026-07-27 09:40:00"}]
|
||||
orig = downstream_repo.fetch_filled_orders
|
||||
|
|
|
|||
Loading…
Reference in New Issue