# -*- coding: utf-8 -*- """ 下游/上游只读表访问 (trading_* 与 strategy_daily_results, 153 代理, 严格单表) ============================================================================== 这三张表**归下游系统维护**, PMS 只读 (设计 §9)。 列名口径 (2026-07-27 实机 SHOW COLUMNS 确认, 见 check_db.py 输出): trading_position: id, stock_code, stock_name, total_quantity, available_quantity, frozen_quantity, cost_price, market_price, market_value, profit_loss, ... → **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, 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)。 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 「运维 → 导出下游表结构」可见, 也是回填 D1 的现成材料。 """ from __future__ import annotations from app.db.session import fetch_all, fetch_one # 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) QTY_CANDIDATES = ["total_quantity", "current_qty", "total_qty", "position_qty", "hold_qty", "stock_qty", "volume", "quantity", "qty", "position_volume", "hold_volume"] AVAIL_CANDIDATES = ["available_quantity", "available_qty", "avail_qty", "can_use_volume", "available_volume", "sellable_qty", "enable_amount", "can_sell_qty"] COST_CANDIDATES = ["cost_price", "avg_cost", "open_price", "position_cost", "cost"] FROZEN_CANDIDATES = ["frozen_quantity", "frozen_qty", "frozen_volume", "freeze_qty"] PRICE_CANDIDATES = ["market_price", "last_price", "current_price", "price"] FILLED_STATUSES = ("completed", "filled") def to_dot(code: str) -> str: """SH600000 / 600000 → 600000.SH (PMS 内部统一点式)。""" c = (code or "").strip().upper() if not c: return "" if "." in c: return c if c[:2] in ("SH", "SZ", "BJ") and c[2:].isdigit(): return f"{c[2:]}.{c[:2]}" if c.isdigit() and len(c) == 6: return f"{c}.SH" if c[0] == "6" else (f"{c}.SZ" if c[0] in "03" else f"{c}.BJ") return c def to_prefix(code: str) -> str: """600000.SH → SH600000 (strategy_daily_results 口径)。""" c = (code or "").strip().upper() if "." in c: num, mkt = c.split(".", 1) return f"{mkt}{num}" return c def _pick(keys, candidates): low = {str(k).lower(): k for k in keys} for c in candidates: if c in low: return low[c] return None def describe(table: str) -> list: """SHOW COLUMNS —— 供页面导出、回填 QMT_INTERFACE_REQUIREMENTS D1。""" if table not in ("trading_position", "trading_order", "trading_buy_plan", "strategy_daily_results", "gp_stock_category"): raise ValueError(f"不允许探测的表: {table}") return fetch_all(f"SHOW COLUMNS FROM {table}") # ================================================================ trading_position def fetch_positions() -> dict: """下游持仓快照。返回 {"rows":[{ts_code, qty, avail_qty, cost, frozen}], "columns":{...}}""" rows = fetch_all("SELECT * FROM trading_position LIMIT 1000") if not rows: return {"rows": [], "columns": {"qty": None, "avail": None, "cost": None}, "raw_count": 0} keys = rows[0].keys() qty_col = _pick(keys, QTY_CANDIDATES) avail_col = _pick(keys, AVAIL_CANDIDATES) cost_col = _pick(keys, COST_CANDIDATES) frozen_col = _pick(keys, FROZEN_CANDIDATES) price_col = _pick(keys, PRICE_CANDIDATES) code_col = _pick(keys, ["stock_code", "ts_code", "code", "security_code"]) or "stock_code" out = [] for r in rows: code = to_dot(str(r.get(code_col) or "")) if not code: continue out.append({ "ts_code": code, "qty": _int(r.get(qty_col)) if qty_col else None, "avail_qty": _int(r.get(avail_col)) if avail_col else None, "cost": _float(r.get(cost_col)) if cost_col else None, "frozen": _int(r.get(frozen_col)) if frozen_col else None, "price": _float(r.get(price_col)) if price_col else None, }) return {"rows": out, "raw_count": len(rows), "columns": {"code": code_col, "qty": qty_col, "avail": avail_col, "cost": cost_col, "frozen": frozen_col, "price": price_col}} def _int(v): try: return int(float(v or 0)) except (TypeError, ValueError): return 0 def _float(v): try: return float(v or 0) except (TypeError, ValueError): return 0.0 # ================================================================ trading_order def fetch_filled_orders(*, since_id=None, since_time=None, limit: int = 500) -> list: """已成交单增量拉取 (回放用)。价格口径: filled_price > order_price (下游 filled_amount 不可靠)。 order_id 可能是字符串委托号 —— 游标同时支持数值与字符串比较, 取不到则按时间兜底。 """ # 状态枚举为常量 (QMT A2 待正式确认), 直接内联避免 IN 绑定展开 where = ["order_status IN ('" + "', '".join(FILLED_STATUSES) + "')"] p = {"n": int(limit)} if since_id not in (None, "", 0): where.append("order_id > :sid") p["sid"] = since_id elif since_time: where.append("(filled_time >= :st OR order_time >= :st)") p["st"] = since_time sql = ("SELECT * FROM trading_order WHERE " + " AND ".join(where) + " ORDER BY order_id ASC LIMIT :n") rows = fetch_all(sql, p) return [_norm_order(r) for r in rows] def latest_filled_order_id(): """当前已成交单里最大的 order_id —— 回放游标冷启动时的锚点。 取 MAX 而不是"最新时间", 是为了跟游标推进用同一把尺子: `fetch_filled_orders` 走的是 `order_id > :sid` + `ORDER BY order_id ASC`, 即**字典序** (order_id 形如 `SELL_601956.SH_1778549400`, 并非时间序)。锚点若按时间取, 会跟字典序对不上而漏行。 """ r = fetch_one("SELECT MAX(order_id) AS mx FROM trading_order WHERE order_status IN ('" + "', '".join(FILLED_STATUSES) + "')") return (r or {}).get("mx") def _norm_order(r: dict) -> dict: side = str(r.get("order_side") or "").strip().lower() if side in ("1", "b", "买入", "买"): side = "buy" elif side in ("2", "s", "卖出", "卖"): side = "sell" qty = r.get("filled_quantity") or r.get("filled_qty") or r.get("order_quantity") price = r.get("filled_price") or r.get("filled_avg_price") or r.get("order_price") return {"order_id": r.get("order_id"), "ts_code": to_dot(str(r.get("stock_code") or "")), "side": side, "qty": _int(qty), "price": _float(price), "done_time": str(r.get("filled_time") or r.get("order_time") or ""), "status": r.get("order_status"), "raw": r} # ================================================================ trading_buy_plan def fetch_buy_plans(*, is_active=None, limit: int = 200) -> list: """上游买入计划 (PMS 作为承接方, 替代原 ENTRY_GATE 角色 —— 设计 §6)。 is_active: 7=待仲裁 (上游产出待承接), 6=待挂单 (下游取走), 5=盘中拒。 """ sql = ("SELECT id, strategy_id, stock_code, stock_name, target_price, buy_amount, " "factor_code, trading_time, create_time, update_time, tp_ratio, sl_ratio, " "prob_thresh, hold_days, is_active, approved_by FROM trading_buy_plan") p = {"n": int(limit)} if is_active is not None: sql += " WHERE is_active = :ia" p["ia"] = int(is_active) sql += " ORDER BY update_time DESC LIMIT :n" rows = fetch_all(sql, p) out = [] for r in rows: px = _float(r.get("target_price")) out.append({"plan_id": r.get("id"), "ts_code": to_dot(str(r.get("stock_code") or "")), "name": r.get("stock_name"), "price": px, "amount": _float(r.get("buy_amount")), "score": _float(r.get("prob_thresh")), "factor": r.get("factor_code"), "tp_ratio": _float(r.get("tp_ratio")), "sl_ratio": _float(r.get("sl_ratio")), "is_active": r.get("is_active"), "update_time": r.get("update_time")}) return out # ================================================================ strategy_daily_results def fetch_refs(ts_code: str): """决策系统昨夜结论: 支撑/压力参考位 (主口径; 停更超期由 services 兜底自算)。""" r = fetch_one( "SELECT stock_code, signal_type, support_level, pressure_level, trade_date " "FROM strategy_daily_results WHERE stock_code = :code " "ORDER BY trade_date DESC LIMIT 1", {"code": to_prefix(ts_code)}) if not r: return None return {"ts_code": ts_code, "signal_type": r.get("signal_type"), "support": _float(r.get("support_level")) or None, "pressure": _float(r.get("pressure_level")) or None, "trade_date": r.get("trade_date")} INDUSTRY_COL_CANDIDATES = ("industry", "category", "sector", "industry_name", "sw_industry", "sw_l1", "sw_l2", "industry_l1", "board_name", "plate_name") CODE_COL_CANDIDATES = ("ts_code", "stock_code", "code", "symbol", "sec_code", "secu_code", "security_code", "gp_code") _cat_cols = {"at": 0.0, "data": None} CAT_COLS_TTL = 600.0 def category_columns(force: bool = False) -> dict: """`SHOW COLUMNS FROM gp_stock_category` → 认出代码列与行业列 (缓存 10 分钟)。 先认列再查, 而不是拿一堆候选列名硬撞: 2026-07-31 实测撞出来的是 `Unknown column 'stock_code'` —— 报错本身没错, 但撞法会把「列不存在」和「这只票不在 表里」混成一锅, 而且错误串长到没法看。SHOW COLUMNS 一次就说清了。 """ import time now = time.time() if not force and _cat_cols["data"] is not None and now - _cat_cols["at"] < CAT_COLS_TTL: return _cat_cols["data"] d = {"columns": None, "code_col": None, "industry_col": None, "error": None} try: rows = fetch_all("SHOW COLUMNS FROM gp_stock_category") cols = [str(r.get("Field") or r.get("field") or r.get("COLUMN_NAME") or "") for r in (rows or [])] cols = [c for c in cols if c] d["columns"] = cols low = {c.lower(): c for c in cols} d["code_col"] = next((low[k] for k in CODE_COL_CANDIDATES if k in low), None) d["industry_col"] = next((low[k] for k in INDUSTRY_COL_CANDIDATES if k in low), None) if not cols: d["error"] = "SHOW COLUMNS 回了空 —— 表可能不存在或代理不给看" elif not d["code_col"]: d["error"] = f"没有可识别的代码列; 实际列: {cols}" elif not d["industry_col"]: d["error"] = f"没有可识别的行业列; 实际列: {cols}" except Exception as e: d["error"] = f"{type(e).__name__}: {str(e)[:200]}" _cat_cols.update({"at": now, "data": d}) return d def probe_category(ts_code: str) -> dict: """查 gp_stock_category 并把**过程**带出来。 存在的理由: 原来的 fetch_sector_from_category 把异常 `except: continue` 吞掉, 表不存在 / 列名对不上 / 代理拒绝 一律返回 None, 跟"这只票没有行业"完全无法区分 —— 于是行业硬拦截会**静默失效**。调用方要判"数据源到底通不通", 必须看得见 error。 返回 {value, code_col, industry_col, columns, error}: value=None 且 error=None 才是真正的"表能用, 只是这只票不在里面"。 """ meta = category_columns() out = {"value": None, "code_col": meta.get("code_col"), "industry_col": meta.get("industry_col"), "columns": meta.get("columns"), "error": meta.get("error")} if out["error"] or not out["code_col"]: return out col = out["code_col"] dot = to_dot(ts_code) forms = [dot, to_prefix(dot), dot.split(".")[0]] # 点式 / 前缀式 / 纯数字 for form in dict.fromkeys(forms): try: r = fetch_one(f"SELECT * FROM gp_stock_category WHERE {col} = :code LIMIT 1", {"code": form}) except Exception as e: out["error"] = f"{col}={form}: {type(e).__name__}: {str(e)[:160]}" return out if r: out["matched_form"] = form ind = out["industry_col"] if ind and r.get(ind): out["value"] = str(r[ind]) else: for k in INDUSTRY_COL_CANDIDATES: if r.get(k): out["value"], out["industry_col"] = str(r[k]), k break return out return out def fetch_sector_from_category(ts_code: str): """行业适配器 gp_stock_category (映射表就绪前的临时数据源 —— 设计 §5)。""" return probe_category(ts_code)["value"] # ================================================================ gp_code_all (中文名映射) # 只读, 严格单表 (session.assert_single_table 不许 JOIN/逗号连表): 名称走 153 代理的 # gp_code_all。gp_code_two 是点式 (688280.SH, 与 PMS 内部一致), gp_code 是前缀式 # (SH688280) —— 两列都匹配一遍, 兜住个别行 gp_code_two 为空。表里 industry 列不可靠 # (示例为 NULL), 不在这里取行业, 行业仍走 fetch_sector_from_category。 _NAME_CACHE = {} # 点式 ts_code -> {"name","full"} _NAME_AT = {} # 点式 ts_code -> 写入时刻 epoch _NAME_TTL = 6 * 3600 # 名称基本不变, 缓存 6 小时, 免得每次刷新都撞库 def fetch_names(codes) -> dict: """代码 → {"name": 简称, "full": 全称}。取不到的代码退回 name=代码本身。""" import time now = time.time() dots, out = [], {} for c in (codes or []): dot = to_dot(str(c or "")) if not dot: continue hit = _NAME_CACHE.get(dot) if hit is not None and now - _NAME_AT.get(dot, 0) < _NAME_TTL: out[dot] = hit else: dots.append(dot) dots = list(dict.fromkeys(dots)) if not dots: return out prefixes = [to_prefix(x) for x in dots] binds, dkeys, pkeys = {}, [], [] for i, (dot, pre) in enumerate(zip(dots, prefixes)): binds["d%d" % i] = dot dkeys.append(":d%d" % i) binds["p%d" % i] = pre pkeys.append(":p%d" % i) sql = ("SELECT gp_code, gp_code_two, gp_name, fullname FROM gp_code_all " "WHERE gp_code_two IN (%s) OR gp_code IN (%s)" % (", ".join(dkeys), ", ".join(pkeys))) found = {} try: for r in fetch_all(sql, binds): code = to_dot(str(r.get("gp_code_two") or r.get("gp_code") or "")) if not code: continue nm = str(r.get("gp_name") or "").strip() found[code] = {"name": nm or code, "full": str(r.get("fullname") or "").strip()} except Exception: # 库不可达 / 表不在: 本轮退回代码本身, **不写缓存** (下次重试) return {**out, **{dot: {"name": dot, "full": ""} for dot in dots}} for dot in dots: rec = found.get(dot) or {"name": dot, "full": ""} _NAME_CACHE[dot] = rec _NAME_AT[dot] = now out[dot] = rec return out