"""选股计划逐票对账(只读)——"这只票为什么在/不在计划里"。 背景:机会线索页(基座前端,环节级雷达,跑全部主题池)与每日选股计划 (个股级,券商覆盖 ∩ upside≥0 ∩ 十条赛道 ∩ 非风险,传导档优先排序) 答的不是同一个问题,读数经常"看起来大相径庭"。本工具把任意一只票的 全部判定摊开:赛道命中(哪路)、覆盖与 upside、热度、传导(谁指向它)、 gate、score、榜位名次,落榜给出确切原因——审计承诺(下游对接文档 "每只候选可回溯")的落地件。 跑法【桥机 factorevaluation-UTC · ~/akg-factor-bridge】: docker compose exec -T akg-factor-bridge python plan_reconcile.py 300750 SH600438 002074.SZ docker compose exec -T akg-factor-bridge python plan_reconcile.py # 不带票=打印当日主榜前20/观察档前10 docker compose exec -T akg-factor-bridge python plan_reconcile.py --date 2026-08-04 300750 代码三种形态都收(600000.SH / SH600000 / 600000,600/688 归 SH,其余归 SZ)。 纯只读:因子表 / 基座视图 / yml 全部 SELECT 与本地解析,不写任何东西。 """ from __future__ import annotations import re import sys import pandas as pd import common import db import tracks _RISK_RE = re.compile(r"^(\*?S?ST|退市)") def _norm_code(s: str) -> str: """任意形态 -> 前缀式(SH600000)。裸 6 位码按交易所惯例补前缀。""" s = s.strip().upper() if re.fullmatch(r"\d{6}\.(SH|SZ|BJ)", s): return common.to_prefix(s) if re.fullmatch(r"(SH|SZ|BJ)\d{6}", s): return s if re.fullmatch(r"\d{6}", s): exch = "SH" if s[0] == "6" else ("BJ" if s[0] in "48" else "SZ") return f"{exch}{s}" raise SystemExit(f"认不出的代码形态: {s!r}(收 600000.SH / SH600000 / 600000)") def _factor(table: str, d: str) -> dict[str, float]: df = db.read_mysql("factor", f"SELECT stock_code, factor_value FROM {table} " f"WHERE trade_date=%s", (d,)) return {str(r.stock_code).strip(): float(r.factor_value) for r in df.itertuples()} def _load(d: str): gate = _factor("t_factor_akg_gate", d) score = _factor("t_factor_akg_score", d) upside = _factor("t_factor_akg_upside", d) heat = _factor("t_factor_akg_heat", d) tr = _factor("t_factor_akg_transmission", d) # 赛道命中:前缀码 -> [(赛道, 命中键, 路)],图谱路在前(resolve 已排好) tdf, _missing = tracks.resolve_members(only_confirmed=True, dedup=False) hits: dict[str, list[tuple[str, str, str]]] = {} for r in tdf.itertuples(): hits.setdefault(common.to_prefix(str(r.ts_code)), []).append( (r.track, r.theme, r.source_rule)) # 按锚强度排序(环节锚 > 链锚 > 主题弱锚)。resolve_members 是按 yml 里 # 赛道的先后顺序产行的,不排序的话 hits[0] 取到的是"yml 中最靠前的赛道", # 而不是"最强的锚"——08-05 实测宁德时代显示成算力、国轩高科显示成通信, # 就是这么来的:真凭据在后面,前面那条是宽主题捞进来的。勿回退。 _RULE_RANK = {"graph_segment": 0, "graph_chain": 1, "pool_theme": 2} for k in hits: hits[k].sort(key=lambda h: _RULE_RANK.get(h[2], 9)) # 传导指向:scan_date=d 的候选里谁的 quiet 含这只票 try: tv = db.read_pg( "SELECT ts_code, target, n_sources, moved_ratio, mkt_trade_date " "FROM v_factor_transmission WHERE scan_date=%s", (d,)) except Exception as e: # noqa: BLE001 —— 视图不可用只影响传导明细 print(f"⚠️ v_factor_transmission 读取失败(传导明细缺席): {e!r}") tv = pd.DataFrame(columns=["ts_code", "target", "n_sources", "moved_ratio", "mkt_trade_date"]) tmap: dict[str, list[str]] = {} for r in tv.itertuples(): tmap.setdefault(common.to_prefix(str(r.ts_code)), []).append( f"{r.target}(源{int(r.n_sources)}×空间{1 - float(r.moved_ratio):.0%})") stale = "" if len(tv) and tv["mkt_trade_date"].notna().any(): md = str(tv["mkt_trade_date"].dropna().iloc[0])[:10] if md != d: stale = f"(⚠️ 传导快照日 {md} ≠ 档位日 {d},该日传导降级采信)" # 图谱证据 + 简称 ev: dict[str, dict] = {} try: mem = db.read_pg("SELECT segment_name, ts_code, chain " "FROM v_factor_segment_members WHERE ts_code IS NOT NULL") for r in mem.itertuples(): k = common.to_prefix(str(r.ts_code).strip()) e = ev.setdefault(k, {"segs": set(), "chains": set()}) e["segs"].add(str(r.segment_name)) if r.chain and str(r.chain).strip(): e["chains"].add(str(r.chain).strip()) except Exception as e: # noqa: BLE001 print(f"⚠️ 环节投影读取失败(图谱证据缺席): {e!r}") names: dict[str, str] = {} try: import json as _json pools = db.read_pg("SELECT members FROM industry_pools") for _, row in pools.iterrows(): ms = row["members"] if isinstance(ms, str): ms = _json.loads(ms) for m in ms or []: if (m or {}).get("ts_code"): names.setdefault(common.to_prefix(m["ts_code"]), m.get("name") or "") except Exception as e: # noqa: BLE001 print(f"⚠️ 简称加载失败: {e!r}") # 榜位名次:150 是主榜与观察档的分界,**下方不设界**—— # 观察档分 = 100 + clip(组内分, ±9.9),区间是 [90.1, 109.9], # 首版写 sc>=100 把 [90.1,100) 那半截整段漏掉(08-05 实测:md 说 675、 # 工具只数出 232,差 443 只)。score 表本就只有 gate>0 的票出行, # 低于 150 的一律是观察档,不需要下界。勿回退。 sc = pd.Series(score) main = sc[sc >= 150].sort_values(ascending=False) obs = sc[sc < 150].sort_values(ascending=False) rank_main = {k: i + 1 for i, k in enumerate(main.index)} rank_obs = {k: i + 1 for i, k in enumerate(obs.index)} return dict(gate=gate, score=score, upside=upside, heat=heat, tr=tr, hits=hits, tmap=tmap, stale=stale, ev=ev, names=names, main=main, obs=obs, rank_main=rank_main, rank_obs=rank_obs) def _fmt(v, pat="{:.2f}"): return "—" if v is None else pat.format(v) def explain(k: str, L: dict) -> None: nm = L["names"].get(k, "") g = L["gate"].get(k) up = L["upside"].get(k) ht = L["heat"].get(k) trv = L["tr"].get(k) sc = L["score"].get(k) hits = L["hits"].get(k, []) paths = L["tmap"].get(k, []) e = L["ev"].get(k, {"segs": set(), "chains": set()}) risk = bool(_RISK_RE.match(nm.replace(" ", ""))) if nm else False print(f"\n◆ {k} {nm}") if hits: shown = ";".join(f"{t}←{key}({rule})" for t, key, rule in hits[:4]) print(f" 赛道命中 {len(hits)} 路:{shown}" + ("…" if len(hits) > 4 else "")) else: print(" 赛道命中:无(十条赛道三路映射都够不着)") print(f" 覆盖/upside:{'有覆盖,upside=' + _fmt(up, '{:+.1%}') if up is not None else '无券商覆盖'}" f" 热度:{_fmt(ht)} 传导分:{_fmt(trv)}") if paths: print(f" 传导指向:{';'.join(paths[:4])}" + ("…" if len(paths) > 4 else "")) if e["segs"]: print(f" 图谱证据:环节 {len(e['segs'])} 个({'、'.join(sorted(e['segs'])[:4])}" + ("…" if len(e["segs"]) > 4 else "") + ")" + (f",链名 {'、'.join(sorted(e['chains'])[:4])}" if e["chains"] else ",边上无链名")) if g == 2.0: n = L["rank_main"].get(k) # 档界:score=200+档×20+组内分(±9.9) → 强≥230.1、弱≥210.1、无≤209.9 tier = "强传导" if sc and sc >= 230 else ("弱传导" if sc and sc >= 210 else "无传导") print(f" ▶ 判决:主榜第 {n}/{len(L['main'])} 名(score={sc:.1f},{tier}档)" + ("——计划默认只显示前 20,名次靠后不等于不在计划里" if n and n > 20 else "")) elif g == 1.0: print(f" ▶ 判决:观察档第 {L['rank_obs'].get(k)}/{len(L['obs'])} 名(score={sc:.1f}," f"无券商覆盖、低置信)") elif g == 0.0: if risk: reason = "重大风险闸(ST/退市族),07-31 拍板默认杜绝" elif up is not None and up < 0: reason = f"有覆盖但 upside={up:+.1%} < 0——贵了不买是绝对下限" elif up is not None and hits: reason = "覆盖、upside、赛道三者都过——按机制不该是 0,把本行发我核(疑似口径错位)" elif up is not None: reason = ("有覆盖、upside≥0,但不在十条赛道(赛道闸拦下)" + ("——图上有环节证据,属映射够不着的错杀池,看首批锚能否接住" if e["segs"] else "")) elif not hits and (trv or 0) <= 0: reason = "无覆盖、无传导、不在赛道——两锚皆无" else: reason = "无覆盖且当日不在传导链上(观察档条件差最后一步)" print(f" ▶ 判决:不采纳(gate=0)。原因:{reason}") else: print(" ▶ 判决:当日档位表无此票" + ("(可能不在覆盖池 universe,或当日未出行)" if not hits else "——在赛道却无档位行,把本行发我核")) def audit(L: dict) -> None: """锚质量审计(--audit):主榜成员里有多少是靠宽主题弱锚进来的。 主题弱锚(pool_theme)是 industry_pools 的概念池成员,池宽则噪声大—— 08-05 实测:宁德时代记成算力、国轩高科记成通信、东方日升记成商业航空航天。 档位判定本身不看是哪路锚(在赛道就算数),所以噪声不改变对错、只改变 "凭什么";但宽主题同时也在**放人进主榜**,这才是要拍板的地方。 本审计回答两问:逐赛道的主榜成员有多少带可审计的图谱锚; 哪些主题键在独家放人(该股在所有赛道都没有图谱锚)——它们就是下一批 "降级或剔除"的候选。链锚扩充落地后重跑本审计,看图谱锚占比抬升多少。""" main_set = {k for k, g in L["gate"].items() if g == 2.0} by_track: dict[str, dict[str, set]] = {} theme_only_admits: dict[str, set] = {} n_graph = 0 for k in main_set: hs = L["hits"].get(k, []) if not hs: continue has_graph_any = any(r != "pool_theme" for _, _, r in hs) if has_graph_any: n_graph += 1 for t, key, rule in hs: d = by_track.setdefault(t, {"all": set(), "graph": set()}) d["all"].add(k) if rule != "pool_theme": d["graph"].add(k) if rule == "pool_theme" and not has_graph_any: theme_only_admits.setdefault(key, set()).add(k) n_in_track = sum(1 for k in main_set if L["hits"].get(k)) print(f"\n—— 锚质量审计:主榜 {len(main_set)} 只,其中 {n_in_track} 只在赛道内 ——") print(f" 带图谱锚(环节/链,可审计到图谱边): {n_graph} 只" f"({n_graph / max(1, n_in_track):.0%});" f"仅靠主题弱锚: {n_in_track - n_graph} 只") print("\n 逐赛道(成员数 / 其中带图谱锚):") for t, d in sorted(by_track.items(), key=lambda kv: -len(kv[1]["all"])): print(f" {t:<8} {len(d['all']):>4} / {len(d['graph']):>4}" f"({len(d['graph']) / max(1, len(d['all'])):.0%})") print("\n 独家放人的主题键前 20(这些股在所有赛道都没有图谱锚," "只靠该主题进的主榜——降级候选):") for key, ks in sorted(theme_only_admits.items(), key=lambda kv: -len(kv[1]))[:20]: sample = "、".join(L["names"].get(x, x) for x in sorted(ks)[:3]) print(f" {key:<16} {len(ks):>4} 只 例:{sample}") def main() -> int: args = [a for a in sys.argv[1:]] do_audit = "--audit" in args if do_audit: args.remove("--audit") d = None if "--date" in args: i = args.index("--date") d = args[i + 1] del args[i:i + 2] if d is None: row = db.read_mysql("factor", "SELECT MAX(trade_date) d FROM t_factor_akg_gate") v = None if row.empty else row.iloc[0, 0] if v is None or pd.isna(v): print("档位表为空——先跑当日构建。") return 2 d = pd.Timestamp(v).date().isoformat() L = _load(d) print(f"选股计划对账 @ 档位日 {d}{L['stale']}") print(f"主榜 {len(L['main'])} 只 / 观察档 {len(L['obs'])} 只(150 分界;主榜默认展示前 20)") if do_audit: audit(L) if args: for a in args: explain(_norm_code(a), L) elif not do_audit: print("\n—— 主榜前 20(传导档优先,与计划 API 同序;本清单不设每主题限额," "计划 API 默认 theme_cap=5 故名单会略有出入)——") for i, (k, s) in enumerate(L["main"].head(20).items(), 1): hits = L["hits"].get(k, []) anchor = "?" if hits: t, key, rule = hits[0] anchor = f"{t}←{key}" + ("(弱)" if rule == "pool_theme" else "(图谱)") print(f" {i:>2}. {k} {L['names'].get(k, ''): <6} score={s:.1f} " f"upside={_fmt(L['upside'].get(k), '{:+.1%}')} " f"热度={_fmt(L['heat'].get(k))} " f"赛道={anchor}" + (f" 传导指向={L['tmap'][k][0]}" if L["tmap"].get(k) else "")) print("\n—— 观察档前 10 ——") for i, (k, s) in enumerate(L["obs"].head(10).items(), 1): print(f" {i:>2}. {k} {L['names'].get(k, ''): <6} score={s:.1f} " f"热度={_fmt(L['heat'].get(k))}" + (f" 传导指向={L['tmap'][k][0]}" if L["tmap"].get(k) else "")) print("\n用法:把机会线索卡片上的代表公司码传进来逐票对账," "例如 python plan_reconcile.py 300750 002074 688041") return 0 if __name__ == "__main__": raise SystemExit(main())