From 22384865fbdb92c4ce603c137b1cac52ab6450ba Mon Sep 17 00:00:00 2001
From: Cai <cai@nbcai.cc>
Date: Fri, 11 Sep 2026 18:15:14 +0800
Subject: [PATCH] chore: 更新2026-09-11股票估值每日台账
---
ai-valuation-analyst/tools/enrich_valuation_bubbles.py | 13 +++++++------
1 files changed, 7 insertions(+), 6 deletions(-)
diff --git a/ai-valuation-analyst/tools/enrich_valuation_bubbles.py b/ai-valuation-analyst/tools/enrich_valuation_bubbles.py
index 60bb56f..22ba603 100644
--- a/ai-valuation-analyst/tools/enrich_valuation_bubbles.py
+++ b/ai-valuation-analyst/tools/enrich_valuation_bubbles.py
@@ -639,7 +639,7 @@
f"- 价格交易日：`{trade_date_text}`",
f"- 泡沫解释版本：`{trade_date_text}/v{SCRIPT_VERSION}`",
f"- 记录数：`{len(rows)}`",
- "- 全量覆盖：`677`个已评估主体，其中本表为可形成数值区间判定的`672`只，另`5`只见同目录`latest_gaps.csv`。",
+ f"- 数值判定覆盖：本表共`{len(rows)}`只；无法形成当日数值判定的证券单列于同目录`latest_gaps.csv`。",
f"- 估值泡沫：`{bubble_count}`只；定义为当前价高于正式基准合理区间上沿。",
"- 原因性质：除价格位置外，泡沫原因均是基于反向估值、基础报告和量价显影的最可能解释，不是已证实的资金流因果。",
f"- 输入快照 SHA-256：`{source_hash}`；泡沫解释脚本：`enrich_valuation_bubbles.py v{SCRIPT_VERSION}`。",
@@ -729,15 +729,16 @@
latest_md = resolve_under(project_root, args.latest_md)
fieldnames, rows = read_csv(latest_csv)
source_hash = hashlib.sha256(canonical_base_csv(fieldnames, rows)).hexdigest().upper()
- if len(rows) != 672:
- raise RuntimeError(f"Expected 672 current numeric judgements, got {len(rows)}")
+ if not rows:
+ raise RuntimeError("Current numeric judgement file is empty")
tickers = [row["ticker"] for row in rows]
if len(set(tickers)) != len(tickers):
raise RuntimeError("Duplicate tickers in latest.csv")
trade_dates = {date.fromisoformat(row["trade_date"]) for row in rows}
- if len(trade_dates) != 1:
- raise RuntimeError(f"Expected one trade date, got {sorted(trade_dates)}")
- metrics = market_metrics(tickers, next(iter(trade_dates)), args.skip_market)
+ metrics: dict[str, MarketMetrics] = {}
+ for trade_date in sorted(trade_dates):
+ date_tickers = [row["ticker"] for row in rows if date.fromisoformat(row["trade_date"]) == trade_date]
+ metrics.update(market_metrics(date_tickers, trade_date, args.skip_market))
missing_market = sorted(set(tickers) - set(metrics)) if not args.skip_market else []
enriched: list[dict[str, str]] = []
--
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