Initial fundamental dashboard

.gitignore

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+__pycache__/
+*.pyc
+node_modules/
+logs/
+outputs/
+缓存/
+备份/
+.DS_Store
+Thumbs.db

README.md

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+# 商品期货基本面评分面板
+
+本仓库用于根据本地 Excel 数据生成商品期货基本面评分 HTML 面板。
+
+## 文件说明
+
+- `基本面评分面板.html`：当前已生成的可视化面板，可直接打开查看。
+- `generate_fundamental_dashboard.py`：底层计算与 HTML 生成脚本。
+- `refresh_dashboard_server.py`：本地刷新服务，支持在页面点击“刷新数据”后重新运行生成脚本。
+- `wind数据汇总.xlsx`：Wind 导出的原始数据。
+- `钢联数据汇总.xlsx`：钢联导出的原始数据。
+- `基本面指标确认.xlsx`：各品种各维度使用的指标与公式。
+- `月差拼接数据.xlsx`、`月差/`：月差相关资料。
+
+## 更新数据后重新生成
+
+将新的 Excel 数据覆盖到同名文件后，在仓库根目录运行：
+
+```powershell
+python generate_fundamental_dashboard.py
+```
+
+运行完成后打开 `基本面评分面板.html` 即可查看更新后的面板。
+
+## 使用页面内“刷新数据”按钮
+
+如果希望在浏览器页面中点击“刷新数据”自动重新计算，请先启动本地服务：
+
+```powershell
+python refresh_dashboard_server.py
+```
+
+然后用浏览器打开终端输出的地址，通常是：
+
+```text
+http://127.0.0.1:8765/基本面评分面板.html
+```
+
+通过该地址打开时，页面内“刷新数据”按钮会调用 `generate_fundamental_dashboard.py` 并刷新页面。
+
+## Python 依赖
+
+脚本依赖：
+
+```text
+pandas
+numpy
+openpyxl
+```
+
+如本机缺少依赖，可安装：
+
+```powershell
+pip install pandas numpy openpyxl
+```
+

generate_fundamental_dashboard.py

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+from __future__ import annotations
+
+import html
+import json
+import math
+import re
+from dataclasses import dataclass
+from datetime import datetime
+from pathlib import Path
+from typing import Any
+
+import numpy as np
+import pandas as pd
+
+
+BASE_DIR = Path(__file__).resolve().parent
+CONFIRM_FILE = BASE_DIR / "基本面指标确认.xlsx"
+WIND_FILE = BASE_DIR / "wind数据汇总.xlsx"
+STEEL_FILE = BASE_DIR / "钢联数据汇总.xlsx"
+OUTPUT_FILE = BASE_DIR / "基本面评分面板.html"
+
+DIMENSIONS = ["利润", "产量", "库存", "需求"]
+INVERSE_DIMS = {"库存"}
+DIM_COLORS = {
+    "利润": "#2563eb",
+    "产量": "#dc2626",
+    "库存": "#1d4ed8",
+    "需求": "#0f9f6e",
+    "月差": "#64748b",
+}
+DEFAULT_BAND_WINDOW = 15
+DEFAULT_BAND_K = 3.0
+DEFAULT_BAND_TRIM = 0.10
+HISTORY_START_DEFAULT = "2026-01-01"
+BOARD_MAP = {
+    "黑色": ["焦煤", "焦炭", "铁矿", "螺纹", "热卷", "硅铁", "锰硅", "不锈钢"],
+    "建材": ["玻璃", "纯碱", "PVC", "原木"],
+    "有色": ["沪铜", "沪铝", "沪锌", "沪铅", "沪镍", "沪锡", "氧化铝", "铝合金", "工业硅", "多晶硅", "碳酸锂", "国际铜"],
+    "贵金属": ["沪金", "沪银", "铂", "钯"],
+    "能源": ["原油", "液化气", "燃油", "LU燃油", "沥青", "动力煤", "欧线"],
+    "煤化工": ["尿素", "甲醇"],
+    "油化工": ["塑料", "聚丙烯", "丙烯", "纯苯", "苯乙烯", "对二甲苯", "PTA", "乙二醇", "短纤", "瓶片", "烧碱", "丁二烯"],
+    "农产品": ["玉米", "淀粉", "豆一", "豆二", "豆粕", "豆油", "菜籽油", "菜籽粕", "棕榈油", "鸡蛋", "生猪", "棉花", "白糖", "苹果", "红枣", "花生", "棉纱"],
+    "软商品": ["纸浆", "双胶纸", "橡胶", "20号胶", "BR橡胶"],
+    "金融": ["IF", "IC", "IM", "IH", "二年债", "五年债", "十年债", "三十年债"],
+}
+
+
+@dataclass
+class Metric:
+    name: str
+    source: str
+    unit: str
+    freq: str
+    series: pd.Series
+
+
+def clean_name(value: Any) -> str:
+    if pd.isna(value):
+        return ""
+    text = str(value).strip()
+    text = text.replace("（", "(").replace("）", ")")
+    text = text.replace("；", ";").replace("，", ",")
+    return re.sub(r"\s+", "", text)
+
+
+def read_metrics(path: Path, sheet: str, name_row: int, unit_row: int, freq_row: int, data_row: int, source: str) -> list[Metric]:
+    raw = pd.read_excel(path, sheet_name=sheet, header=None)
+    dates = pd.to_datetime(raw.iloc[data_row:, 0], errors="coerce")
+    metrics: list[Metric] = []
+    for col in range(1, raw.shape[1]):
+        name = clean_name(raw.iat[name_row, col])
+        if not name:
+            continue
+        values = pd.to_numeric(raw.iloc[data_row:, col], errors="coerce")
+        frame = pd.DataFrame({"date": dates, "value": values}).dropna(subset=["date", "value"])
+        if frame.empty:
+            continue
+        series = frame.drop_duplicates("date").set_index("date")["value"].sort_index()
+        if series.empty:
+            continue
+        metrics.append(
+            Metric(
+                name=name,
+                source=source,
+                unit=str(raw.iat[unit_row, col]) if pd.notna(raw.iat[unit_row, col]) else "",
+                freq=str(raw.iat[freq_row, col]) if pd.notna(raw.iat[freq_row, col]) else "",
+                series=series,
+            )
+        )
+    return metrics
+
+
+def build_metric_index(metrics: list[Metric]) -> tuple[dict[str, Metric], list[str]]:
+    grouped: dict[str, list[Metric]] = {}
+    for metric in metrics:
+        grouped.setdefault(metric.name, []).append(metric)
+    selected: dict[str, Metric] = {}
+    for name, items in grouped.items():
+        selected[name] = max(items, key=lambda m: (m.series.index.max(), m.series.notna().sum()))
+    return selected, sorted(selected.keys(), key=len, reverse=True)
+
+
+def normalize_expr(expr: Any) -> str:
+    if pd.isna(expr):
+        return ""
+    text = str(expr).strip()
+    text = text.replace("（", "(").replace("）", ")")
+    text = text.replace("；", ";").replace("，", ",")
+    text = re.sub(r"\s+", "", text)
+    text = re.sub(r"(?i)\bSum\s*\(", "(", text)
+    text = text.replace(";", "+")
+    return text
+
+
+def parse_expression(expr: Any, metric_index: dict[str, Metric], metric_names: list[str]) -> tuple[str, dict[str, Metric], list[str]]:
+    text = normalize_expr(expr)
+    if not text:
+        return "", {}, []
+    used: dict[str, Metric] = {}
+    token_expr = text
+    for idx, name in enumerate(metric_names):
+        if name and name in token_expr:
+            token = f"m{idx}"
+            token_expr = token_expr.replace(name, token)
+            used[token] = metric_index[name]
+    leftovers = re.sub(r"m\d+", " ", token_expr)
+    leftovers = re.sub(r"[0-9eE\.\+\-\*/\(\)\s,]+", " ", leftovers)
+    missing = [x.strip() for x in re.split(r"\s+", leftovers) if x.strip()]
+    return token_expr, used, missing
+
+
+def eval_expression(expr: Any, metric_index: dict[str, Metric], metric_names: list[str]) -> tuple[pd.Series | None, list[str], list[Metric]]:
+    token_expr, used, missing = parse_expression(expr, metric_index, metric_names)
+    if not token_expr or not used:
+        return None, missing, []
+    local_env = {token: metric.series for token, metric in used.items()}
+    try:
+        value = eval(token_expr, {"__builtins__": {}}, local_env)
+    except Exception:
+        return None, missing or [token_expr], list(used.values())
+    if isinstance(value, (int, float, np.number)):
+        return None, missing, list(used.values())
+    series = pd.to_numeric(value, errors="coerce").dropna().sort_index()
+    return (series if not series.empty else None), missing, list(used.values())
+
+
+def circular_day_diff(day_values: np.ndarray, target_day: int) -> np.ndarray:
+    diff = np.abs(day_values - target_day)
+    return np.minimum(diff, 366 - diff)
+
+
+def trimmed_values(values: pd.Series, trim: float = DEFAULT_BAND_TRIM) -> pd.Series:
+    values = pd.to_numeric(values, errors="coerce").dropna().sort_values()
+    if values.empty or trim <= 0:
+        return values
+    cut = int(len(values) * trim)
+    if len(values) - cut * 2 < 4:
+        return values
+    return values.iloc[cut : len(values) - cut]
+
+
+def seasonal_band_sample(history: pd.Series, day: int, window: int = DEFAULT_BAND_WINDOW) -> tuple[pd.Series, int]:
+    history = pd.to_numeric(history, errors="coerce").dropna().sort_index()
+    if history.empty:
+        return history, window
+    days = history.index.dayofyear.to_numpy()
+    sample = history[circular_day_diff(days, day) <= window]
+    used_window = window
+    if len(sample) < 8:
+        sample = history[circular_day_diff(days, day) <= 30]
+        used_window = 30
+    if len(sample) < 8:
+        sample = history
+        used_window = 366
+    return sample, used_window
+
+
+def band_score(latest_value: float, history: pd.Series, day: int, inverse: bool = False) -> dict[str, Any] | None:
+    sample, used_window = seasonal_band_sample(history, day)
+    sample = trimmed_values(sample)
+    if len(sample) < 4:
+        return None
+    mean = float(sample.mean())
+    std = float(sample.std(ddof=0))
+    if not math.isfinite(std):
+        std = 0.0
+    low = mean - DEFAULT_BAND_K * std
+    high = mean + DEFAULT_BAND_K * std
+    if not math.isfinite(low) or not math.isfinite(high):
+        return None
+    if high == low:
+        raw_score = 100.0 if latest_value >= high else 0.0
+    elif latest_value >= high:
+        raw_score = 100.0
+    elif latest_value <= low:
+        raw_score = 0.0
+    else:
+        raw_score = 100.0 * (latest_value - low) / (high - low)
+    score = 100.0 - raw_score if inverse else raw_score
+    return {
+        "score": max(0.0, min(100.0, score)),
+        "band_low": low,
+        "band_high": high,
+        "band_mean": mean,
+        "band_window": used_window,
+        "band_k": DEFAULT_BAND_K,
+        "band_trim": DEFAULT_BAND_TRIM,
+    }
+
+
+def seasonal_percentile(series: pd.Series) -> dict[str, Any] | None:
+    series = pd.to_numeric(series, errors="coerce").dropna().sort_index()
+    if series.empty:
+        return None
+    latest_date = series.index.max()
+    latest_value = float(series.loc[latest_date])
+    history = series[series.index < latest_date].dropna()
+    if history.empty:
+        return None
+    day = int(latest_date.dayofyear)
+    day_diff = np.abs(history.index.dayofyear - day)
+    sample = history[day_diff <= 15]
+    window = 15
+    if len(sample) < 8:
+        sample = history[day_diff <= 30]
+        window = 30
+    if len(sample) < 8:
+        sample = history
+        window = 366
+    less = float((sample < latest_value).sum())
+    equal = float((sample == latest_value).sum())
+    raw_pct = 100.0 * (less + 0.5 * equal) / len(sample)
+    latest_year = int(latest_date.year)
+    yearly: dict[str, list[tuple[str, float]]] = {}
+    clipped = series[series.index.year >= latest_year - 8]
+    for dt, val in clipped.items():
+        yearly.setdefault(str(int(dt.year)), []).append((dt.strftime("%m-%d"), float(val)))
+    return {
+        "latest_date": latest_date.strftime("%Y-%m-%d"),
+        "latest_value": latest_value,
+        "raw_percentile": round(raw_pct, 1),
+        "sample_size": int(len(sample)),
+        "window": window,
+        "years": yearly,
+        "chart_transform": "linear_z_score_in_browser",
+    }
+
+
+def commodity_boards(name: str) -> list[str]:
+    boards = [board for board, names in BOARD_MAP.items() if name in names]
+    return boards or ["其他"]
+
+
+def score_series_at(series: pd.Series, date: pd.Timestamp, inverse: bool = False) -> float | None:
+    series = pd.to_numeric(series, errors="coerce").dropna().sort_index()
+    available = series[series.index <= date]
+    if available.empty:
+        return None
+    value_date = available.index.max()
+    value = float(available.loc[value_date])
+    history = series[series.index < value_date].dropna()
+    if history.empty:
+        return None
+    band = band_score(value, history, int(value_date.dayofyear), inverse)
+    if band:
+        return float(band["score"])
+    sample, _ = seasonal_band_sample(history, int(value_date.dayofyear))
+    if sample.empty:
+        return None
+    less = float((sample < value).sum())
+    equal = float((sample == value).sum())
+    raw = 100.0 * (less + 0.5 * equal) / len(sample)
+    return 100.0 - raw if inverse else raw
+
+
+def build_score_history(dim_series: dict[str, pd.Series]) -> list[dict[str, Any]]:
+    available = [s.dropna().sort_index() for s in dim_series.values() if s is not None and not s.dropna().empty]
+    if not available:
+        return []
+    latest = max(s.index.max() for s in available)
+    start = pd.Timestamp(HISTORY_START_DEFAULT)
+    if latest < start:
+        start = min(s.index.min() for s in available)
+    dates = pd.date_range(start=start, end=latest, freq="D")
+    history: list[dict[str, Any]] = []
+    for date in dates:
+        scores: dict[str, float] = {}
+        for dim, series in dim_series.items():
+            score = score_series_at(series, date, dim in INVERSE_DIMS)
+            if score is not None and math.isfinite(score):
+                scores[dim] = score
+        if not scores:
+            continue
+        dims_with_demand = [d for d in DIMENSIONS if d in scores]
+        dims_without_demand = [d for d in DIMENSIONS if d != "需求" and d in scores]
+        total = float(np.mean([scores[d] for d in dims_with_demand])) if dims_with_demand else None
+        total_no_demand = float(np.mean([scores[d] for d in dims_without_demand])) if dims_without_demand else None
+        history.append(
+            {
+                "date": date.strftime("%Y-%m-%d"),
+                "total": round(total, 1) if total is not None else None,
+                "totalNoDemand": round(total_no_demand, 1) if total_no_demand is not None else None,
+            }
+        )
+    return history
+
+
+def make_records() -> dict[str, Any]:
+    metrics = []
+    metrics.extend(read_metrics(WIND_FILE, "wind", 1, 3, 2, 8, "Wind"))
+    metrics.extend(read_metrics(STEEL_FILE, "钢联", 1, 2, 5, 10, "钢联"))
+    metric_index, metric_names = build_metric_index(metrics)
+    confirm = pd.read_excel(CONFIRM_FILE).fillna("")
+    commodities: list[dict[str, Any]] = []
+    for idx, row in confirm.iterrows():
+        name = str(row["品种"]).strip()
+        if not name:
+            continue
+        dims: dict[str, Any] = {}
+        dim_series: dict[str, pd.Series] = {}
+        valid_scores: list[float] = []
+        for dim in DIMENSIONS:
+            series, missing, used_metrics = eval_expression(row.get(dim, ""), metric_index, metric_names)
+            if series is not None:
+                dim_series[dim] = series
+            stat = seasonal_percentile(series) if series is not None else None
+            if stat:
+                latest_dt = pd.Timestamp(stat["latest_date"])
+                history = series[series.index < latest_dt].dropna()
+                band = band_score(stat["latest_value"], history, int(latest_dt.dayofyear), dim in INVERSE_DIMS)
+                if band:
+                    score = band["score"]
+                    stat.update(band)
+                else:
+                    raw = stat["raw_percentile"]
+                    score = 100.0 - raw if dim in INVERSE_DIMS else raw
+                stat["score"] = round(score, 1)
+                stat["direction"] = "低库存更优，按正常区间反向计分" if dim in INVERSE_DIMS else "高于正常区间更优"
+                stat["expr"] = str(row.get(dim, "")).strip()
+                stat["metrics"] = [
+                    {"name": m.name, "source": m.source, "unit": m.unit, "freq": m.freq}
+                    for m in used_metrics
+                ]
+                valid_scores.append(float(score))
+            dims[dim] = stat or {
+                "score": None,
+                "raw_percentile": None,
+                "direction": "缺数据",
+                "expr": str(row.get(dim, "")).strip(),
+                "missing": missing,
+                "metrics": [{"name": m.name, "source": m.source, "unit": m.unit, "freq": m.freq} for m in used_metrics],
+            }
+        total = round(float(np.mean(valid_scores)), 1) if valid_scores else None
+        boards = commodity_boards(name)
+        commodities.append(
+            {
+                "rank": None,
+                "name": name,
+                "board": " / ".join(boards),
+                "boards": boards,
+                "total": total,
+                "valid_count": len(valid_scores),
+                "dims": dims,
+                "scoreHistory": build_score_history(dim_series),
+            }
+        )
+    ranked = sorted([c for c in commodities if c["total"] is not None], key=lambda x: x["total"], reverse=True)
+    for i, item in enumerate(ranked, 1):
+        item["rank"] = i
+    no_score = [c for c in commodities if c["total"] is None]
+    commodities = ranked + no_score
+    return {
+        "generated_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        "source_files": {
+            "wind": WIND_FILE.name,
+            "steel": STEEL_FILE.name,
+            "confirm": CONFIRM_FILE.name,
+        },
+        "dimensions": DIMENSIONS + ["月差"],
+        "boards": sorted(set(board for c in commodities for board in c.get("boards", [c["board"]]))),
+        "commodities": commodities,
+    }
+
+
+def html_template(data: dict[str, Any]) -> str:
+    payload = json.dumps(data, ensure_ascii=False, allow_nan=False)
+    return f"""<!doctype html>
+<html lang="zh-CN">
+<head>
+<meta charset="utf-8">
+<meta name="viewport" content="width=device-width, initial-scale=1">
+<title>NO.5 可更新数据 - 基本面评分面板</title>
+<style>
+:root {{
+  --yellow:#fff200; --blue:#1d4ed8; --red:#dc2626; --green:#059669;
+  --line:#d8dee8; --text:#172033; --muted:#667085; --bg:#f5f7fb;
+}}
+* {{ box-sizing: border-box; }}
+body {{ margin:0; font-family: "Microsoft YaHei", Arial, sans-serif; color:var(--text); background:var(--bg); }}
+.topbar {{ position:sticky; top:0; z-index:10; display:flex; align-items:center; gap:12px; padding:7px 14px; background:var(--yellow); border-bottom:1px solid #d4c900; box-shadow:0 1px 4px rgba(0,0,0,.12); }}
+.brand {{ font-weight:800; margin-right:auto; }}
+.ctrl {{ display:flex; align-items:center; gap:6px; font-size:14px; white-space:nowrap; }}
+input, select, button {{ height:32px; border:1px solid #b9c3d4; border-radius:4px; background:white; padding:0 10px; font-size:14px; }}
+input {{ width:340px; }}
+input.mini {{ width:64px; }}
+input[type="checkbox"] {{ width:16px; height:16px; padding:0; }}
+button {{ cursor:pointer; font-weight:700; color:#475467; }}
+.tabbtn.active {{ color:#1d4ed8; border-color:#1d4ed8; }}
+.stamp {{ margin-left:auto; font-size:13px; white-space:nowrap; }}
+.summary {{ display:grid; grid-template-columns:280px 1fr 1fr; gap:12px; padding:12px 14px 4px; }}
+.card {{ background:white; border:1px solid var(--line); border-radius:7px; padding:12px; box-shadow:0 1px 5px rgba(16,24,40,.05); }}
+.kpi-title {{ font-weight:800; color:#344054; margin-bottom:5px; }}
+.kpi-number {{ font-size:42px; line-height:1; font-weight:900; color:#111827; }}
+.hint {{ color:var(--muted); font-size:12px; line-height:1.55; }}
+.chips {{ display:flex; gap:6px; flex-wrap:wrap; margin-top:8px; }}
+.chip {{ border:1px solid #4c84ff; color:#1d4ed8; border-radius:4px; padding:6px 8px; min-width:160px; display:flex; justify-content:space-between; font-size:13px; font-weight:700; background:#f8fbff; }}
+.chip.red {{ border-color:#ef4444; color:#dc2626; background:#fffafa; }}
+.chip.good {{ border-color:#22c55e; color:#047857; background:#f6fffa; }}
+.note {{ padding:4px 14px 10px; color:#64748b; font-size:12px; }}
+.rows {{ margin:0 14px 24px; background:white; border:1px solid var(--line); }}
+.history-view {{ display:none; margin:0 14px 24px; background:white; border:1px solid var(--line); padding:12px; }}
+.history-view.active {{ display:block; }}
+.history-tools {{ display:flex; align-items:center; gap:10px; flex-wrap:wrap; margin-bottom:8px; }}
+.history-tools input {{ width:150px; }}
+.history-legend {{ display:flex; flex-wrap:wrap; gap:5px 10px; max-height:92px; overflow:auto; padding:6px 0 8px; border-top:1px solid var(--line); }}
+.history-legend-item {{ display:inline-flex; align-items:center; gap:4px; min-width:70px; font-size:12px; color:#475467; cursor:pointer; user-select:none; }}
+.history-legend-item::before {{ content:""; width:18px; height:2px; background:var(--c); display:inline-block; }}
+.history-legend-item.active {{ font-weight:900; color:#111827; }}
+.history-chart-wrap {{ position:relative; border-top:1px solid var(--line); }}
+#historySvg {{ height:620px; }}
+.history-line {{ cursor:pointer; transition:opacity .12s ease, stroke-width .12s ease; }}
+.history-tooltip {{ position:absolute; display:none; min-width:260px; max-width:760px; padding:8px 10px; border:1px solid #cfd6e0; border-radius:6px; background:rgba(255,255,255,.96); box-shadow:0 8px 22px rgba(15,23,42,.15); font-size:12px; color:#344054; pointer-events:none; z-index:3; }}
+.history-tooltip .date {{ font-weight:900; color:#111827; margin-bottom:5px; }}
+.history-tooltip .grid {{ display:grid; grid-template-columns:repeat(3, minmax(150px, 1fr)); gap:1px 12px; }}
+.history-tooltip .row {{ display:flex; justify-content:space-between; gap:12px; line-height:1.45; white-space:nowrap; }}
+.history-tooltip .name {{ color:var(--c); font-weight:700; }}
+.commodity {{ display:grid; grid-template-columns:48px minmax(0,1fr); border-top:1px solid var(--line); }}
+.commodity:first-child {{ border-top:0; }}
+.side {{ display:flex; align-items:center; justify-content:center; writing-mode:vertical-rl; font-weight:900; color:#12356b; background:#fbfdff; border-right:1px solid var(--line); letter-spacing:2px; }}
+.body {{ min-width:0; }}
+.scoreline {{ display:grid; grid-template-columns:160px repeat(5, minmax(130px, 1fr)); align-items:stretch; gap:8px; padding:8px 10px; border-bottom:1px solid var(--line); background:#fbfcff; }}
+.total {{ display:flex; align-items:center; gap:8px; font-weight:900; color:var(--blue); white-space:nowrap; }}
+.total .num {{ font-size:28px; }}
+.dimbox {{ background:white; border-left:4px solid var(--blue); padding:5px 8px; min-height:42px; }}
+.dimbox.bad {{ opacity:.65; border-left-color:#94a3b8; }}
+.dimname {{ font-size:13px; color:#475467; font-weight:800; display:flex; justify-content:space-between; }}
+.dimscore {{ font-size:13px; font-weight:900; color:#1d4ed8; }}
+.dimhint {{ font-size:12px; color:#667085; white-space:nowrap; overflow:hidden; text-overflow:ellipsis; }}
+.detail {{ padding:0 10px 8px; color:#667085; font-size:12px; }}
+.charts {{ display:grid; grid-template-columns:repeat(4, minmax(260px,1fr)); }}
+.chartcell {{ min-width:0; border-top:1px solid var(--line); border-right:1px solid var(--line); padding:8px 10px 10px; }}
+.chartcell:nth-child(4n) {{ border-right:0; }}
+.chart-title {{ text-align:center; font-size:18px; color:#475467; margin:2px 0 4px; }}
+.metric-title {{ color:#667085; font-size:12px; min-height:32px; line-height:1.35; overflow:hidden; display:-webkit-box; -webkit-line-clamp:2; -webkit-box-orient:vertical; }}
+svg {{ width:100%; height:230px; display:block; }}
+.axis {{ stroke:#cfd6e0; stroke-width:1; }}
+.grid {{ stroke:#e5e7eb; stroke-width:1; }}
+.legend {{ display:flex; flex-wrap:wrap; justify-content:center; gap:8px; min-height:21px; font-size:12px; color:#475467; }}
+.legend span::before {{ content:""; display:inline-block; width:18px; height:2px; margin-right:4px; vertical-align:middle; background:var(--c); }}
+.empty {{ padding:24px; text-align:center; color:#667085; }}
+@media (max-width: 1200px) {{
+  .summary {{ grid-template-columns:1fr; }}
+  .scoreline {{ grid-template-columns:1fr 1fr 1fr; }}
+  .charts {{ grid-template-columns:1fr 1fr; }}
+  input {{ width:220px; }}
+}}
+@media (max-width: 760px) {{
+  .topbar {{ flex-wrap:wrap; }}
+  .stamp {{ margin-left:0; }}
+  .scoreline {{ grid-template-columns:1fr; }}
+  .charts {{ grid-template-columns:1fr; }}
+  .commodity {{ grid-template-columns:34px minmax(0,1fr); }}
+}}
+</style>
+</head>
+<body>
+<div class="topbar">
+  <div class="brand">NO.5 可更新数据</div>
+  <label class="ctrl">品种 <input id="search" placeholder="搜索品种或指标"></label>
+  <label class="ctrl">维度 <select id="dim"><option>全部</option></select></label>
+  <label class="ctrl">板块 <select id="board"><option>全部</option></select></label>
+  <label class="ctrl">窗口 <input class="mini" id="bandWindow" type="number" min="3" max="90" step="1" value="15"></label>
+  <label class="ctrl">倍数 <input class="mini" id="bandK" type="number" min="0.5" max="6" step="0.5" value="3"></label>
+  <label class="ctrl">去尾 <input class="mini" id="bandTrim" type="number" min="0" max="40" step="5" value="10"></label>
+  <label class="ctrl"><input id="includeDemand" type="checkbox" checked>需求计分</label>
+  <button class="tabbtn active" id="dashboardTab">面板</button>
+  <button class="tabbtn" id="historyTab">评分走势</button>
+  <button id="refreshData">刷新数据</button>
+  <button id="reset">重置</button>
+  <div class="stamp">核心修正：库存反向计分　生成时间：<span id="generated"></span></div>
+</div>
+<section class="summary">
+  <div class="card">
+    <div class="kpi-title">基本面总分</div>
+    <div class="kpi-number" id="avgScore">--</div>
+    <div class="hint" id="coverage">当前筛选覆盖 -- 个有可用数据的品种；月差当前暂无映射，未计入总分。</div>
+  </div>
+  <div class="card">
+    <div class="kpi-title">基本面较强</div>
+    <div class="chips" id="strong"></div>
+  </div>
+  <div class="card">
+    <div class="kpi-title">基本面较弱</div>
+    <div class="chips" id="weak"></div>
+  </div>
+</section>
+<div class="note">维度得分按同期正常波动区间计算：正向指标高于上沿为 100，低于下沿为 0，区间内线性映射；库存反向。阴影带参数只影响图表展示，总分使用默认 ±15 天、3 倍标准差、去尾 10%。</div>
+<main class="rows" id="rows"></main>
+<section class="history-view" id="historyView">
+  <div class="history-tools">
+    <strong>各品种基本面得分变化</strong>
+    <label class="ctrl">开始 <input id="historyStart" type="date" value="2026-01-01"></label>
+    <label class="ctrl">结束 <input id="historyEnd" type="date"></label>
+  </div>
+  <div class="history-legend" id="historyLegend"></div>
+  <div class="history-chart-wrap" id="historyChartWrap">
+    <svg id="historySvg" viewBox="0 0 1600 620" preserveAspectRatio="none"></svg>
+    <div class="history-tooltip" id="historyTooltip"></div>
+  </div>
+</section>
+<script>
+const DATA = {payload};
+const OLDER_COLORS = ["#1976d2","#65a30d","#a21caf","#9ca3af","#0f9f9f","#374151","#7c3aed"];
+function yearColor(year, years) {{
+  const ordered = Object.keys(years).map(Number).sort((a,b)=>b-a);
+  const rank = ordered.indexOf(Number(year));
+  if (rank === 0) return "#ef4444";
+  if (rank === 1) return "#f97316";
+  return OLDER_COLORS[(rank - 2 + OLDER_COLORS.length) % OLDER_COLORS.length];
+}}
+const dimColors = {json.dumps(DIM_COLORS, ensure_ascii=False)};
+const dims = DATA.dimensions;
+const search = document.getElementById("search");
+const dimSel = document.getElementById("dim");
+const boardSel = document.getElementById("board");
+const bandWindow = document.getElementById("bandWindow");
+const bandK = document.getElementById("bandK");
+const bandTrim = document.getElementById("bandTrim");
+const includeDemand = document.getElementById("includeDemand");
+const dashboardTab = document.getElementById("dashboardTab");
+const historyTab = document.getElementById("historyTab");
+const rowsEl = document.getElementById("rows");
+const historyView = document.getElementById("historyView");
+const historyStart = document.getElementById("historyStart");
+const historyEnd = document.getElementById("historyEnd");
+const historyLegend = document.getElementById("historyLegend");
+const historyTooltip = document.getElementById("historyTooltip");
+const historyChartWrap = document.getElementById("historyChartWrap");
+const refreshData = document.getElementById("refreshData");
+for (const d of dims) dimSel.append(new Option(d, d));
+for (const b of DATA.boards) boardSel.append(new Option(b, b));
+document.getElementById("generated").textContent = DATA.generated_at;
+function todayString() {{
+  const d = new Date();
+  return `${{d.getFullYear()}}-${{String(d.getMonth()+1).padStart(2,"0")}}-${{String(d.getDate()).padStart(2,"0")}}`;
+}}
+function majorityHistoryEndDate() {{
+  const counts = new Map();
+  for (const c of DATA.commodities) {{
+    const last = (c.scoreHistory || []).map(p => p.date).sort().at(-1);
+    if (last) counts.set(last, (counts.get(last) || 0) + 1);
+  }}
+  let best = "", bestCount = -1;
+  for (const [date, count] of counts) {{
+    if (count > bestCount || (count === bestCount && date > best)) {{
+      best = date; bestCount = count;
+    }}
+  }}
+  return best || todayString();
+}}
+historyEnd.value = majorityHistoryEndDate();
+let activeView = "dashboard";
+document.getElementById("reset").onclick = () => {{ search.value=""; dimSel.value="全部"; boardSel.value="全部"; bandWindow.value="15"; bandK.value="3"; bandTrim.value="10"; includeDemand.checked=true; historyStart.value="2026-01-01"; historyEnd.value = majorityHistoryEndDate(); render(); }};
+dashboardTab.onclick = () => {{ activeView="dashboard"; dashboardTab.classList.add("active"); historyTab.classList.remove("active"); render(); }};
+historyTab.onclick = () => {{ activeView="history"; historyTab.classList.add("active"); dashboardTab.classList.remove("active"); render(); }};
+refreshData.onclick = refreshFromLocalProgram;
+search.oninput = dimSel.onchange = boardSel.onchange = bandWindow.oninput = bandK.oninput = bandTrim.oninput = includeDemand.onchange = historyStart.onchange = historyEnd.onchange = render;
+
+function fmt(v, n=1) {{ return v == null || Number.isNaN(v) ? "--" : Number(v).toFixed(n); }}
+function matches(c) {{
+  const q = search.value.trim().toLowerCase();
+  const dim = dimSel.value;
+  const board = boardSel.value;
+  if (board !== "全部" && !(c.boards || [c.board]).includes(board)) return false;
+  if (dim !== "全部" && dim !== "月差" && !c.dims[dim]?.score && c.dims[dim]?.score !== 0) return false;
+  if (!q) return true;
+  const hay = [c.name, c.board, ...Object.values(c.dims).map(d => [d.expr, ...(d.metrics||[]).map(m=>m.name)].join(" "))].join(" ").toLowerCase();
+  return hay.includes(q);
+}}
+function activeDims() {{ return includeDemand.checked ? ["利润","产量","库存","需求"] : ["利润","产量","库存"]; }}
+function computeTotal(c) {{
+  const keys = activeDims();
+  const values = keys.map(d => c.dims[d]?.score).filter(v => v != null && Number.isFinite(Number(v))).map(Number);
+  return {{total: values.length ? values.reduce((s,v)=>s+v,0)/values.length : null, valid: values.length, denom: keys.length}};
+}}
+function rankedList(list) {{
+  const mapped = list.map(c => Object.assign({{}}, c, computeTotal(c)));
+  const scored = mapped.filter(c => c.total != null).sort((a,b)=>b.total-a.total);
+  scored.forEach((c,i)=>c.displayRank=i+1);
+  return scored.concat(mapped.filter(c => c.total == null));
+}}
+function topChips(list, reverse=false) {{
+  return list.slice().sort((a,b)=> reverse ? a.total-b.total : b.total-a.total).slice(0,6).map(c => `<div class="chip ${{reverse?"red":"good"}}"><span>${{c.displayRank||"-"}}. ${{esc(c.name)}}</span><span>${{fmt(c.total)}}</span></div>`).join("");
+}}
+function esc(s) {{ return String(s ?? "").replace(/[&<>"']/g, m => ({{"&":"&amp;","<":"&lt;",">":"&gt;",'"':"&quot;","'":"&#39;"}}[m])); }}
+function render() {{
+  const list = rankedList(DATA.commodities.filter(matches));
+  const scored = list.filter(c => c.total != null);
+  document.getElementById("avgScore").textContent = scored.length ? fmt(scored.reduce((s,c)=>s+c.total,0)/scored.length) : "--";
+  document.getElementById("coverage").textContent = `当前筛选覆盖 ${{scored.length}} 个有可用数据的品种；${{includeDemand.checked ? "需求参与总分" : "需求不参与总分"}}；月差当前暂无映射。`;
+  document.getElementById("strong").innerHTML = topChips(scored, false) || `<span class="hint">暂无可用数据</span>`;
+  document.getElementById("weak").innerHTML = topChips(scored, true) || `<span class="hint">暂无可用数据</span>`;
+  rowsEl.style.display = activeView === "dashboard" ? "block" : "none";
+  historyView.classList.toggle("active", activeView === "history");
+  rowsEl.innerHTML = list.length ? list.map(renderCommodity).join("") : `<div class="empty">没有匹配的品种</div>`;
+  for (const cell of document.querySelectorAll("[data-chart]")) {{
+    try {{
+      drawChart(cell, JSON.parse(cell.dataset.chart));
+    }} catch (err) {{
+      cell.innerHTML = `<text x="260" y="115" text-anchor="middle" font-size="14" fill="#667085">绘图参数异常</text>`;
+    }}
+  }}
+  if (activeView === "history") drawHistoryChart(list.filter(c => c.total != null));
+}}
+function renderCommodity(c) {{
+  const dimCards = [...Object.entries(c.dims).map(([d,v]) => renderDim(d,v)), renderMonthSpread()].join("");
+  const chartDims = dimSel.value === "全部" || dimSel.value === "月差" ? ["利润","产量","库存","需求"] : [dimSel.value];
+  const charts = chartDims.filter(d => d !== "月差").map(d => renderChartCell(c, d, c.dims[d])).join("");
+  return `<section class="commodity">
+    <div class="side">${{esc(c.name)}}</div>
+    <div class="body">
+      <div class="scoreline"><div class="total"><span>#${{c.displayRank||"-"}}</span><span class="num">${{fmt(c.total)}}</span><span>总分</span></div>${{dimCards}}</div>
+      <div class="detail">季节性口径：最新值相对同期正常区间；库存反向，其余正向。有效维度：${{c.valid}}/${{c.denom}}　板块：${{esc(c.board)}}</div>
+      <div class="charts">${{charts}}</div>
+    </div>
+  </section>`;
+}}
+function renderDim(dim, v) {{
+  const color = dimColors[dim] || "#64748b";
+  const ok = v && v.score != null;
+  return `<div class="dimbox ${{ok?"":"bad"}}" style="border-left-color:${{color}}">
+    <div class="dimname"><span>${{esc(dim)}}</span><span class="dimscore" style="color:${{color}}">${{fmt(v?.score)}}</span></div>
+    <div class="dimhint">${{esc(ok ? v.direction : "缺数据/未配置")}}</div>
+  </div>`;
+}}
+function renderMonthSpread() {{
+  return `<div class="dimbox bad" style="border-left-color:#94a3b8"><div class="dimname"><span>月差</span><span class="dimscore">--</span></div><div class="dimhint">未配置</div></div>`;
+}}
+function renderChartCell(c, dim, v) {{
+  const title = `${{esc(c.name)}}${{esc(dim)}}`;
+  if (!v || !v.years) return `<div class="chartcell"><div class="chart-title">${{title}}</div><div class="metric-title">${{esc(v?.expr || "未配置")}}</div><div class="empty">缺少可绘制数据</div></div>`;
+  return `<div class="chartcell">
+    <div class="chart-title">${{title}}</div>
+    <div class="metric-title">${{esc(v.expr)}}</div>
+    <div class="legend">${{Object.keys(v.years).map(y=>`<span style="--c:${{yearColor(y, v.years)}}">${{y}}</span>`).join("")}}</div>
+    <svg data-chart='${{esc(JSON.stringify(v.years))}}' viewBox="0 0 520 230" preserveAspectRatio="none"></svg>
+  </div>`;
+}}
+function parseDay(md) {{
+  const [m,d] = md.split("-").map(Number);
+  const date = new Date(2024, m-1, d);
+  const start = new Date(2024,0,1);
+  return Math.round((date-start)/86400000)+1;
+}}
+function chartParams() {{
+  return {{
+    window: Math.max(3, Math.min(90, Number(bandWindow.value) || 15)),
+    k: Math.max(0.5, Math.min(6, Number(bandK.value) || 3)),
+    trim: Math.max(0, Math.min(40, Number(bandTrim.value) || 0)) / 100,
+  }};
+}}
+function mean(arr) {{ return arr.reduce((s,v)=>s+v,0) / arr.length; }}
+function std(arr) {{
+  if (!arr.length) return 0;
+  const m = mean(arr);
+  return Math.sqrt(arr.reduce((s,v)=>s+(v-m)*(v-m),0) / arr.length);
+}}
+function circularDiff(a, b) {{
+  const d = Math.abs(a - b);
+  return Math.min(d, 366 - d);
+}}
+function trimmed(arr, trim) {{
+  const sorted = arr.filter(Number.isFinite).sort((a,b)=>a-b);
+  if (!sorted.length || trim <= 0) return sorted;
+  const cut = Math.floor(sorted.length * trim);
+  if (sorted.length - cut * 2 < 4) return sorted;
+  return sorted.slice(cut, sorted.length - cut);
+}}
+function smoothBand(band, radius) {{
+  if (!band.length || radius <= 0) return band;
+  const n = band.length;
+  radius = Math.min(radius, Math.max(0, Math.floor((n - 1) / 2)));
+  if (radius <= 0) return band;
+  const smoothed = band.map((p, i) => {{
+    let low = 0, high = 0, mid = 0, wsum = 0;
+    for (let offset = -radius; offset <= radius; offset++) {{
+      const idx = ((i + offset) % n + n) % n;
+      const weight = radius + 1 - Math.abs(offset);
+      low += band[idx][1] * weight;
+      high += band[idx][2] * weight;
+      mid += band[idx][3] * weight;
+      wsum += weight;
+    }}
+    low /= wsum; high /= wsum; mid /= wsum;
+    if (low > high) {{
+      const tmp = low; low = high; high = tmp;
+    }}
+    mid = Math.max(low, Math.min(high, mid));
+    return [p[0], low, high, mid];
+  }});
+  return smoothed;
+}}
+function buildNormalizedChart(years) {{
+  const params = chartParams();
+  const rawPoints = [];
+  Object.entries(years).forEach(([year, pts]) => {{
+    pts.forEach(p => {{
+      const value = Number(p[1]);
+      if (Number.isFinite(value)) rawPoints.push({{year, md:p[0], day:parseDay(p[0]), value}});
+    }});
+  }});
+  const rawValues = rawPoints.map(p=>p.value);
+  if (!rawValues.length) return {{years:{{}}, band:[]}};
+  const m = mean(rawValues);
+  let s = std(rawValues);
+  if (!Number.isFinite(s) || s === 0) s = 1;
+  const z = v => (v - m) / s;
+  const normYears = {{}};
+  Object.entries(years).forEach(([year, pts]) => {{
+    normYears[year] = pts.map(p => [p[0], z(Number(p[1]))]).filter(p => Number.isFinite(p[1]));
+  }});
+  const band = [];
+  for (let day=1; day<=366; day++) {{
+    const samples = trimmed(rawPoints.filter(p => circularDiff(p.day, day) <= params.window).map(p=>p.value), params.trim);
+    if (samples.length < 4) continue;
+    const bm = mean(samples);
+    const bs = std(samples);
+    const date = new Date(2024, 0, day);
+    const md = `${{String(date.getMonth()+1).padStart(2,"0")}}-${{String(date.getDate()).padStart(2,"0")}}`;
+    band.push([md, z(bm - params.k * bs), z(bm + params.k * bs), z(bm)]);
+  }}
+  const smoothRadius = Math.max(3, Math.min(18, Math.round(params.window * 0.75)));
+  return {{years:normYears, band:smoothBand(band, smoothRadius)}};
+}}
+function drawChart(svg, years) {{
+  const normalized = buildNormalizedChart(years);
+  years = normalized.years;
+  const band = normalized.band;
+  const W=520,H=230,L=44,R=8,T=16,B=30;
+  const bandValues = band.flatMap(p => [p[1], p[2]]).filter(Number.isFinite);
+  const values = Object.values(years).flat().map(p=>p[1]).filter(Number.isFinite).concat(bandValues);
+  if (!values.length) return;
+  let min=Math.min(...values), max=Math.max(...values);
+  if (min===max) {{ min-=1; max+=1; }}
+  const pad=(max-min)*0.12; min-=pad; max+=pad;
+  const x=d=> L + (parseDay(d)-1)/365*(W-L-R);
+  const y=v=> T + (max-v)/(max-min)*(H-T-B);
+  let out = "";
+  for (let i=0;i<=4;i++) {{
+    const yy=T+i*(H-T-B)/4, val=max-i*(max-min)/4;
+    out += `<line class="grid" x1="${{L}}" y1="${{yy}}" x2="${{W-R}}" y2="${{yy}}"></line><text x="4" y="${{yy+4}}" font-size="12" fill="#667085">${{val.toFixed(1)}}</text>`;
+  }}
+  for (const [label, day] of [["1/1",1],["4/1",92],["7/1",183],["10/1",275]]) {{
+    const xx=L+(day-1)/365*(W-L-R);
+    out += `<line class="grid" x1="${{xx}}" y1="${{T}}" x2="${{xx}}" y2="${{H-B}}"></line><text x="${{xx-10}}" y="${{H-9}}" font-size="12" fill="#667085">${{label}}</text>`;
+  }}
+  out += `<line class="axis" x1="${{L}}" y1="${{H-B}}" x2="${{W-R}}" y2="${{H-B}}"></line><line class="axis" x1="${{L}}" y1="${{T}}" x2="${{L}}" y2="${{H-B}}"></line>`;
+  if (band.length) {{
+    const sortedBand = band.slice().sort((a,b)=>parseDay(a[0])-parseDay(b[0]));
+    const upper = sortedBand.map((p,j)=>`${{j?'L':'M'}}${{x(p[0]).toFixed(1)}},${{y(p[2]).toFixed(1)}}`).join(" ");
+    const lower = sortedBand.slice().reverse().map(p=>`L${{x(p[0]).toFixed(1)}},${{y(p[1]).toFixed(1)}}`).join(" ");
+    out += `<path d="${{upper}} ${{lower}} Z" fill="#94a3b8" opacity="0.18"></path>`;
+    const mid = sortedBand.map((p,j)=>`${{j?'L':'M'}}${{x(p[0]).toFixed(1)}},${{y(p[3]).toFixed(1)}}`).join(" ");
+    out += `<path d="${{mid}}" fill="none" stroke="#94a3b8" stroke-width="1.2" stroke-dasharray="4 4" opacity="0.7" vector-effect="non-scaling-stroke"></path>`;
+  }}
+  Object.entries(years).forEach(([year, pts]) => {{
+    const color=yearColor(year, years);
+    const sorted=pts.slice().sort((a,b)=>parseDay(a[0])-parseDay(b[0]));
+    const d=sorted.map((p,j)=>`${{j?'L':'M'}}${{x(p[0]).toFixed(1)}},${{y(p[1]).toFixed(1)}}`).join(" ");
+    out += `<path d="${{d}}" fill="none" stroke="${{color}}" stroke-width="2.2" vector-effect="non-scaling-stroke"></path>`;
+  }});
+  svg.innerHTML = out;
+}}
+function refreshFromLocalProgram() {{
+  const command = `& 'C:\\Users\\cjn_w\\.cache\\codex-runtimes\\codex-primary-runtime\\dependencies\\python\\python.exe' generate_fundamental_dashboard.py`;
+  fetch("http://127.0.0.1:8765/refresh", {{method:"POST"}})
+    .then(r => r.ok ? r.text() : Promise.reject(new Error("refresh service unavailable")))
+    .then(() => location.reload())
+    .catch(async () => {{
+      try {{ await navigator.clipboard.writeText(command); }} catch (e) {{}}
+      alert("浏览器不能直接运行本地 Python。已尝试复制刷新命令；若启用本地刷新服务，此按钮会自动运行底层计算并刷新页面。");
+    }});
+}}
+function historyColor(i) {{
+  const palette = ["#ef4444","#f97316","#1976d2","#65a30d","#a21caf","#0f9f9f","#374151","#9ca3af","#7c3aed","#0891b2","#be123c","#4d7c0f"];
+  return palette[i % palette.length];
+}}
+function drawHistoryChart(list) {{
+  const svg = document.getElementById("historySvg");
+  historyTooltip.style.display = "none";
+  const start = historyStart.value || "2026-01-01";
+  const end = historyEnd.value || todayString();
+  const useDemand = includeDemand.checked;
+  const series = list.map(c => {{
+    const pts = (c.scoreHistory || [])
+      .filter(p => p.date >= start && p.date <= end)
+      .map(p => [p.date, useDemand ? p.total : p.totalNoDemand])
+      .filter(p => p[1] != null && Number.isFinite(Number(p[1])));
+    return {{name:c.name, points:pts}};
+  }}).filter(s => s.points.length >= 2);
+  const W=1600,H=620,L=54,R=18,T=28,B=42;
+  if (!series.length) {{
+    svg.innerHTML = `<text x="800" y="300" text-anchor="middle" font-size="18" fill="#667085">暂无可绘制数据</text>`;
+    historyLegend.innerHTML = "";
+    return;
+  }}
+  const minDate = new Date(start).getTime();
+  const maxDate = new Date(end).getTime();
+  const span = Math.max(1, maxDate - minDate);
+  const x = d => L + (new Date(d).getTime() - minDate) / span * (W-L-R);
+  const y = v => T + (100 - v) / 100 * (H-T-B);
+  let out = "";
+  for (let i=0;i<=5;i++) {{
+    const val = i * 20, yy = y(val);
+    out += `<line class="grid" x1="${{L}}" y1="${{yy}}" x2="${{W-R}}" y2="${{yy}}"></line><text x="8" y="${{yy+4}}" font-size="12" fill="#667085">${{val}}</text>`;
+  }}
+  const ticks = 6;
+  for (let i=0;i<=ticks;i++) {{
+    const t = minDate + span * i / ticks;
+    const d = new Date(t);
+    const label = `${{d.getFullYear()}}-${{String(d.getMonth()+1).padStart(2,"0")}}`;
+    const xx = L + (W-L-R) * i / ticks;
+    out += `<line class="grid" x1="${{xx}}" y1="${{T}}" x2="${{xx}}" y2="${{H-B}}"></line><text x="${{xx-22}}" y="${{H-12}}" font-size="12" fill="#667085">${{label}}</text>`;
+  }}
+  out += `<line class="axis" x1="${{L}}" y1="${{H-B}}" x2="${{W-R}}" y2="${{H-B}}"></line><line class="axis" x1="${{L}}" y1="${{T}}" x2="${{L}}" y2="${{H-B}}"></line>`;
+  series.forEach((s,i) => {{
+    const d = s.points.map((p,j)=>`${{j?'L':'M'}}${{x(p[0]).toFixed(1)}},${{y(Number(p[1])).toFixed(1)}}`).join(" ");
+    out += `<path class="history-line" data-i="${{i}}" d="${{d}}" fill="none" stroke="${{historyColor(i)}}" stroke-width="1.6" opacity="0.68" vector-effect="non-scaling-stroke"><title>${{esc(s.name)}}</title></path>`;
+  }});
+  out += `<g class="history-crosshair" style="display:none"><line id="historyGuideX" x1="${{L}}" y1="${{T}}" x2="${{L}}" y2="${{H-B}}" stroke="#64748b" stroke-width="1" stroke-dasharray="4 4" opacity="0.75" vector-effect="non-scaling-stroke"></line><line id="historyGuideY" x1="${{L}}" y1="${{T}}" x2="${{W-R}}" y2="${{T}}" stroke="#64748b" stroke-width="1" stroke-dasharray="4 4" opacity="0.75" vector-effect="non-scaling-stroke"></line></g>`;
+  svg.innerHTML = out;
+  historyLegend.innerHTML = series.map((s,i)=>`<span class="history-legend-item" data-i="${{i}}" style="--c:${{historyColor(i)}}">${{esc(s.name)}}</span>`).join("");
+
+  function setHighlight(idx) {{
+    svg.querySelectorAll(".history-line").forEach(path => {{
+      const active = idx == null || Number(path.dataset.i) === idx;
+      path.setAttribute("opacity", active ? "0.95" : "0.12");
+      path.setAttribute("stroke-width", active ? "3.2" : "1.1");
+    }});
+    historyLegend.querySelectorAll(".history-legend-item").forEach(item => item.classList.toggle("active", idx != null && Number(item.dataset.i) === idx));
+  }}
+  historyLegend.querySelectorAll(".history-legend-item").forEach(item => {{
+    item.onmouseenter = () => setHighlight(Number(item.dataset.i));
+    item.onmouseleave = () => setHighlight(null);
+  }});
+  svg.querySelectorAll(".history-line").forEach(path => {{
+    path.onmouseenter = () => setHighlight(Number(path.dataset.i));
+    path.onmouseleave = () => setHighlight(null);
+  }});
+  const crosshair = svg.querySelector(".history-crosshair");
+  const guideX = svg.querySelector("#historyGuideX");
+  const guideY = svg.querySelector("#historyGuideY");
+
+  function nearestPoint(points, targetTime) {{
+    let best = null, bestDist = Infinity;
+    for (const p of points) {{
+      const dist = Math.abs(new Date(p[0]).getTime() - targetTime);
+      if (dist < bestDist) {{ best = p; bestDist = dist; }}
+    }}
+    return best;
+  }}
+  svg.onmousemove = ev => {{
+    const rect = svg.getBoundingClientRect();
+    const px = (ev.clientX - rect.left) / rect.width * W;
+    const clamped = Math.max(L, Math.min(W-R, px));
+    const targetTime = minDate + (clamped - L) / (W-L-R) * span;
+    const date = new Date(targetTime);
+    const dateText = `${{date.getFullYear()}}-${{String(date.getMonth()+1).padStart(2,"0")}}-${{String(date.getDate()).padStart(2,"0")}}`;
+    const rows = series.map((s,i) => {{
+      const p = nearestPoint(s.points, targetTime);
+      return p ? {{name:s.name, score:Number(p[1]), color:historyColor(i), date:p[0]}} : null;
+    }}).filter(Boolean).sort((a,b)=>b.score-a.score);
+    const py = (ev.clientY - rect.top) / rect.height * H;
+    const guideYValue = Math.max(0, Math.min(100, 100 - ((py - T) / (H - T - B)) * 100));
+    const nearest = rows.length ? rows.reduce((best, r) => Math.abs(Number(r.score) - guideYValue) < Math.abs(Number(best.score) - guideYValue) ? r : best, rows[0]) : null;
+    if (crosshair) {{
+      crosshair.style.display = "block";
+      guideX.setAttribute("x1", clamped.toFixed(1));
+      guideX.setAttribute("x2", clamped.toFixed(1));
+      const gy = y(guideYValue);
+      guideY.setAttribute("y1", gy.toFixed(1));
+      guideY.setAttribute("y2", gy.toFixed(1));
+    }}
+    historyTooltip.innerHTML = `<div class="date">${{dateText}}　光标得分 ${{fmt(guideYValue)}}${{nearest ? "　近线 " + esc(nearest.name) + " " + fmt(nearest.score) : ""}}</div><div class="grid">` + rows.map(r => `<div class="row"><span class="name" style="--c:${{r.color}}; color:${{r.color}}">${{esc(r.name)}}</span><span>${{fmt(r.score)}}</span></div>`).join("") + `</div>`;
+    const wrap = historyChartWrap.getBoundingClientRect();
+    let left = ev.clientX - wrap.left + 14;
+    let top = ev.clientY - wrap.top + 14;
+    historyTooltip.style.display = "block";
+    const tw = historyTooltip.offsetWidth || 260;
+    const th = historyTooltip.offsetHeight || 360;
+    if (left + tw > wrap.width) left = ev.clientX - wrap.left - tw - 14;
+    if (top + th > wrap.height) top = Math.max(8, wrap.height - th - 8);
+    historyTooltip.style.left = `${{Math.max(8,left)}}px`;
+    historyTooltip.style.top = `${{Math.max(8,top)}}px`;
+  }};
+  svg.onmouseleave = () => {{
+    historyTooltip.style.display = "none";
+    if (crosshair) crosshair.style.display = "none";
+    setHighlight(null);
+  }};
+}}
+render();
+</script>
+</body>
+</html>"""
+
+
+def main() -> None:
+    data = make_records()
+    OUTPUT_FILE.write_text(html_template(data), encoding="utf-8")
+    scored = [c for c in data["commodities"] if c["total"] is not None]
+    print(f"Wrote {OUTPUT_FILE}")
+    print(f"Scored commodities: {len(scored)} / {len(data['commodities'])}")
+    if scored:
+        print("Top 5:", ", ".join(f"{c['name']} {c['total']}" for c in scored[:5]))
+        print("Bottom 5:", ", ".join(f"{c['name']} {c['total']}" for c in scored[-5:]))
+
+
+if __name__ == "__main__":
+    main()

refresh_dashboard_server.py

@@ -0,0 +1,42 @@
+from __future__ import annotations
+
+import http.server
+import subprocess
+import sys
+from pathlib import Path
+
+
+BASE_DIR = Path(__file__).resolve().parent
+PORT = 8765
+
+
+class Handler(http.server.SimpleHTTPRequestHandler):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, directory=str(BASE_DIR), **kwargs)
+
+    def do_POST(self):
+        if self.path != "/refresh":
+            self.send_error(404)
+            return
+        proc = subprocess.run(
+            [sys.executable, str(BASE_DIR / "generate_fundamental_dashboard.py")],
+            cwd=str(BASE_DIR),
+            text=True,
+            capture_output=True,
+        )
+        body = (proc.stdout or "") + (proc.stderr or "")
+        self.send_response(200 if proc.returncode == 0 else 500)
+        self.send_header("Access-Control-Allow-Origin", "*")
+        self.send_header("Content-Type", "text/plain; charset=utf-8")
+        self.end_headers()
+        self.wfile.write(body.encode("utf-8", errors="replace"))
+
+    def end_headers(self):
+        self.send_header("Access-Control-Allow-Origin", "*")
+        super().end_headers()
+
+
+if __name__ == "__main__":
+    server = http.server.ThreadingHTTPServer(("127.0.0.1", PORT), Handler)
+    print(f"http://127.0.0.1:{PORT}/基本面评分面板.html")
+    server.serve_forever()

月差/A-期货日级数据/SKILL.md

@@ -0,0 +1,132 @@
+---
+name: A-期货日级数据
+description: 通过 mysql_dll2.dll 连接 MySQL 数据库并执行 SQL 查询。当用户需要查询 MySQL 数据库、执行 SQL 语句、获取数据库中的数据时触发。 触发关键词包括：查询数据库、查合约、查日线、查K线、查结算价、查持仓量、查成交量、查保证金、 查品种数据、读取数据库、SQL查询、查某品种某合约、查期货数据、从数据库取数据、db查询、查纯碱、查螺纹等。 注意：此 Skill 依赖 mysql_dll2.dll 文件，仅限 Windows 平台使用。数据库编号固定为 1。
+disable: true
+allowed-tools: 
+---
+
+.dll 连接 MySQL 数据库并执行 SQL 查询。当用户需要查询 MySQL 数据库、执行 SQL 语句、获取数据库中的数据时触发。
+  触发关键词包括：查询数据库、查合约、查日线、查K线、查结算价、查持仓量、查成交量、查保证金、
+  查品种数据、读取数据库、SQL查询、查某品种某合约、查期货数据、从数据库取数据、db查询、查纯碱、查螺纹等。
+  注意：此 Skill 依赖 mysql_dll2.dll 文件，仅限 Windows 平台使用。数据库编号固定为 1。
+allowed-tools: 
+disable: true
+---
+
+# A-期货日级数据
+
+## 用途
+
+把自然语言翻译成 SQL 执行，返回原始数据。不生成汇总、不分析、不联想。
+
+---
+
+## 数据库
+
+- **db_index：固定为 1**，无需询问用户
+
+---
+
+## 调用方式
+
+```python
+import sys
+sys.path.insert(0, r"<skill_scripts_dir>")
+from mysql_client import MysqlDLLClient
+
+db = MysqlDLLClient()
+result = db.query(1, "SELECT * FROM `contract_day` WHERE p_code = ?", ["sa"])
+print(result)
+db.close()
+```
+
+---
+
+## 字段说明（references/field_mapping.md）
+
+| 英文字段名 | 中文含义 | 字段类型 |
+|-----------|---------|---------|
+| contract | 合约 | varchar(10) |
+| open | 开盘价 | float |
+| high | 高（最高价） | float |
+| low | 低（最低价） | float |
+| close | 收（收盘价） | float |
+| volume | 成交（成交量） | float |
+| oi | 持仓（持仓量） | float |
+| p_code | 品种 | varchar(4) |
+| jys | 交易所 | varchar(6) |
+| times | 时间 | datetime |
+
+### 品种 vs 合约
+
+| 概念 | 字段 | 说明 | 示例 |
+|------|------|------|------|
+| 品种 | `p_code` | 品种代码，拼音小写 | `sa`（纯碱）、`rb`（螺纹钢） |
+| 合约 | `contract` | 品种 + 交割月份 | `sa605`（纯碱2026年5月交割） |
+
+> 郑商所（CZCE）合约月份为3位，如 `SR501`、`MA509`。
+
+---
+
+## 查询示例
+
+**查所有品种某时间段数据（直接一条SQL搞定，不需要先查品种）**
+
+```sql
+SELECT * FROM contract_day WHERE times >= '2026-01-01' AND times <= '2026-12-31'
+```
+
+**查纯碱26年所有合约数据**
+
+```
+p_code = 'SA'
+时间范围: times >= '2026-01-01' AND times <= '2026-12-31'
+```
+
+**查纯碱605合约数据**
+
+```
+contract = 'SA605'
+```
+
+**查螺纹钢26年所有数据**
+
+```
+p_code = 'RB'
+时间范围: times >= '2026-01-01' AND times <= '2026-12-31'
+```
+
+---
+
+## 执行规则
+
+1. **直接执行，不询问确认。**
+2. **只返回数据，不生成汇总、不分析。**
+3. **db_index 固定为 1。**
+4. **参数化查询**，所有条件用 `?` 占位符传参。
+5. **查所有品种时直接一条 SQL**，不需要先 `SELECT DISTINCT p_code` 再逐条查。
+
+---
+
+## 依赖文件
+
+```
+scripts/
+└── mysql_client.py
+lib/
+└── mysql_dll/
+    ├── mysql_dll2.dll
+    ├── jsoncpp.dll
+    ├── libcrypto-1_1-x64.dll
+    ├── libmysql.dll
+    ├── libssl-1_1-x64.dll
+    └── mysqlcppconn-9-vs14.dll
+```
+
+DLL 由 `mysql_client.py` 自动加载，无需手动配置。
+
+---
+
+## 品种代码对照（references/variety_mapping.md）
+
+详见 `references/variety_mapping.md`，包含所有交易所品种代码。

月差/A-期货日级数据/references/field_mapping.md

@@ -0,0 +1,29 @@
+# 数据库字段中英文对照表
+
+## 品种 vs 合约
+
+| 概念 | 字段 | 说明 | 示例 |
+|------|------|------|------|
+| **品种** | `p_code` | 品种代码，拼音小写，代表品种分类 | `rb`（螺纹钢）、`cu`（铜） |
+| **合约** | `contract` | 具体合约代码 = 品种 + 交割月份 | `rb2506`（螺纹钢2025年6月交割） |
+
+> 郑商所（CZCE）合约月份为3位，如 `SR501`、`MA509`。
+
+
+## 字段说明
+
+| 英文字段名 | 中文注释 | 字段类型 |
+|-----------|---------|---------|
+| contract | 合约 | varchar(10) |
+| open | 开盘价 | float |
+| high | 高（最高价） | float |
+| low | 低（最低价） | float |
+| close | 收（收盘价） | float |
+| volume | 成交（成交量） | float |
+| oi | 持仓（持仓量） | float |
+| p_code | 品种 | varchar(4) |
+| jys | 交易所 | varchar(6) |
+| times | 时间 | datetime |
+
+
+

月差/A-期货日级数据/references/variety_mapping.md

@@ -0,0 +1,119 @@
+# 期货品种中英文对照表
+
+## 中金所（CFFEX）
+
+| p_code（查询用） | 中文名称 | 合约位数 | 备注 |
+|-----------------|---------|---------|------|
+| if / IF | 沪深300股指期货 | 4位 | 如 IF2506 |
+| ih / IH | 上证50股指期货 | 4位 | 如 IH2506 |
+| im / IM | 中证1000股指期货 | 4位 | 如 IM2506 |
+| ic / IC | 中证500股指期货 | 4位 | 如 IC2506 |
+| tf / TF | 5年国债期货 | 4位 | 如 TF2506 |
+| t / T | 10年国债期货 | 4位 | 如 T2506 |
+| ts / TS | 2年国债期货 | 4位 | 如 TS2506 |
+| tl / TL | 30年国债期货 | 4位 | 如 TL2506 |
+
+---
+
+## 上海期货交易所（SHFE）
+
+| p_code | 中文名称 | 合约位数 | 示例 |
+|--------|---------|---------|------|
+| cu | 铜 | 4位 | cu2506 |
+| al | 铝 | 4位 | al2506 |
+| zn | 锌 | 4位 | zn2506 |
+| pb | 铅 | 4位 | pb2506 |
+| ni | 镍 | 4位 | ni2506 |
+| sn | 锡 | 4位 | sn2506 |
+| au | 黄金 | 4位 | au2506 |
+| ag | 白银 | 4位 | ag2506 |
+| rb | 螺纹钢 | 4位 | rb2506 |
+| wr | 线材 | 4位 | wr2506 |
+| hc | 热轧卷板 | 4位 | hc2506 |
+| ss | 不锈钢 | 4位 | ss2506 |
+| fu | 燃料油 | 4位 | fu2506 |
+| bu | 沥青 | 4位 | bu2506 |
+| ru | 天然橡胶 | 4位 | ru2506 |
+| sp | 纸浆 | 4位 | sp2506 |
+| br | 丁二烯橡胶 | 4位 | br2506 |
+
+---
+
+## 大连商品交易所（DCE）
+
+| p_code | 中文名称 | 合约位数 | 示例 |
+|--------|---------|---------|------|
+| a | 豆一 | 4位 | a2506 |
+| b | 豆二 | 4位 | b2506 |
+| m | 豆粕 | 4位 | m2506 |
+| y | 豆油 | 4位 | y2506 |
+| p | 棕榈油 | 4位 | p2506 |
+| c | 玉米 | 4位 | c2506 |
+| cs | 玉米淀粉 | 4位 | cs2506 |
+| jd | 鸡蛋 | 4位 | jd2506 |
+| l | 聚乙烯 | 4位 | l2506 |
+| v | 聚氯乙烯 | 4位 | v2506 |
+| pp | 聚丙烯 | 4位 | pp2506 |
+| j | 焦炭 | 4位 | j2506 |
+| jm | 焦煤 | 4位 | jm2506 |
+| i | 铁矿石 | 4位 | i2506 |
+| eg | 乙二醇 | 4位 | eg2506 |
+| rr | 粳米 | 4位 | rr2506 |
+| eb | 苯乙烯 | 4位 | eb2506 |
+| pg | 液化石油气 | 4位 | pg2506 |
+| lh | 生猪 | 4位 | lh2506 |
+
+---
+
+## 郑州商品交易所（CZCE）
+
+> ⚠️ **郑商所合约特殊规则：合约月份只有 3 位数字**
+> 例如：SR501（白糖2501年1月），MA509（甲醇2509年9月）
+> 年份只取个位数，与其他交易所4位不同！
+
+| p_code | 中文名称 | 合约格式 | 示例 |
+|--------|---------|---------|------|
+| SR | 白糖 | 品种+3位 | SR501 |
+| CF | 棉花 | 品种+3位 | CF501 |
+| MA | 甲醇 | 品种+3位 | MA509 |
+| TA | PTA | 品种+3位 | TA509 |
+| OI | 菜籽油 | 品种+3位 | OI509 |
+| RM | 菜籽粕 | 品种+3位 | RM509 |
+| RS | 菜籽 | 品种+3位 | RS509 |
+| WH | 强麦 | 品种+3位 | WH509 |
+| PM | 普麦 | 品种+3位 | PM509 |
+| RI | 早籼稻 | 品种+3位 | RI509 |
+| JR | 粳稻 | 品种+3位 | JR509 |
+| LR | 晚籼稻 | 品种+3位 | LR509 |
+| AP | 苹果 | 品种+3位 | AP509 |
+| CJ | 红枣 | 品种+3位 | CJ509 |
+| SF | 硅铁 | 品种+3位 | SF509 |
+| SM | 锰硅 | 品种+3位 | SM509 |
+| ZC | 动力煤 | 品种+3位 | ZC509 |
+| FG | 玻璃 | 品种+3位 | FG509 |
+| SA | 纯碱 | 品种+3位 | SA509 |
+| UR | 尿素 | 品种+3位 | UR509 |
+| PF | 短纤 | 品种+3位 | PF509 |
+| PX | 对二甲苯 | 品种+3位 | PX509 |
+| PR | 丙烯 | 品种+3位 | PR509 |
+| SH | 烧碱 | 品种+3位 | SH509 |
+
+---
+
+## 上海国际能源交易中心（INE）
+
+| p_code | 中文名称 | 合约位数 | 示例 |
+|--------|---------|---------|------|
+| sc | 原油 | 4位 | sc2506 |
+| lu | 低硫燃料油 | 4位 | lu2506 |
+| nr | 20号胶 | 4位 | nr2506 |
+| bc | 国际铜 | 4位 | bc2506 |
+
+---
+
+## 广州期货交易所（GFEX）
+
+| p_code | 中文名称 | 合约位数 | 示例 |
+|--------|---------|---------|------|
+| si | 工业硅 | 4位 | si2506 |
+| lc | 碳酸锂 | 4位 | lc2506 |

月差/A-期货日级数据/scripts/mysql_client.py

@@ -0,0 +1,172 @@
+import ctypes
+import json
+from pathlib import Path
+import time
+
+
+class MysqlDLLClient:
+    """
+    MySQL DLL 调用客户端
+    用于调用 mysql_dll2.dll 执行 SQL
+
+    Example
+    -------
+    db = MysqlDLLClient()
+
+    data = db.query(
+        7,
+        "select * from min15_a_jq where times>=? and times<=?",
+        ["2025-12-24 00:00:00", "2025-12-26 00:00:00"]
+    )
+
+    print(data)
+    """
+
+    def __init__(self, dll_path=None):
+        """
+        初始化 DLL
+
+        Parameters
+        ----------
+        dll_path : str | Path
+            dll路径，默认当前目录 mysql_dll2.dll
+        """
+
+        if dll_path is None:
+            root = Path(__file__).resolve().parent.parent
+            dll_path = root / "lib/mysql_dll/mysql_dll2.dll"
+
+        self.dll = ctypes.WinDLL(str(dll_path))
+
+        self._init_functions()
+
+        time.sleep(1)
+
+        ret = self.dll.InitDBConfig()
+        if ret != 1:
+            raise RuntimeError("服务器授权失败")
+
+    # ---------------------------------------------------------
+    # 初始化 DLL 函数声明
+    # ---------------------------------------------------------
+    def _init_functions(self):
+
+        # 初始化数据库配置
+        self.dll.InitDBConfig.argtypes = []
+        self.dll.InitDBConfig.restype = ctypes.c_int
+
+        # 关闭 DLL
+        self.dll.ShutdownDLL.argtypes = []
+        self.dll.ShutdownDLL.restype = None
+
+        # QuerySQL_Auto
+        self.dll.QuerySQL_Auto.argtypes = [
+            ctypes.c_int,                       # db_index
+            ctypes.c_char_p,                    # sql
+            ctypes.c_char_p,                    # params
+            ctypes.POINTER(ctypes.c_void_p),    # out_buf
+            ctypes.POINTER(ctypes.c_int)        # out_size
+        ]
+
+        self.dll.QuerySQL_Auto.restype = ctypes.c_int
+
+        # FreeBuffer
+        self.dll.FreeBuffer.argtypes = [ctypes.c_void_p]
+        self.dll.FreeBuffer.restype = None
+
+    # ---------------------------------------------------------
+    # 参数转换
+    # ---------------------------------------------------------
+    def _build_params(self, params):
+        """
+        参数列表转 DLL 参数格式
+
+        ["2025-01-01","2025-01-02"]
+
+        ->
+
+        b"s:2025-01-01|s:2025-01-02"
+        """
+
+        if not params:
+            return b""
+
+        arr = []
+
+        for p in params:
+            if isinstance(p, str):
+                arr.append(f"s:{p}")
+            elif isinstance(p, int):
+                arr.append(f"i:{p}")
+            elif isinstance(p, float):
+                arr.append(f"f:{p}")
+            else:
+                raise TypeError(f"不支持的参数类型: {type(p)}")
+
+        return "|".join(arr).encode()
+
+    # ---------------------------------------------------------
+    # 查询
+    # ---------------------------------------------------------
+    def query(self, db_index, sql, params=None):
+        """
+        执行 SQL 查询
+
+        Parameters
+        ----------
+        db_index : int
+            数据库编号
+
+        sql : str
+            SQL语句
+
+        params : list
+            SQL参数
+
+        Returns
+        -------
+        str
+            查询结果（JSON 或文本）
+        """
+
+        if isinstance(sql, str):
+            sql = sql.encode()
+
+        params_bytes = self._build_params(params)
+
+        out_buf = ctypes.c_void_p()
+        out_size = ctypes.c_int()
+
+        ret = self.dll.QuerySQL_Auto(
+            db_index,
+            sql,
+            params_bytes,
+            ctypes.byref(out_buf),
+            ctypes.byref(out_size)
+        )
+
+        if ret != 0:
+            raise RuntimeError("SQL执行失败")
+
+        try:
+            data = ctypes.string_at(out_buf.value, out_size.value)
+            return json.loads(data.decode())
+        finally:
+            self.dll.FreeBuffer(out_buf)
+
+    # ---------------------------------------------------------
+    # 关闭
+    # ---------------------------------------------------------
+    def close(self):
+        """关闭 DLL"""
+        if self.dll:
+            self.dll.ShutdownDLL()
+
+    # ---------------------------------------------------------
+    # with 支持
+    # ---------------------------------------------------------
+    def __enter__(self):
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        self.close()