diff --git a/data_platform/daily_all_update.py b/data_platform/daily_all_update.py
new file mode 100644
index 00000000..0110d5de
--- /dev/null
+++ b/data_platform/daily_all_update.py
@@ -0,0 +1,490 @@
+#!/usr/bin/env python3
+"""
+全市场每日增量更新 - 日线 + 15分钟线
+
+功能：
+  1. 日线：腾讯K线API → 更新Parquet + vnpy DB
+  2. 15分钟线：新浪API（800条） → 增量合并Parquet + 导入vnpy DB
+
+设计原则：
+  - 增量更新，不重复下载
+  - 失败不影响其他股票
+  - 进度持久化，支持断点续传
+  - 限频保护
+  - 日志完整
+
+用法：
+  python3 daily_all_update.py                  # 全量更新（日线+15min）
+  python3 daily_all_update.py --skip-daily     # 只更新15min
+  python3 daily_all_update.py --skip-15min     # 只更新日线
+"""
+
+import argparse
+import json
+import os
+import re
+import sqlite3
+import sys
+import time
+import logging
+import urllib.request
+import urllib.error
+from datetime import datetime, timedelta
+from pathlib import Path
+from typing import Optional, List, Tuple
+
+import pandas as pd
+
+# ======================== 配置 ========================
+
+LOG_DIR = Path("/Volumes/stock/logs/daily_update")
+DAILY_DIR = Path("/Volumes/stock/A股数据/日线数据/daily")
+MINUTE_15_DIR = Path("/Volumes/stock/minute_kline/15min")
+VNPY_DB_PATH = Path("/Volumes/stock/sanguo_vnpy/data/quant_trading.db")
+ALL_STOCKS_FILE = Path("/Volumes/stock/A股数据/stock_info/stock_basic_info_raw_20260326_113530.csv")
+PROGRESS_DIR = Path("/Volumes/stock/logs/daily_update/progress")
+
+REQUEST_INTERVAL = 0.3
+MAX_RETRIES = 3
+CONSECUTIVE_FAIL_PAUSE = 60
+MAX_CONSECUTIVE_FAILS = 10
+DB_BATCH_SIZE = 50000
+
+HEADERS = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7)"}
+
+
+def setup_logging():
+    LOG_DIR.mkdir(parents=True, exist_ok=True)
+    ts = datetime.now().strftime("%Y%m%d_%H%M%S")
+    log_file = LOG_DIR / f"update_{ts}.log"
+
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s %(levelname)s %(message)s",
+        handlers=[
+            logging.FileHandler(log_file, encoding="utf-8"),
+            logging.StreamHandler(),
+        ],
+    )
+    return logging.getLogger(__name__)
+
+
+logger = setup_logging()
+
+
+def _make_opener():
+    return urllib.request.build_opener(urllib.request.ProxyHandler({}))
+
+
+# ======================== 工具函数 ========================
+
+def get_market_prefix(code: str) -> Tuple[str, str]:
+    code = re.sub(r"[^0-9]", "", code).zfill(6)
+    if code.startswith(("60", "68", "51")):
+        return "sh", code
+    return "sz", code
+
+
+def get_all_codes() -> List[str]:
+    df = pd.read_csv(ALL_STOCKS_FILE)
+    for col in ["代码", "code", "股票代码"]:
+        if col in df.columns:
+            return [str(c).zfill(6) for c in df[col].tolist()]
+    raise ValueError(f"找不到代码列: {list(df.columns)}")
+
+
+def nas_mounted() -> bool:
+    return DAILY_DIR.exists() and MINUTE_15_DIR.exists()
+
+
+# ======================== 日线更新 ========================
+
+def fetch_tencent_daily(code: str, start_date: str, end_date: str) -> Optional[pd.DataFrame]:
+    """腾讯K线API获取日线增量"""
+    prefix, clean = get_market_prefix(code)
+    tq = f"{prefix}{clean}"
+    days = (pd.Timestamp(end_date) - pd.Timestamp(start_date)).days + 10
+    url = f"https://web.ifzq.gtimg.cn/appstock/app/fqkline/get?param={tq},day,{start_date},,{days},"
+
+    opener = _make_opener()
+    req = urllib.request.Request(url, headers=HEADERS)
+    with opener.open(req, timeout=10) as r:
+        raw = r.read().decode("utf-8", errors="replace")
+    data = json.loads(raw)
+    d = data.get("data")
+    if not isinstance(d, dict):
+        return None
+    klines = d.get(tq, {}).get("day", [])
+    if not klines:
+        return None
+
+    df = pd.DataFrame(klines)
+    ncols = len(df.columns)
+    if ncols >= 7:
+        df.columns = ["date", "open", "close", "high", "low", "volume", "amount"][:ncols]
+    else:
+        df.columns = ["date", "open", "close", "high", "low", "volume"][:ncols]
+    if "amount" not in df.columns:
+        df["amount"] = 0.0
+    for c in ["open", "close", "high", "low", "volume", "amount"]:
+        df[c] = pd.to_numeric(df[c], errors="coerce").fillna(0)
+    df["date"] = pd.to_datetime(df["date"]).dt.strftime("%Y-%m-%d")
+    mask = (df["date"] >= start_date) & (df["date"] <= end_date)
+    result = df.loc[mask, ["date", "open", "high", "low", "close", "volume", "amount"]]
+    return result if not result.empty else None
+
+
+def update_daily_parquet(code: str, new_data: pd.DataFrame) -> int:
+    """增量写入日线Parquet"""
+    prefix, clean = get_market_prefix(code)
+    year = datetime.now().year
+    parquet_path = DAILY_DIR / str(year) / f"{prefix}{clean}_daily.parquet"
+
+    if parquet_path.exists():
+        existing = pd.read_parquet(parquet_path)
+        combined = pd.concat([existing, new_data], ignore_index=True)
+        combined = combined.drop_duplicates(subset=["date"], keep="last")
+        combined = combined.sort_values("date").reset_index(drop=True)
+    else:
+        parquet_path.parent.mkdir(parents=True, exist_ok=True)
+        combined = new_data
+
+    tmp = parquet_path.with_suffix(".tmp")
+    combined.to_parquet(tmp, index=False)
+    tmp.rename(parquet_path)
+    return len(new_data)
+
+
+def get_daily_last_date(code: str) -> str:
+    prefix, clean = get_market_prefix(code)
+    for year in range(datetime.now().year, 2009, -1):
+        fpath = DAILY_DIR / str(year) / f"{prefix}{clean}_daily.parquet"
+        if fpath.exists():
+            try:
+                df = pd.read_parquet(fpath, columns=["date"])
+                if not df.empty:
+                    return str(df["date"].max())[:10]
+            except Exception:
+                pass
+    return ""
+
+
+def run_daily_update(codes: List[str]) -> dict:
+    """日线增量更新"""
+    logger.info("=" * 60)
+    logger.info("日线增量更新开始，共 %d 只", len(codes))
+    today = datetime.now().strftime("%Y-%m-%d")
+
+    stats = {"updated": 0, "skipped": 0, "failed": 0, "records": 0, "db_records": 0}
+    all_db_values = []
+    consecutive_fails = 0
+
+    for i, code in enumerate(codes):
+        if i > 0:
+            time.sleep(REQUEST_INTERVAL)
+
+        last_date = get_daily_last_date(code)
+        if not last_date:
+            stats["skipped"] += 1
+            continue
+        next_day = (pd.Timestamp(last_date) + timedelta(days=1)).strftime("%Y-%m-%d")
+        if next_day > today:
+            stats["skipped"] += 1
+            continue
+
+        data = None
+        for attempt in range(MAX_RETRIES):
+            try:
+                data = fetch_tencent_daily(code, next_day, today)
+                break
+            except Exception as e:
+                if attempt < MAX_RETRIES - 1:
+                    time.sleep(1)
+                else:
+                    logger.debug("日线 %s 失败: %s", code, e)
+
+        if data is None or data.empty:
+            stats["skipped"] += 1
+            continue
+
+        # 校验
+        if (data[["open", "high", "low", "close"]] <= 0).any().any():
+            stats["failed"] += 1
+            continue
+
+        try:
+            n = update_daily_parquet(code, data)
+            stats["updated"] += 1
+            stats["records"] += n
+            consecutive_fails = 0
+
+            # 收集vnpy DB数据
+            prefix, clean = get_market_prefix(code)
+            exchange = "SSE" if prefix == "sh" else "SZSE"
+            for _, row in data.iterrows():
+                all_db_values.append((
+                    clean, exchange, str(row["date"]), "d",
+                    float(row.get("volume", 0)), float(row.get("amount", 0)), 0.0,
+                    float(row.get("open", 0)), float(row.get("high", 0)),
+                    float(row.get("low", 0)), float(row.get("close", 0)),
+                ))
+                stats["db_records"] += 1
+        except Exception as e:
+            stats["failed"] += 1
+            consecutive_fails += 1
+            logger.warning("日线写入失败 %s: %s", code, e)
+
+        if consecutive_fails >= MAX_CONSECUTIVE_FAILS:
+            logger.error("连续失败 %d 次，暂停 %d 秒", consecutive_fails, CONSECUTIVE_FAIL_PAUSE)
+            time.sleep(CONSECUTIVE_FAIL_PAUSE)
+            consecutive_fails = 0
+
+        if (i + 1) % 500 == 0:
+            logger.info("日线进度: %d/%d updated=%d", i + 1, len(codes), stats["updated"])
+
+    # 写vnpy DB
+    if all_db_values:
+        _write_vnpy_db(all_db_values, "日线")
+
+    logger.info("日线完成: %s", json.dumps(stats, ensure_ascii=False))
+    return stats
+
+
+# ======================== 15分钟线更新 ========================
+
+def try_sina_15min(symbol: str, datalen: int = 800) -> Optional[pd.DataFrame]:
+    """新浪15分钟K线API"""
+    url = (
+        f"https://quotes.sina.cn/cn/api/jsonp_v2.php/var%20=min15_{symbol}=/"
+        f"CN_MarketDataService.getKLineData?symbol={symbol}&scale=15&ma=no&datalen={datalen}"
+    )
+    opener = _make_opener()
+    req = urllib.request.Request(url, headers=HEADERS)
+    with opener.open(req, timeout=15) as r:
+        raw = r.read().decode("utf-8", errors="replace")
+    m = re.search(r"\((\[.*\])\)", raw, re.DOTALL)
+    if not m:
+        return None
+    data = json.loads(m.group(1))
+    if not data:
+        return None
+    df = pd.DataFrame(data)
+    cols = ["day", "open", "high", "low", "close", "volume", "amount"]
+    for c in cols:
+        if c not in df.columns:
+            return None
+    return df[cols]
+
+
+def update_15min_parquet(code: str) -> Tuple[str, int]:
+    """增量下载并合并15分钟线"""
+    prefix, clean = get_market_prefix(code)
+    symbol = f"{prefix}{clean}"
+    parquet_path = MINUTE_15_DIR / f"{prefix}{clean}_15min.parquet"
+
+    df_new = None
+    for attempt in range(MAX_RETRIES):
+        try:
+            df_new = try_sina_15min(symbol)
+            if df_new is not None and len(df_new) > 0:
+                break
+        except Exception:
+            if attempt < MAX_RETRIES - 1:
+                time.sleep(1)
+
+    if df_new is None or df_new.empty:
+        return "failed", 0
+
+    # 数据校验
+    for col in ["open", "high", "low", "close"]:
+        df_new[col] = pd.to_numeric(df_new[col], errors="coerce")
+    df_new["volume"] = pd.to_numeric(df_new["volume"], errors="coerce").fillna(0)
+    df_new["amount"] = pd.to_numeric(df_new["amount"], errors="coerce").fillna(0)
+
+    bad_zero = (df_new[["close", "open"]] <= 0).any(axis=1)
+    if bad_zero.any():
+        df_new = df_new[~bad_zero]
+    bad_ohlc = (df_new["high"] < df_new[["open", "close"]].max(axis=1)) | \
+               (df_new["low"] > df_new[["open", "close"]].min(axis=1))
+    if bad_ohlc.any():
+        df_new = df_new[~bad_ohlc]
+    if df_new.empty:
+        return "failed", 0
+
+    # 转回object类型
+    df_new["volume"] = df_new["volume"].astype(str)
+    df_new["amount"] = df_new["amount"].astype(str)
+
+    if parquet_path.exists():
+        existing = pd.read_parquet(parquet_path)
+        old_len = len(existing)
+        combined = pd.concat([existing, df_new], ignore_index=True)
+        combined = combined.drop_duplicates(subset=["day"], keep="last")
+        combined = combined.sort_values("day").reset_index(drop=True)
+        new_rows = len(combined) - old_len
+    else:
+        combined = df_new
+        new_rows = len(df_new)
+
+    tmp = parquet_path.with_suffix(".tmp")
+    combined.to_parquet(tmp, index=False)
+    tmp.rename(parquet_path)
+    return "ok", new_rows
+
+
+def run_15min_update(codes: List[str]) -> dict:
+    """15分钟线增量更新"""
+    logger.info("=" * 60)
+    logger.info("15分钟线增量更新开始，共 %d 只", len(codes))
+
+    stats = {"updated": 0, "skipped": 0, "failed": 0, "records": 0, "db_records": 0}
+    all_db_values = []
+    consecutive_fails = 0
+
+    # 加载进度（支持断点续传）
+    progress_file = PROGRESS_DIR / "15min_progress.json"
+    PROGRESS_DIR.mkdir(parents=True, exist_ok=True)
+    done_set = set()
+    if progress_file.exists():
+        try:
+            done_set = set(json.loads(progress_file.read_text()).get("done", []))
+        except Exception:
+            pass
+
+    todo = [c for c in codes if c not in done_set]
+    logger.info("待更新: %d（已完成: %d）", len(todo), len(done_set))
+
+    for i, code in enumerate(todo):
+        if i > 0:
+            time.sleep(REQUEST_INTERVAL)
+
+        try:
+            status, new_rows = update_15min_parquet(code)
+        except Exception as e:
+            status, new_rows = "failed", 0
+            logger.debug("15min %s 异常: %s", code, e)
+
+        if status == "ok":
+            stats["updated"] += 1
+            stats["records"] += new_rows
+            consecutive_fails = 0
+
+            # 收集vnpy DB数据
+            prefix, clean = get_market_prefix(code)
+            parquet_path = MINUTE_15_DIR / f"{prefix}{clean}_15min.parquet"
+            if parquet_path.exists() and new_rows > 0:
+                df = pd.read_parquet(parquet_path)
+                # 只取最新的增量部分
+                if len(df) > new_rows:
+                    df_new_part = df.iloc[-new_rows:]
+                else:
+                    df_new_part = df
+
+                exchange = "SSE" if prefix == "sh" else "SZSE"
+                for _, row in df_new_part.iterrows():
+                    all_db_values.append((
+                        clean, exchange, str(row["day"]), "1m",
+                        float(row.get("volume", 0)), float(row.get("amount", 0)), 0.0,
+                        float(row.get("open", 0)), float(row.get("high", 0)),
+                        float(row.get("low", 0)), float(row.get("close", 0)),
+                    ))
+                stats["db_records"] += len(df_new_part)
+        else:
+            stats["failed"] += 1
+            consecutive_fails += 1
+
+        done_set.add(code)
+
+        if consecutive_fails >= MAX_CONSECUTIVE_FAILS:
+            logger.error("连续失败 %d 次，暂停 %d 秒", consecutive_fails, CONSECUTIVE_FAIL_PAUSE)
+            time.sleep(CONSECUTIVE_FAIL_PAUSE)
+            consecutive_fails = 0
+
+        if (i + 1) % 500 == 0:
+            logger.info("15min进度: %d/%d updated=%d failed=%d", i + 1, len(todo), stats["updated"], stats["failed"])
+            # 保存进度
+            progress_file.write_text(json.dumps({"done": list(done_set), "ts": datetime.now().isoformat()}))
+
+    # 写vnpy DB
+    if all_db_values:
+        _write_vnpy_db(all_db_values, "15min")
+
+    # 保存最终进度
+    progress_file.write_text(json.dumps({"done": list(done_set), "ts": datetime.now().isoformat()}))
+    logger.info("15min完成: %s", json.dumps(stats, ensure_ascii=False))
+    return stats
+
+
+# ======================== vnpy DB写入 ========================
+
+def _write_vnpy_db(values: list, label: str):
+    """增量写入vnpy SQLite DB"""
+    logger.info("写入vnpy DB [%s]: %d 条记录", label, len(values))
+    try:
+        conn = sqlite3.connect(str(VNPY_DB_PATH), timeout=120)
+        c = conn.cursor()
+        c.execute("PRAGMA journal_mode=WAL")
+        for j in range(0, len(values), DB_BATCH_SIZE):
+            c.executemany(
+                """INSERT OR REPLACE INTO dbbardata
+                (symbol,exchange,datetime,interval,volume,turnover,open_interest,
+                 open_price,high_price,low_price,close_price)
+                VALUES (?,?,?,?,?,?,?,?,?,?,?)""",
+                values[j : j + DB_BATCH_SIZE],
+            )
+            conn.commit()
+            logger.info("  DB批次 %d/%d", j // DB_BATCH_SIZE + 1, (len(values) - 1) // DB_BATCH_SIZE + 1)
+
+        # 更新overview
+        c.execute(
+            """INSERT OR REPLACE INTO dbbaroverview (symbol,exchange,interval,count,start,end)
+            SELECT symbol,exchange,interval,COUNT(*),MIN(datetime),MAX(datetime)
+            FROM dbbardata GROUP BY symbol,exchange,interval"""
+        )
+        conn.commit()
+        conn.close()
+        logger.info("✅ vnpy DB [%s] 写入完成", label)
+    except Exception as e:
+        logger.error("❌ vnpy DB [%s] 写入失败: %s", label, e)
+
+
+# ======================== 主入口 ========================
+
+def main():
+    parser = argparse.ArgumentParser(description="全市场每日增量更新")
+    parser.add_argument("--skip-daily", action="store_true", help="跳过日线更新")
+    parser.add_argument("--skip-15min", action="store_true", help="跳过15分钟线更新")
+    args = parser.parse_args()
+
+    if not nas_mounted():
+        logger.error("❌ NAS未挂载，退出")
+        sys.exit(1)
+
+    codes = get_all_codes()
+    logger.info("全市场股票数: %d", len(codes))
+    logger.info("更新时间: %s", datetime.now().isoformat())
+
+    t_start = time.time()
+    report = {}
+
+    if not args.skip_daily:
+        report["daily"] = run_daily_update(codes)
+
+    if not args.skip_15min:
+        report["15min"] = run_15min_update(codes)
+
+    elapsed = time.time() - t_start
+    report["elapsed_sec"] = round(elapsed, 1)
+    logger.info("=" * 60)
+    logger.info("全部完成，耗时 %.1f 秒", elapsed)
+    logger.info(json.dumps(report, ensure_ascii=False, indent=2))
+
+    # 写入报告
+    report_file = LOG_DIR / f"report_{datetime.now().strftime('%Y%m%d')}.json"
+    report_file.write_text(json.dumps(report, ensure_ascii=False, indent=2))
+
+    return report
+
+
+if __name__ == "__main__":
+    main()