cfdaily
304 lines
9.8 KiB
Python
304 lines
9.8 KiB
Python
#!/usr/bin/env python3
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"""
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BaoStock 15分钟线历史回补脚本 (v1.1)
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功能：用BaoStock免费数据源全量重建全市场15分钟K线历史数据
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策略：
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- 全量重建：BaoStock获取完整历史，完全替换旧parquet
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- 旧文件备份到 backup/ 目录
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- 增量模式：已有BaoStock重建过的文件自动跳过（检查标记）
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BaoStock特点：
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- 无反爬限制，0.35s/只
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- 不复权数据（adjustflag=3）
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- 分钟线从1999年起，我们取2024-01-01起
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用法：
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python3 backfill_15min_baostock.py # 全量回补
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python3 backfill_15min_baostock.py --start 20200101 # 指定起始日期
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python3 backfill_15min_baostock.py --limit 10 # 只处理前10只（测试）
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python3 backfill_15min_baostock.py --force # 强制重建（覆盖已有BaoStock数据）
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变更记录：
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v1.0 (2026-05-05) 赵云创建
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v1.1 (2026-05-05) 修复：旧新浪数据含后复权值，改为全量重建模式
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"""
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import argparse
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import json
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import logging
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import os
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import shutil
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import sys
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import time
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from datetime import datetime
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from pathlib import Path
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from typing import List, Optional, Tuple
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import baostock as bs
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import pandas as pd
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# ======================== 配置 ========================
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NAS_ROOT = Path("/Volumes/stock")
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MINUTE_15_DIR = NAS_ROOT / "minute_kline" / "15min"
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BACKUP_DIR = MINUTE_15_DIR / "backup_sina" # 旧新浪数据备份
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LOG_DIR = NAS_ROOT / "logs" / "daily_update"
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PROGRESS_DIR = LOG_DIR / "progress"
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ALL_STOCKS_FILE = NAS_ROOT / "A股数据" / "stock_info" / "all_stocks.csv"
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# BaoStock配置
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BS_START_DATE = "2024-01-01"
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BS_INTERVAL = 0.4 # 请求间隔秒
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BS_MAX_RETRIES = 2
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PROGRESS_SAVE_EVERY = 500
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# ======================== 日志 ========================
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def setup_logging():
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LOG_DIR.mkdir(parents=True, exist_ok=True)
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ts = datetime.now().strftime("%Y%m%d_%H%M%S")
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log_file = LOG_DIR / f"backfill_15min_{ts}.log"
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s %(levelname)s %(message)s",
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handlers=[
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logging.FileHandler(log_file, encoding="utf-8"),
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logging.StreamHandler(),
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],
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)
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return logging.getLogger(__name__)
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logger = setup_logging()
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# ======================== 工具函数 ========================
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def get_all_codes() -> List[str]:
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df = pd.read_csv(ALL_STOCKS_FILE)
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for col in ["代码", "code", "股票代码"]:
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if col in df.columns:
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return [str(c).zfill(6) for c in df[col].tolist()]
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raise ValueError(f"找不到代码列: {list(df.columns)}")
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def code_to_baostock(code: str) -> Tuple[str, str]:
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"""6位代码 → (BaoStock格式, parquet前缀)"""
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if code.startswith(("6", "68", "51")):
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return f"sh.{code}", "sh"
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else:
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return f"sz.{code}", "sz"
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def is_backfilled(parquet_path: Path) -> bool:
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"""检查文件是否已经被BaoStock回补过"""
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# 用标记文件判断
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marker = parquet_path.parent / f".{parquet_path.stem}.baostock"
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return marker.exists()
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def load_progress() -> set:
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progress_file = PROGRESS_DIR / "backfill_15min_progress.json"
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if progress_file.exists():
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try:
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return set(json.loads(progress_file.read_text()).get("done", []))
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except Exception:
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pass
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return set()
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def save_progress(done_set: set):
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PROGRESS_DIR.mkdir(parents=True, exist_ok=True)
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progress_file = PROGRESS_DIR / "backfill_15min_progress.json"
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progress_file.write_text(json.dumps({
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"done": sorted(done_set),
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"ts": datetime.now().isoformat(),
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}, ensure_ascii=False))
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# ======================== 核心逻辑 ========================
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def fetch_bs_15min(bs_code: str, start_date: str, end_date: str) -> Optional[pd.DataFrame]:
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"""从BaoStock获取15min不复权数据"""
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rs = bs.query_history_k_data_plus(
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bs_code,
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"date,time,code,open,high,low,close,volume,amount,adjustflag",
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start_date=start_date,
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end_date=end_date,
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frequency="15",
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adjustflag="3", # 不复权
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)
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if rs.error_code != "0":
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logger.debug("BaoStock %s 错误: %s %s", bs_code, rs.error_code, rs.error_msg)
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return None
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rows = []
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while rs.next():
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rows.append(rs.get_row_data())
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if not rows:
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return None
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df = pd.DataFrame(rows, columns=["date", "time", "code", "open", "high", "low",
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"close", "volume", "amount", "adjustflag"])
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# 转换时间格式: 20260428094500000 → 2026-04-28 09:45:00
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df["day"] = df["time"].apply(lambda t: f"{t[:4]}-{t[4:6]}-{t[6:8]} {t[8:10]}:{t[10:12]}:00")
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# 数值转换
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for col in ["open", "high", "low", "close"]:
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df[col] = pd.to_numeric(df[col], errors="coerce")
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df["volume"] = df["volume"].astype(str)
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df["amount"] = df["amount"].astype(str)
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# 保留与parquet一致的列
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df = df[["day", "open", "high", "low", "close", "volume", "amount"]]
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# 过滤无效数据
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df = df.dropna(subset=["open", "high", "low", "close"])
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bad_ohlc = (df["high"] < df[["open", "close"]].max(axis=1)) | \
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(df["low"] > df[["open", "close"]].min(axis=1))
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if bad_ohlc.any():
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df = df[~bad_ohlc]
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return df if not df.empty else None
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def backfill_one(code: str, start_date: str, end_date: str, force: bool = False) -> Tuple[str, int]:
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"""
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全量重建单只股票的15min历史
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返回: (status, total_rows)
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"""
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bs_code, prefix = code_to_baostock(code)
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parquet_path = MINUTE_15_DIR / f"{prefix}{code}_15min.parquet"
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# 已回补过的跳过
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if not force and is_backfilled(parquet_path):
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return "skipped", 0
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# 获取BaoStock数据
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df_new = None
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for attempt in range(BS_MAX_RETRIES):
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try:
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df_new = fetch_bs_15min(bs_code, start_date, end_date)
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if df_new is not None and len(df_new) > 0:
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break
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except Exception as e:
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logger.debug("backfill %s 重试%d: %s", code, attempt + 1, e)
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time.sleep(1)
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if df_new is None or df_new.empty:
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return "failed", 0
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# 备份旧文件
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if parquet_path.exists():
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BACKUP_DIR.mkdir(parents=True, exist_ok=True)
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backup_path = BACKUP_DIR / parquet_path.name
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if not backup_path.exists(): # 不覆盖已有备份
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shutil.copy2(str(parquet_path), str(backup_path))
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# 写入新文件
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try:
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df_new = df_new.sort_values("day").reset_index(drop=True)
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df_new.to_parquet(parquet_path, index=False)
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# 写标记文件
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marker = parquet_path.parent / f".{parquet_path.stem}.baostock"
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marker.write_text(datetime.now().isoformat())
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return "ok", len(df_new)
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except Exception as e:
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logger.error("写入 %s 失败: %s", code, e)
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return "failed", 0
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# ======================== 主流程 ========================
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def main():
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parser = argparse.ArgumentParser(description="BaoStock 15min历史回补（全量重建）")
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parser.add_argument("--start", default=BS_START_DATE, help="回补起始日期 (YYYYMMDD)")
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parser.add_argument("--end", default="", help="结束日期 (默认今天)")
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parser.add_argument("--codes", help="指定股票代码，逗号分隔")
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parser.add_argument("--limit", type=int, default=0, help="限制处理数量（测试用）")
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parser.add_argument("--force", action="store_true", help="强制重建（覆盖已有BaoStock数据）")
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args = parser.parse_args()
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start_date = f"{args.start[:4]}-{args.start[4:6]}-{args.start[6:8]}"
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end_date = f"{args.end[:4]}-{args.end[4:6]}-{args.end[6:8]}" if args.end else datetime.now().strftime("%Y-%m-%d")
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if not NAS_ROOT.exists():
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logger.error("❌ NAS未挂载")
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sys.exit(1)
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# 登录BaoStock
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lg = bs.login()
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if lg.error_code != "0":
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logger.error("❌ BaoStock登录失败: %s", lg.error_msg)
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sys.exit(1)
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logger.info("✅ BaoStock登录成功")
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# 获取股票列表
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if args.codes:
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codes = [c.strip() for c in args.codes.split(",")]
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else:
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codes = get_all_codes()
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if args.limit > 0:
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codes = codes[:args.limit]
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logger.info("=" * 60)
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logger.info("BaoStock 15min全量重建开始")
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logger.info(f" 股票数: {len(codes)}")
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logger.info(f" 日期范围: {start_date} ~ {end_date}")
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logger.info(f" 数据目录: {MINUTE_15_DIR}")
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logger.info(f" 旧数据备份: {BACKUP_DIR}")
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# 进度恢复
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done_set = load_progress()
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if args.force:
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todo = codes # 强制模式不跳过
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else:
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todo = [c for c in codes if c not in done_set]
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logger.info(f" 待处理: {len(todo)}（已完成: {len(done_set)}）")
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stats = {"ok": 0, "skipped": 0, "failed": 0, "rows": 0}
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t_start = time.time()
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for i, code in enumerate(todo):
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try:
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status, total_rows = backfill_one(code, start_date, end_date, args.force)
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except Exception as e:
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status, total_rows = "failed", 0
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logger.debug("backfill %s 异常: %s", code, e)
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stats[status] = stats.get(status, 0) + 1
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if status == "ok":
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stats["rows"] += total_rows
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done_set.add(code)
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if (i + 1) % PROGRESS_SAVE_EVERY == 0:
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save_progress(done_set)
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elapsed = time.time() - t_start
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logger.info("进度: %d/%d ok=%d skipped=%d failed=%d rows=%d (%.0f秒)",
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i + 1, len(todo), stats["ok"], stats["skipped"],
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stats["failed"], stats["rows"], elapsed)
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# 频率控制
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if i < len(todo) - 1:
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time.sleep(BS_INTERVAL)
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# 保存最终进度
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save_progress(done_set)
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bs.logout()
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elapsed = time.time() - t_start
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logger.info("=" * 60)
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logger.info("✅ 回补完成，耗时 %.1f 秒", elapsed)
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logger.info("统计: %s", json.dumps(stats, ensure_ascii=False))
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if __name__ == "__main__":
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main()
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