feat: 修复daily历史覆盖度缺口+增加覆盖度校验

- 新增 repair_daily_backfill.py:按daily_basic基准检测并补拉覆盖不足交易日
  (解决2012-2013沪市+创业板整年缺失问题,断点续传日期级检测无法发现)
- importer.py: 新增 check_daily_coverage() 覆盖度审计函数
- incremental_import.py: 增量导入后自动跑覆盖度校验并告警
- 数据批量导入.ipynb: 增加数据完整性检验单元格
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xiaoqiang
2026-08-26 10:47:32 +00:00
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
修复 daily 表历史覆盖度缺口(2012-2013 沪市+创业板缺失)
背景:daily 表 2012-2013 年只有深市主板/中小板(2012 年 1383 只、2013 年 677 只),
缺全部沪市 + 创业板。原因:当年全量导入沪市请求失败/中断,但深市成功,
导致断点续传的"日期级"缺失检测(NOT EXISTS trade_date)认为该日已有数据,
永不补拉。
修复策略(覆盖度级校验):
1. 对指定日期范围,对比 daily 与 daily_basic 的当日去重股票数
(daily_basic 同期数据完整,作为覆盖度基准)
2. daily 当日股票数 < daily_basic 当日股票数 × (1 - tolerance) 的日期 → 判定为"部分缺失"
3. 部分缺失的日期按全市场重新拉取(Tushare daily 按 trade_date 返回全市场)
4. 用 INSERT ON CONFLICT DO NOTHING 幂等写入,可重复执行
用法:
python3 repair_daily_backfill.py [--start 2012-01-01] [--end 2013-12-31] [--tolerance 0.05] [--dry-run]
"""
import os
import sys
import time
import argparse
import logging
from datetime import datetime
HERE = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, HERE)
# 显式加载 .env(config.py 会加载,但确保顺序正确)
try:
from dotenv import load_dotenv
env_path = os.path.join(HERE, ".env")
if os.path.exists(env_path):
load_dotenv(env_path, override=False)
except ImportError:
pass
import importer
from importer import (
get_pg_connection, get_ts_pro, batch_insert,
fetch_with_retry, _normalize_daily_df,
)
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(message)s",
handlers=[
logging.FileHandler(os.path.join(HERE, "repair_daily_backfill.log"), encoding="utf-8"),
logging.StreamHandler(),
],
)
logger = logging.getLogger("repair_daily_backfill")
def get_coverage_ratio(conn, trade_date: str) -> tuple:
"""返回 (daily_stocks, daily_basic_stocks)。无参考数据时 daily_basic_stocks=None"""
cur = conn.cursor()
try:
cur.execute("SELECT COUNT(DISTINCT ts_code) FROM daily WHERE trade_date=%s", (trade_date,))
d_cnt = cur.fetchone()[0]
cur.execute("SELECT COUNT(DISTINCT ts_code) FROM daily_basic WHERE trade_date=%s", (trade_date,))
db_cnt = cur.fetchone()[0]
return d_cnt, db_cnt
finally:
cur.close()
def find_partial_dates(conn, start_date: str, end_date: str, tolerance: float) -> list:
"""
找出 daily 覆盖度不足的交易日(单条 SQL 聚合,避免逐日查询)。
返回 [(trade_date, daily_cnt, daily_basic_cnt), ...]
判据:daily_basic 有数据且 daily 股票数 < daily_basic × (1 - tolerance)
"""
cur = conn.cursor()
try:
cur.execute(
"""
SELECT db.trade_date,
COALESCE(d.cnt, 0) AS daily_cnt,
db.cnt AS db_cnt
FROM (SELECT trade_date, COUNT(DISTINCT ts_code) AS cnt
FROM daily_basic
WHERE trade_date BETWEEN %s AND %s
GROUP BY trade_date) db
LEFT JOIN (SELECT trade_date, COUNT(DISTINCT ts_code) AS cnt
FROM daily
WHERE trade_date BETWEEN %s AND %s
GROUP BY trade_date) d
ON d.trade_date = db.trade_date
WHERE COALESCE(d.cnt, 0) < db.cnt * (1 - %s)
ORDER BY db.trade_date
""",
(start_date, end_date, start_date, end_date, tolerance),
)
partial = [(r[0].strftime("%Y-%m-%d"), r[1], r[2]) for r in cur.fetchall()]
finally:
cur.close()
return partial
def backfill_date(pro, conn, td_str: str) -> bool:
"""拉取单个交易日全市场 daily 数据并写入。成功返回 True"""
td_compact = td_str.replace("-", "")
def fetch():
return pro.daily(trade_date=td_compact)
df = fetch_with_retry(fetch, max_retries=4, delay=3)
if df is None or df.empty:
logger.warning(f" [{td_str}] 返回空数据,跳过")
return False
df = _normalize_daily_df(df)
# 幂等写入:已存在的行跳过(ON CONFLICT DO NOTHING)
batch_insert("daily", df, conn, ["ts_code", "trade_date"])
return True
def main():
parser = argparse.ArgumentParser(description="修复 daily 表历史覆盖度缺口")
parser.add_argument("--start", default="2012-01-01", help="起始日期 YYYY-MM-DD")
parser.add_argument("--end", default="2013-12-31", help="结束日期 YYYY-MM-DD")
parser.add_argument("--tolerance", type=float, default=0.05,
help="覆盖度容差,默认 0.05(daily 少于 daily_basic 的 95% 即判定缺失)")
parser.add_argument("--dry-run", action="store_true", help="只扫描不导入")
args = parser.parse_args()
conn = get_pg_connection()
logger.info("=" * 60)
logger.info(f"[覆盖度扫描] {args.start} ~ {args.end} (容差 {args.tolerance:.0%})")
partial = find_partial_dates(conn, args.start, args.end, args.tolerance)
if not partial:
logger.info(" 未发现覆盖度不足的交易日 ✅")
conn.close()
return
logger.info(f" 发现 {len(partial)} 个覆盖度不足的交易日:")
# 按年份统计
years = {}
for td, d_cnt, db_cnt in partial:
y = td[:4]
years.setdefault(y, []).append((td, d_cnt, db_cnt))
for y in sorted(years):
lst = years[y]
logger.info(f" {y} 年: {len(lst)} 个交易日 | 样例 {lst[0][0]}(daily={lst[0][1]}/db={lst[0][2]})")
if args.dry_run:
logger.info("[dry-run] 不执行导入,以上为待补拉清单")
conn.close()
return
pro = get_ts_pro()
success = 0
fail_list = []
for i, (td, d_cnt, db_cnt) in enumerate(partial, 1):
ok = backfill_date(pro, conn, td)
if ok:
success += 1
else:
fail_list.append(td)
if i % 20 == 0 or i == len(partial):
logger.info(f" 进度: {i}/{len(partial)} 成功={success} 失败={len(fail_list)}")
time.sleep(0.35) # 限流保护
conn.close()
logger.info(f" 补拉完成: 成功 {success}/{len(partial)}")
if fail_list:
logger.warning(f" 失败日期({len(fail_list)}): {fail_list[:20]}...")
# 写失败清单供重试
with open(os.path.join(HERE, "repair_failed_dates.txt"), "w") as f:
f.write("\n".join(fail_list))
if __name__ == "__main__":
main()