#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""dbbardata_probe.py — 只读探测 dbbardata 现状(schema + 抽样各 interval 覆盖)。

走 symbol 索引,避免全表 COUNT(亿级慢)。回答:
  - dbbardata 有哪些 interval(d/15m/5m)
  - 个股日线(interval='d' 类)含不含退市股(000005/000023/600811/600074)
  - 在市股(600519/000001)日线日期范围
  - ETF(510300/159915)有没有(判断 dbbardata 是否覆盖 ETF)
用于决定迁移单元5(dbbardata 个股日线切 baostock 源)的工作量。
"""
import sqlite3
from pathlib import Path

DB = Path(r"C:\sanguo_vnpy_v2\data\quant_trading.db")
c = sqlite3.connect(str(DB), timeout=60)
c.execute("PRAGMA busy_timeout = 60000")

cols = [r[1] for r in c.execute("PRAGMA table_info(dbbardata)")]
print(f"DB: {DB}")
print(f"dbbardata cols({len(cols)}): {cols}")

print("\n=== 抽样: 各 symbol 的 interval 覆盖 (走索引, 快) ===")
samples = {
    "退市": ["000005", "000023", "600811", "600074"],
    "在市个股": ["600519", "000001"],
    "ETF/基金": ["510300", "159915", "510050"],
}
for label, syms in samples.items():
    print(f"\n[{label}]")
    for sym in syms:
        rows = c.execute(
            "SELECT interval, COUNT(*), MIN(datetime), MAX(datetime) "
            "FROM dbbardata WHERE symbol=? GROUP BY interval",
            (sym,),
        ).fetchall()
        print(f"  {sym}: {rows}")

c.close()