claude_dev
c2a89d01a4
spec §14 方案A 数据层迁移完成 + E2E 验证(read_db_daily: 在市/退市治偏差/ETF 全OK):
- dbbardata('d') 1826万含退市(治回测幸存者偏差, INSERT OR REPLACE staging迁移, WHERE OHLC NOT NULL+COALESCE)
- constituent_unified 7110行/9指数(300/500/50 baostock全集 + 深证4指 akshare cni union + 中证1000/2000 snapshot)
- pe/pb 不进DB -> valuation_baostock/<year>.parquet 按年宽表(2003-2026)
- 废弃 daily_baostock_full/bs_index_constituent(rename _old 保留); 旧4 schtask disabled
- 新 schtask sanguo-bs-eod 18:05(baostock个股日线+15min+拆pe/pb DAILY_LIMIT 48000) + sanguo-xt-eod 18:40(ETF/基金xtata)
- 权威源: baostock个股日线+估值+15min+复权+300/500/50 / xtata ETF+基金+当天实时 / akshare三表+事件+深证中证成份股
- 全程备份+staging+_old保留可回滚; 脚本 audit/probe/migrate/merge/cleanup/fix_config/verify/bs_eod/xt_eod/wrapper/register_schtasks
- 待办(spec §6 使用层): LocalParquetProvider 接 constituent_unified+valuation_baostock + 实时拼接
38 lines
1.5 KiB
Python
38 lines
1.5 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""probe_constituent.py — 单元3 前置: 探查成份股两源 schema (写 migrate 前必须看清)。
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1. bs_index_constituent (DB, baostock 300/500/50 历史): cols/rows/distinct index_code/抽样
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2. data/index_const_hist/*.parquet (akshare cni 深证 union): 文件列表 + 每个 shape/cols/抽样
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"""
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import glob
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import os
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import sqlite3
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import pandas as pd
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DB = r"C:\sanguo_vnpy_v2\data\quant_trading.db"
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HIST = r"C:\sanguo_vnpy_v2\data\index_const_hist"
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c = sqlite3.connect(DB, timeout=60)
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c.execute("PRAGMA busy_timeout = 60000")
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cols = [r[1] for r in c.execute("PRAGMA table_info(bs_index_constituent)")]
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print("[bs_index_constituent] cols:", cols)
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print(" rows:", c.execute("SELECT COUNT(*) FROM bs_index_constituent").fetchone()[0])
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idx = [r[0] for r in c.execute(
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"SELECT DISTINCT index_code FROM bs_index_constituent ORDER BY index_code")]
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print(" distinct index_code:", idx)
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print(" distinct updateDate count:", c.execute(
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"SELECT COUNT(DISTINCT updateDate) FROM bs_index_constituent").fetchone()[0])
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print(" sample rows:", c.execute(
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"SELECT * FROM bs_index_constituent LIMIT 3").fetchall())
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c.close()
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print("\n[index_const_hist parquets]")
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files = sorted(glob.glob(os.path.join(HIST, "*.parquet")))
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print("files:", [os.path.basename(f) for f in files])
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for f in files:
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df = pd.read_parquet(f)
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print(f" {os.path.basename(f)}: shape={df.shape} cols={list(df.columns)}")
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print(f" head:\n{df.head(2).to_string()}")
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