claude_dev
f94a145587
根因(py-spy dump + netstat CLOSE_WAIT 实证): baostock 服务端关长连接→CLOSE_WAIT, send_msg 静默阻塞不抛异常, socket.setdefaulttimeout 不被 baostock 自己 socket 遵守, relogin 只在 error_code≠0 救不了; 一把大事务全程持 WAL 锁阻断全库。修复: per-stock commit 去大事务 + _with_timeout 线程超时包 fetch_k 打破静默 hang + 周期 relogin 每500主动刷连接。VPS --limit 3 验证 11s 不 hang。
354 lines
14 KiB
Python
354 lines
14 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""bs_eod.py — sanguo-bs-eod (方案A schtask 18:05): baostock 个股 EOD 增量。
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每日收盘后跑(VPS, baostock 日终更新就绪):
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- 个股日线(含退市, LOOKBACK 7 天) -> dbbardata('d') INSERT OR REPLACE (治幸存者偏差)
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- 个股 15min(LOOKBACK 7) -> dbbardata('15m')
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- 日线 pe/pb/turn/pctChg/isST -> data/valuation_baostock/<year>.parquet 追加
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- DAILY_LIMIT=48000 单进程单登录, sleep 0.3s, login 探针 graceful skip
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预算: 5537股 × (1日线+1 15min) ≈ 11000 query/天 = 48000 的 23%, 安全。
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退出码: 0=完成; 1=致命; 2=黑名单 graceful skip; 3=query 超限 graceful stop
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"""
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import argparse
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import datetime as dt
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import logging
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import os
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import socket
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import sys
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import threading
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import time
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from pathlib import Path
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for _k in ("http_proxy", "https_proxy", "HTTP_PROXY", "HTTPS_PROXY", "all_proxy", "ALL_PROXY"):
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os.environ.pop(_k, None)
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socket.setdefaulttimeout(30)
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try:
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sys.stdout.reconfigure(line_buffering=True)
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except (AttributeError, ValueError):
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pass
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import baostock as bs
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import pandas as pd
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from dbbardata_utils import normalize_daily_dt
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BASE = Path(r"C:\sanguo_vnpy_v2")
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DB = BASE / "data" / "quant_trading.db"
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VAL_DIR = BASE / "data" / "valuation_baostock"
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LOOKBACK = int(os.environ.get("LOOKBACK_DAYS", "7"))
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DAILY_LIMIT = int(os.environ.get("BS_DAILY_LIMIT", "48000"))
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# ③ 周期 relogin: 每 N 只主动 relogin, 防服务端长连接 idle 超时 → CLOSE_WAIT 静默 hang.
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# CLOSE_WAIT 是静默阻塞不抛异常, 被动 relogin (error_code != 0 触发) 救不了, 必须周期主动刷连接.
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RELOGIN_EVERY = int(os.environ.get("BS_RELOGIN_EVERY", "500"))
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BS_INTERVAL = 0.3
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QUERY_COUNT = 0
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EXC_MAP = {"sh": "SSE", "sz": "SZSE"}
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DAILY_FIELDS = ("date,code,open,high,low,close,volume,amount,turn,"
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"pctChg,peTTM,psTTM,pcfNcfTTM,pbMRQ,isST")
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M15_FIELDS = "date,time,code,open,high,low,close,volume,amount"
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logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s",
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handlers=[logging.StreamHandler(sys.stdout)])
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log = logging.getLogger(__name__)
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def login_once():
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try:
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lg = bs.login()
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if lg.error_code == "0":
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return True
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log.error("login fail: %s %s", lg.error_code, lg.error_msg)
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return False
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except Exception as e:
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log.error("login exc: %s", e)
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return False
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def relogin():
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try:
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bs.logout()
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except Exception:
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pass
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if login_once():
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return True
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time.sleep(2)
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try:
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bs.logout()
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except Exception:
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pass
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return login_once()
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def fetch_all_stocks():
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"""query_stock_basic() 无参 -> 全 A 含退市 (type=1)。返回 [(code, 'sh'/'sz')]。"""
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global QUERY_COUNT
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QUERY_COUNT += 1
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rs = bs.query_stock_basic()
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if rs.error_code != "0":
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raise RuntimeError(f"query_stock_basic: {rs.error_code} {rs.error_msg}")
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fields = list(rs.fields)
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idx = {n: i for i, n in enumerate(fields)}
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out = []
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while rs.next():
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r = rs.get_row_data()
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if r[idx["type"]] != "1":
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continue
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bc = r[idx["code"]]
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if "." not in bc:
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continue
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prefix, num = bc.split(".", 1)
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if prefix in ("sh", "sz") and len(num) == 6 and num.isdigit():
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out.append((num, prefix))
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return out
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def fetch_k(bs_code, fields, freq, start, end):
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global QUERY_COUNT
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QUERY_COUNT += 1
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rs = bs.query_history_k_data_plus(bs_code, fields, start_date=start,
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end_date=end, frequency=freq, adjustflag="3")
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if rs.error_code != "0":
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raise RuntimeError(f"{bs_code}: {rs.error_code} {rs.error_msg}")
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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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return rows
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# ======================== 超时包装 ========================
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# 根因: socket.setdefaulttimeout(30) 对 baostock 客户端的 rs.next() / recv 不可靠遵守,
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# 服务端 hiccup 会无限阻塞主循环. 用 daemon 工作线程 + join(timeout) 强制上限.
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#
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# 线程方案 vs subprocess 隔离: 选线程.
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# 理由: (1) baostock 模块级 singleton, 主线程 join 等子线程 → 单线程串行调用安全;
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# (2) 超时后子线程 daemon 化泄漏, 后续 relogin 的 logout 关旧 socket → 旧线程
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# recv 报错自死, 新 login 走新 socket 不受污染 (relogin retry 兜底恢复);
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# (3) subprocess 方案需重新 login (~1s) + 序列化 rows 复杂, 不值;
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# (4) 与 akshare_static_download.call_ak_with_timeout 同范式.
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def _with_timeout(fn, args=(), kwargs=None, timeout=60):
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"""daemon 线程跑 fn(*args, **kwargs), timeout 秒未完成 raise TimeoutError.
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超时后工作线程泄漏 (daemon=True, 进程退出时强杀); 主线程立即返回让上层 relogin.
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子线程异常透传给主线程 (BaseException 也捕获, 避免 daemon 吞 KeyboardInterrupt).
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"""
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if kwargs is None:
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kwargs = {}
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box = {"val": None, "exc": None}
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def worker():
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try:
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box["val"] = fn(*args, **kwargs)
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except BaseException as e: # noqa: BLE001 - 透传所有异常含 KeyboardInterrupt
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box["exc"] = e
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t = threading.Thread(target=worker, daemon=True)
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t.start()
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t.join(timeout)
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if t.is_alive():
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raise TimeoutError(f"{getattr(fn, '__name__', repr(fn))} 超过 {timeout}s")
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if box["exc"] is not None:
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raise box["exc"]
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return box["val"]
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def fetch_k_with_timeout(bs_code, fields, freq, start, end, timeout=60):
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"""fetch_k + 超时保护 (默认 60s; baostock hiccup 不再无限阻塞)."""
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return _with_timeout(
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fetch_k,
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args=(bs_code, fields, freq, start, end),
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timeout=timeout,
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)
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def fetch_all_stocks_with_timeout(timeout=120):
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"""fetch_all_stocks + 超时保护 (全 A 列表一次性返回, 给 120s)."""
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return _with_timeout(fetch_all_stocks, timeout=timeout)
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def upsert_daily(conn, code, prefix, rows):
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"""日线 rows -> dbbardata('d') + valuation_baostock 当年 parquet 追加。"""
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if not rows:
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return 0
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df = pd.DataFrame(rows, columns=DAILY_FIELDS.split(","))
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for c in ["open", "high", "low", "close", "volume", "amount",
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"turn", "pctChg", "peTTM", "psTTM", "pcfNcfTTM", "pbMRQ"]:
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df[c] = pd.to_numeric(df[c], errors="coerce")
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exc = EXC_MAP[prefix]
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# OHLCV -> dbbardata('d') — datetime 归一纯日期 (dbbardata 双行根治方案A)
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db = pd.DataFrame({
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"symbol": code, "exchange": exc,
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"datetime": df["date"].astype(str).map(normalize_daily_dt),
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"interval": "d", "volume": df["volume"], "turnover": df["amount"],
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"open_interest": 0.0,
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"open_price": df["open"], "high_price": df["high"],
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"low_price": df["low"], "close_price": df["close"],
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})
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conn.executemany(
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"INSERT OR REPLACE INTO dbbardata "
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"(symbol,exchange,datetime,interval,volume,turnover,open_interest,"
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"open_price,high_price,low_price,close_price) VALUES (?,?,?,?,?,?,?,?,?,?,?)",
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db.itertuples(index=False, name=None))
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# pe/pb -> parquet 追加 (isST->int, 修 pyarrow ArrowTypeError)
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vdf = df[["date", "peTTM", "psTTM", "pcfNcfTTM", "pbMRQ", "turn", "pctChg", "isST"]].copy()
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vdf["isST"] = pd.to_numeric(vdf["isST"], errors="coerce").fillna(0).astype(int)
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vdf.insert(0, "symbol", code)
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vdf.insert(1, "exchange", exc)
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yr = dt.date.today().year
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p = VAL_DIR / f"{yr}.parquet"
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if p.exists():
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try:
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old = pd.read_parquet(p)
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vdf = pd.concat([old, vdf]).drop_duplicates(["symbol", "date"], keep="last")
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except Exception:
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pass
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vdf.sort_values(["symbol", "date"]).to_parquet(p, index=False)
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return len(db)
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def _build_15m_dt(date_series, time_series):
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"""baostock 15min datetime 拼接: date="2026-07-21"(带 -) + time="20260721094500000"(17 位)。
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从 17 位 time 第 8-12 位提取 HHMM, date 直连(带 -)。
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产出 'YYYY-MM-DD HH:MM:00' (符合 dbbardata GLOB 模式, 不被清理误删)。
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bug 根因(2026-07-25): 原代码假设 date 纯数字 + time[:6] 取年月,
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但 baostock 实测 date 带 -, time[:6]=YYYYMM, 产乱 datetime 致 15min 全市场停 7-17。
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"""
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_t = time_series.astype(str)
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return (date_series.astype(str) + " "
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+ _t.str.slice(8, 10) + ":" + _t.str.slice(10, 12) + ":00")
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def upsert_15m(conn, code, prefix, rows):
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if not rows:
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return 0
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df = pd.DataFrame(rows, columns=M15_FIELDS.split(","))
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for c in ["open", "high", "low", "close", "volume", "amount"]:
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df[c] = pd.to_numeric(df[c], errors="coerce")
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exc = EXC_MAP[prefix]
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dt_col = _build_15m_dt(df["date"], df["time"])
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db = pd.DataFrame({
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"symbol": code, "exchange": exc, "datetime": dt_col,
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"interval": "15m", "volume": df["volume"], "turnover": df["amount"],
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"open_interest": 0.0,
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"open_price": df["open"], "high_price": df["high"],
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"low_price": df["low"], "close_price": df["close"],
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})
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conn.executemany(
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"INSERT OR REPLACE INTO dbbardata "
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"(symbol,exchange,datetime,interval,volume,turnover,open_interest,"
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"open_price,high_price,low_price,close_price) VALUES (?,?,?,?,?,?,?,?,?,?,?)",
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db.itertuples(index=False, name=None))
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return len(db)
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def _process_one_stock(conn, code, prefix, args, start, end):
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"""单只股票: fetch_k + upsert, 在 with conn 短事务里执行 (大事务根治).
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每只股票一个事务 — hang/kill/异常最多丢 1 只, 已 commit 的其他股不受影响.
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fetch 也包在事务里 (task 要求: "fetch_k + upsert 包在自己事务里");
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fetch 用 fetch_k_with_timeout 保护, 网络挂最多锁 timeout 秒.
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成功返 (n1_daily, n2_15m); 异常时 with conn 自动 ROLLBACK 该股, 异常上抛.
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"""
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bs_code = f"{prefix}.{code}"
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n1 = 0
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n2 = 0
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with conn: # 显式短事务: 成功 commit / 异常 rollback (per-stock 原子)
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if not args.no_daily:
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d_rows = fetch_k_with_timeout(bs_code, DAILY_FIELDS, "d", start, end)
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n1 = upsert_daily(conn, code, prefix, d_rows)
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if not args.no_15m:
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m_rows = fetch_k_with_timeout(bs_code, M15_FIELDS, "15", start, end)
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n2 = upsert_15m(conn, code, prefix, m_rows)
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return n1, n2
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def main():
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global QUERY_COUNT
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ap = argparse.ArgumentParser()
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ap.add_argument("--limit", type=int, default=0)
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ap.add_argument("--no-15m", action="store_true")
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ap.add_argument("--no-daily", action="store_true",
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help="跳日线, 只跑 15min(用于 15min 重灌快)")
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args = ap.parse_args()
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today = dt.date.today()
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end = today.strftime("%Y-%m-%d")
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start = (today - dt.timedelta(days=LOOKBACK)).strftime("%Y-%m-%d")
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log.info("bs_eod start window=%s~%s LOOKBACK=%d limit=%s", start, end, LOOKBACK, args.limit or "无")
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if not login_once():
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log.error("[SKIP] baostock 黑名单/冷却, graceful exit 2")
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sys.exit(2)
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try:
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stocks = fetch_all_stocks_with_timeout()
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except Exception as e:
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log.error("[FATAL] fetch_all: %s", e)
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sys.exit(1)
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log.info("全 A 含退市: %d 只", len(stocks))
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if args.limit:
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stocks = stocks[:args.limit]
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import sqlite3
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VAL_DIR.mkdir(parents=True, exist_ok=True)
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conn = sqlite3.connect(str(DB), timeout=60)
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conn.execute("PRAGMA busy_timeout = 60000")
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conn.execute("PRAGMA journal_mode = WAL")
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stats = {"ok": 0, "empty": 0, "failed": 0, "db_rows": 0}
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limit_reached = False
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t0 = time.time()
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# 大事务根治: 不再 BEGIN/COMMIT 包全程. 每只股票 with conn 短事务独立提交,
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# hang/kill/崩溃最多丢 1 只 (per-stock 隔离), 已 commit 的进度不丢.
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try:
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for i, (code, prefix) in enumerate(stocks):
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if QUERY_COUNT >= DAILY_LIMIT:
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log.warning("query %d 达防线 %d, graceful stop", QUERY_COUNT, DAILY_LIMIT)
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limit_reached = True
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break
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try:
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n1, n2 = _process_one_stock(conn, code, prefix, args, start, end)
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stats["db_rows"] += n1 + n2
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if n1 + n2:
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stats["ok"] += 1
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else:
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stats["empty"] += 1
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except Exception as e:
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# _process_one_stock 异常已 rollback 该股, 其他股已 commit 不受影响
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stats["failed"] += 1
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if stats["failed"] <= 5 or stats["failed"] % 100 == 0:
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log.warning("%s err: %s", code, e)
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if not relogin():
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log.error("%s relogin 失败, 跳过", code)
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if (i + 1) % RELOGIN_EVERY == 0:
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log.info("进度 %d/%d ok=%d empty=%d failed=%d q=%d (%.0fs)",
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i + 1, len(stocks), stats["ok"], stats["empty"],
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stats["failed"], QUERY_COUNT, time.time() - t0)
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# ③ 主动 relogin (双保险之治本): 服务端长连接 idle 超时 → CLOSE_WAIT 静默 hang,
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# 被动 relogin 不触发 (不抛异常), 必须周期主动 logout+login 刷新连接.
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# ② _with_timeout 是治标兜底, 真挂了能打破; 这里治本避免走到那一步.
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if not relogin():
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log.warning("周期 relogin 失败, 继续跑 (下次 fetch 失败时被动 relogin 兜底)")
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if i < len(stocks) - 1:
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time.sleep(BS_INTERVAL)
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finally:
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conn.close()
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try:
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bs.logout()
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except Exception:
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pass
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log.info("[DONE] ok=%d empty=%d failed=%d db_rows=%d query=%d 耗时%.0fs",
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stats["ok"], stats["empty"], stats["failed"], stats["db_rows"],
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QUERY_COUNT, time.time() - t0)
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sys.exit(3 if limit_reached else 0)
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if __name__ == "__main__":
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main()
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