claude_dev
ff84b3d4b0
D-3 模式A影子下单(spec §5): - bridge_client.py: QMT bridge HTTP客户端(urllib, X-Bridge-Token, 失败不抛返回None) - live_orchestrator: _shadow_trades_to_bridge 当日成交POST bridge(默认enabled=false) - persistence: paper_shadow_orders幂等表+save_shadow_order/is_trade_shadowed - config: data_platform.yaml加live段, token走env(BRIDGE_TOKEN) - to_bridge_code symbol转换与guess_exchange一致(2位前缀) 安全: enabled=false默认关+token走env+幂等防重复+影子失败不阻断live_step docs: phase3d-live-trading-design.md(D期完整设计)
255 lines
11 KiB
Python
255 lines
11 KiB
Python
"""C-S3 实走编排（task 2）：每日 live_step 单根推进。
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架构（简化，避开 APScheduler per-account 闭包注入）：
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- 容器 APScheduler 每日 20:30 调 live_runner.run_live_step（全局 job，遍历 live accounts）
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- live_step(account_id) 自包含：恢复状态 → 读当日 raw bar → engine.step → 存状态
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- 当日 raw 由 Mac launchd 增量推 NAS（run_daily_update.sh 加 raw 增量）
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状态恢复：cash=最后余额 / positions=paper_positions / pending=paper_pending_orders
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TODO（分期项）：prev_close 从昨日 raw close 读（首版用当日 open 兜底）；
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listing_days 从 IPO 日算（首版 stub 0）；realized_pnl 未恢复（归因次日重置）。
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"""
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import json
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import logging
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import os
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import sqlite3
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from datetime import datetime, timedelta
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from .account import Account
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from .cta_adapter import PaperCtaEngine
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from .engine import PaperEngine
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from .limit import lot_size_for
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from .models import AccountConfig, MatchSession, OrderSide, PaperOrder
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from .position_ledger import PositionLedger
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from .persistence import (
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load_last_balance, load_positions, save_positions,
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load_pending_orders, save_pending_orders,
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save_shadow_order, is_trade_shadowed,
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)
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from .strategy_runner import StrategyRunner
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logger = logging.getLogger(__name__)
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def _get_account(db_path: str, account_id: int) -> dict:
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with sqlite3.connect(db_path) as conn:
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conn.row_factory = sqlite3.Row
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return dict(conn.execute(
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"SELECT * FROM paper_accounts WHERE id=?", (account_id,)
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).fetchone())
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def _restore_ledger(positions: dict) -> dict:
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"""{symbol:{volume,frozen,avg_price}} → {symbol: PositionLedger}。"""
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return {sym: PositionLedger(sym, p["volume"], p.get("frozen", 0), p["avg_price"])
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for sym, p in positions.items()}
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def live_step(db_path: str, account_id: int, data_source, cfg, today: str | None = None) -> None:
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"""实走单日 step（scheduler 每日调）。data_source=_DataSourceWrapper, cfg=data 配置。
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today: 默认 datetime.now()；验证可指定历史日期（有 raw）。
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"""
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from sanguo_data.datareader import guess_exchange
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from sanguo_api.strategy_registry import get_strategy_class
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from vnpy.trader.utility import ArrayManager
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acc = _get_account(db_path, account_id)
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symbols = json.loads(acc["symbols"] or "[]")
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strategies = json.loads(acc["strategies"] or "[]")
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interval = acc.get("interval") or "d"
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initial = acc["initial_capital"]
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# 1. 恢复 account（cash + positions）
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account = Account(initial)
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last_bal = load_last_balance(db_path, account_id)
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if last_bal:
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account.cash = last_bal["cash"]
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account.positions = _restore_ledger(load_positions(db_path, account_id, "account"))
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# 2. 构造 runners（恢复 positions）
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runners: list = []
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for s in strategies:
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cls = get_strategy_class(s["name"])
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if cls is None:
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continue
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cta = PaperCtaEngine(s["name"], match_session=s.get("match_session", "next_open"),
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listing_days=s.get("listing_days", 0),
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size=lot_size_for(s["symbol"]))
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vt = f"{s['symbol']}.{guess_exchange(s['symbol']).value}"
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strat = cls(cta, s["name"], vt, s.get("params", {}))
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strat.trading = True
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if not hasattr(strat, "am"):
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strat.am = ArrayManager(20)
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cta.set_strategy(strat)
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max_a = s.get("max_allocation")
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runner = StrategyRunner(s["name"], strategy=strat, paper_cta_engine=cta,
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symbol=s["symbol"],
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max_allocation=max_a if max_a is not None else initial)
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runner.positions = _restore_ledger(
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load_positions(db_path, account_id, f"strategy:{s['name']}"))
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runners.append(runner)
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if not runners:
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logger.warning("live_step %s: 无可用策略（容器缺 vnpy_ctastrategy？），跳过", account_id)
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return
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# 3. 日期 + warmup（重放 start~昨日到策略 am 使其 inited；丢弃 warmup 单）
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# 实走每日单根 bar，ArrayManager 需 warmup 才 inited，否则策略无信号。
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today = today or datetime.now().strftime("%Y-%m-%d")
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yesterday = (datetime.strptime(today, "%Y-%m-%d") - timedelta(days=1)).strftime("%Y-%m-%d")
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start_date = acc.get("start_date") or today
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if start_date < yesterday:
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for _wd, wbars in data_source.iter_bars(
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symbols, start_date, yesterday, interval, adjust="qfq", cfg=cfg
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):
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for runner in runners:
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if runner.symbol in wbars:
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runner.paper_cta_engine.on_bar(wbars[runner.symbol])
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runner.paper_cta_engine.pop_orders() # warmup 单丢弃（不撮合）
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# 4. 当日 raw bar（撮合）+ qfq bar（策略 on_bar 信号）
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bars = {}
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qfq_bars = {}
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for sym in symbols:
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rbar = data_source.fetch_day(sym, today, interval, adjust="raw", cfg=cfg)
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if rbar is not None:
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bars[sym] = rbar
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qbar = data_source.fetch_day(sym, today, interval, adjust="qfq", cfg=cfg)
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if qbar is not None:
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qfq_bars[sym] = qbar
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if not bars:
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logger.info("live_step %s: 当日无 raw bar（%s 非交易日或未推？），跳过", account_id, today)
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return
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# 5. 恢复 pending + prev_close
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pending = []
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for o in load_pending_orders(db_path, account_id):
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runner = next((r for r in runners if r.strategy_id == o["strategy_id"]), None)
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if runner is None:
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continue
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pending.append((PaperOrder(
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o["strategy_id"], o["symbol"], OrderSide(o["side"]), o["price"], o["volume"],
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o["is_market"], MatchSession(o["match_session"]), o["listing_days"],
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), runner))
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# prev_close：昨日 raw close（fetch_day 昨日）；失败兜底用当日 open
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prev_close = {}
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for sym in symbols:
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ybar = data_source.fetch_day(sym, yesterday, interval, adjust="raw", cfg=cfg)
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prev_close[sym] = ybar.close_price if ybar else bars[sym].open_price
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# 5. engine.step（单根当日）
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acc_cfg = AccountConfig(
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initial_capital=initial, rate=acc["rate"], slippage=acc["slippage"],
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pricetick=acc["pricetick"], stamp_duty_rate=acc["stamp_duty_rate"],
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transfer_fee_rate=acc["transfer_fee_rate"], min_commission=acc["min_commission"],
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)
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pe = PaperEngine(account, runners, data_source, acc_cfg, db_path, account_id,
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symbols, acc.get("start_date") or today, today, interval,
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risk_free_rate=getattr(cfg, "risk_free_rate", 0.0))
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pending_new, _closes = pe.step(today, bars, qfq_bars, prev_close, pending)
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# 6. 存状态（pending + positions）
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save_pending_orders(db_path, account_id, [
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{"strategy_id": o.strategy_id, "symbol": o.symbol, "side": o.side.value,
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"price": o.price, "volume": o.volume, "is_market": o.is_market,
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"match_session": o.match_session.value, "listing_days": o.listing_days}
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for o, _r in pending_new
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])
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save_positions(db_path, account_id, "account", {
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sym: {"volume": p.volume, "frozen": p.frozen, "avg_price": p.avg_price}
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for sym, p in account.positions.items()}, today)
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for r in runners:
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save_positions(db_path, account_id, f"strategy:{r.strategy_id}", {
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sym: {"volume": p.volume, "frozen": p.frozen, "avg_price": p.avg_price}
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for sym, p in r.positions.items()}, today)
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logger.info("live_step %s 完成 @%s，pending=%d positions=%d",
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account_id, today, len(pending_new), len(account.positions))
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# 7. 影子下单（D-3，spec §5 模式 A）：当日成交 POST bridge，默认关闭
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# enabled=false 时 _shadow_trades_to_bridge 立即 return，live_step 行为完全不变
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_shadow_trades_to_bridge(db_path, account_id, today, cfg)
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def _shadow_trades_to_bridge(db_path: str, account_id: int, today: str, cfg) -> None:
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"""当日成交影子下单到 bridge（D-3，spec §5 模式 A）。
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PaperEngine 模拟撮合为准，当日成交信号同步 POST 到 bridge 影子下单到 miniQMT。
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默认关闭（cfg.live.enabled=false）；任何失败仅记日志，不阻断 live_step。
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幂等：paper_shadow_orders UNIQUE(account_id, trade_id) 保证 scheduler 重跑不重复下单。
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"""
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try:
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live_cfg = getattr(cfg, "live", None) or {}
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if not live_cfg.get("enabled"):
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return
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token = os.environ.get("BRIDGE_TOKEN")
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if not token:
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logger.warning("live_step %s: 影子下单启用但 BRIDGE_TOKEN 未设，跳过", account_id)
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return
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url = live_cfg.get("bridge_url")
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if not url:
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logger.warning("live_step %s: 影子下单启用但 bridge_url 未配，跳过", account_id)
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return
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from .bridge_client import BridgeClient, to_bridge_code
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client = BridgeClient(url, token)
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with sqlite3.connect(db_path) as conn:
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conn.row_factory = sqlite3.Row
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cur = conn.execute(
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"SELECT id, strategy_id, symbol, direction, price, volume "
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"FROM paper_trades WHERE account_id=? AND bar_date=? AND rejected=0",
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(account_id, today),
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)
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trades = [dict(r) for r in cur.fetchall()]
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shadowed = 0
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for t in trades:
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if is_trade_shadowed(db_path, account_id, t["id"]):
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continue
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code = to_bridge_code(t["symbol"])
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resp = client.place_order(
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code, t["direction"], t["price"], t["volume"],
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reason=f"shadow:strategy:{t['strategy_id']}",
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)
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ok = bool(resp and resp.get("ok"))
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status = "ok" if ok else "failed"
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bridge_order_id = resp.get("order_id") if resp else None
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save_shadow_order(db_path, account_id, t["id"], bridge_order_id, status)
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if ok:
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shadowed += 1
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else:
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logger.warning("live_step %s: 影子下单失败 trade=%s code=%s err=%s",
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account_id, t["id"], code,
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resp.get("error") if resp else "no_response")
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if trades:
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logger.info("live_step %s 影子下单: %d/%d ok", account_id, shadowed, len(trades))
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except Exception as e: # noqa: BLE001 影子下单绝不阻断 live_step
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logger.warning("live_step %s: 影子下单异常（不阻断）: %s", account_id, e)
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def list_live_accounts(db_path: str) -> list[int]:
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"""所有 mode=live & status=running 的 account_id（live_runner 遍历用）。"""
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with sqlite3.connect(db_path) as conn:
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rows = conn.execute(
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"SELECT id FROM paper_accounts WHERE mode='live' AND status='running'"
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).fetchall()
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return [r[0] for r in rows]
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def run_live_step(db_path: str) -> None:
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"""每日全局 step：遍历所有 live accounts 调 live_step（scheduler 20:30 调）。
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lazy import _DataSourceWrapper 避免与 routes_paper 循环 import。
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"""
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from sanguo_data.config import find_config_path, load_config
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from sanguo_api.routes_paper import _DataSourceWrapper
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cfg = load_config(find_config_path())
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data_source = _DataSourceWrapper(cfg)
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for aid in list_live_accounts(db_path):
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try:
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live_step(db_path, aid, data_source, cfg)
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except Exception as e: # noqa: BLE001
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logger.error("live_step account %s 失败: %s", aid, e)
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