claude_dev
193064c953
spec §195: 多策略并发下单"先到后到"不可复现 → 每策略独立max_allocation - StrategyRunner: max_allocation字段(默认inf) + used_allocation(持仓市值) - engine._match: BUY cash_enough后查 used+成交额>max_allocation → 拒单max_allocation_exceeded - live_orchestrator: runner传max_allocation(默认initial_capital) - routes_paper: StrategyCfg加max_allocation(API→DB→live_step数据流) - test_soft_limit: 3测试(累计超限拒单/默认不限/SELL不受限) 116 passed(113旧+3新), 无回归.
149 lines
6.8 KiB
Python
149 lines
6.8 KiB
Python
"""PaperEngine 模拟盘主循环（逐根 bar 重放 + 双层记账 + 持久化，spec §4/§9）。
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双源（分红除权准确方案，task #79 恢复）：
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- 撮合/涨跌停/盯市用 **raw**（真实价，涨跌停/成交真实）
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- 策略 on_bar 信号用 **qfq**（前复权，无除权缺口 → MA 信号准）
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run() 双迭代器 zip(raw, qfq) 同日期对齐；step(raw_bars, qfq_bars)。
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"""
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import logging
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import pandas as pd
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from .account import Account
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from .matcher import cross_order
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from .models import MatchSession, OrderSide, PaperTrade
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from .persistence import save_daily_balance, save_trade, update_checkpoint
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from .strategy_runner import StrategyRunner
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logger = logging.getLogger(__name__)
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def _to_series(bar) -> pd.Series:
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return pd.Series({
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"open": bar.open_price, "high": bar.high_price,
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"low": bar.low_price, "close": bar.close_price,
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"date": getattr(bar, "datetime", ""),
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})
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def _trade_to_dict(t: PaperTrade, bar_date) -> dict:
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return {
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"strategy_id": t.strategy_id, "symbol": t.symbol,
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"direction": t.side.value, "price": t.price, "volume": t.volume,
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"commission": t.commission, "stamp_duty": t.stamp_duty,
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"transfer_fee": t.transfer_fee,
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"bar_date": str(bar_date), "match_session": t.match_session.value,
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}
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class PaperEngine:
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def __init__(self, account: Account, runners: list[StrategyRunner],
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data_source, cfg, db_path: str, account_id: int,
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symbols: list[str], start: str, end: str,
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interval: str = "d") -> None:
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self.account = account
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self.runners = runners
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self.data_source = data_source
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self.cfg = cfg
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self.db_path = db_path
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self.account_id = account_id
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self.symbols = symbols
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self.start = start
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self.end = end
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self.interval = interval
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def step(self, bar_date, raw_bars, qfq_bars, prev_close, pending):
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"""单根 bar 推进（回放 run 循环调；实走 live_step 调）。
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撮合/盯市用 raw_bars（真实价）；策略 on_bar 用 qfq_bars（信号准）。
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返回 (新 pending, 当根 closes)。
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"""
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self._bar_count = getattr(self, "_bar_count", 0) + 1
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self.account.unfreeze_all()
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for r in self.runners:
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r.unfreeze_all()
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# 1. 撮合上一根 pending（next_open，用当日 raw bar）
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if pending:
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for order, runner in pending:
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self._match(order, runner, raw_bars, prev_close, bar_date)
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pending = []
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# 2. 喂策略 on_bar（qfq 信号）→ 收新单 → 当根撮合 raw / 缓冲 next_open
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for runner in self.runners:
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sym = runner.symbol
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if sym and sym in qfq_bars:
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runner.paper_cta_engine.on_bar(qfq_bars[sym])
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for order in runner.paper_cta_engine.pop_orders():
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if order.match_session == MatchSession.NEXT_OPEN:
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pending.append((order, runner))
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else: # current_close 当根撮合（raw）
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self._match(order, runner, raw_bars, prev_close, bar_date)
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# 3. 盯市 raw + 入库
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closes = {s: raw_bars[s].close_price for s in raw_bars}
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self.account.mark_to_market(closes)
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save_daily_balance(
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self.db_path, self.account_id, str(bar_date),
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self.account.cash, self.account.market_value, self.account.equity,
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is_checkpoint=(self._bar_count % 500 == 0),
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)
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update_checkpoint(self.db_path, self.account_id, str(bar_date))
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return pending, closes
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def run(self) -> None:
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"""双源 zip(raw, qfq) 同日期对齐，逐根 step。"""
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prev_close: dict[str, float] = {}
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pending: list = [] # [(order, runner)] next_open 待下根撮合
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raw_iter = self.data_source.iter_bars(
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self.symbols, self.start, self.end, self.interval, "raw", None
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)
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qfq_iter = self.data_source.iter_bars(
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self.symbols, self.start, self.end, self.interval, "qfq", None
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)
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for (rdate, raw_bars), (_qdate, qfq_bars) in zip(raw_iter, qfq_iter):
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pending, closes = self.step(rdate, raw_bars, qfq_bars, prev_close, pending)
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prev_close = closes
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def _match(self, order, runner, bars, prev_close, bar_date) -> None:
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if order.symbol not in bars:
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return
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match_bar = _to_series(bars[order.symbol])
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pc = prev_close.get(order.symbol, order.price)
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result = cross_order(order, match_bar, pc, self.cfg)
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if isinstance(result, PaperTrade):
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if result.side == OrderSide.SELL:
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# A 股不能做空：SELL 超过可卖持仓 → 拒单（不开空仓）
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pos = self.account.positions.get(order.symbol)
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if pos is None or pos.available < result.volume:
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save_trade(self.db_path, self.account_id,
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{"strategy_id": order.strategy_id, "symbol": order.symbol,
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"bar_date": str(bar_date)},
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rejected=True,
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reject_reason="insufficient_position_no_short")
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return
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if self.account.cash_enough(result):
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# 软限额：BUY 检查该策略已用额度（消除多策略撮合顺序依赖，spec §195）
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if result.side == OrderSide.BUY:
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closes = {sym: b.close_price for sym, b in bars.items()}
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if (runner.used_allocation(closes) + result.price * result.volume
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> runner.max_allocation):
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save_trade(self.db_path, self.account_id,
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{"strategy_id": order.strategy_id,
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"symbol": order.symbol,
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"bar_date": str(bar_date)},
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rejected=True,
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reject_reason="max_allocation_exceeded")
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return
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self.account.apply_trade(result)
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runner.apply_trade(result)
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save_trade(self.db_path, self.account_id,
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_trade_to_dict(result, bar_date))
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else:
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save_trade(self.db_path, self.account_id,
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{"strategy_id": order.strategy_id, "symbol": order.symbol,
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"bar_date": str(bar_date)},
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rejected=True, reject_reason="insufficient_cash")
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else: # PaperReject
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save_trade(self.db_path, self.account_id,
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{"strategy_id": order.strategy_id, "symbol": order.symbol,
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"bar_date": str(bar_date)},
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rejected=True, reject_reason=result.reason)
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