claude_dev
28aea67232
- 修 submit_cta/optimize 策略字符串→类解析（get_strategy_class） - cta_engine: worker 进程设 vnpy DB→quant_trading.db（修 0 根数据） - equity_curve 取自 calculate_result 的 daily_df（修 get_all_daily_results 对象问题） - kline 补 cfg（find_config_path 共享） - 端到端冒烟通过：DoubleMaStrategy 600000 → equity111/pnl111/trades1/kline117
197 lines
6.9 KiB
Python
197 lines
6.9 KiB
Python
"""CTA strategy backtesting engine wrapper using vnpy_ctastrategy.backtesting."""
|
||
import sys
|
||
import os
|
||
import traceback
|
||
import uuid
|
||
from datetime import datetime
|
||
from pathlib import Path
|
||
|
||
import pandas as pd
|
||
|
||
# Add vnpy source to path for local development
|
||
_VNPY_SRC = os.path.join(os.path.dirname(__file__), "..", "vnpy_v4.4.0")
|
||
_VNPY_SRC = os.path.abspath(_VNPY_SRC)
|
||
if _VNPY_SRC not in sys.path:
|
||
sys.path.insert(0, _VNPY_SRC)
|
||
|
||
from sanguo_backtest.result_store import BacktestResult, save_result
|
||
|
||
|
||
# Mock Exchange enum for local use (replaces vnpy.trader.constant.Exchange)
|
||
class MockExchange:
|
||
SSE = "SSE" # Shanghai Stock Exchange
|
||
SZSE = "SZSE" # Shenzhen Stock Exchange
|
||
|
||
class Exchange:
|
||
SSE = "SSE"
|
||
SZSE = "SZSE"
|
||
|
||
def __init__(self, value):
|
||
self.value = value
|
||
|
||
def __repr__(self):
|
||
return f"Exchange.{self.value}"
|
||
|
||
|
||
Exchange = MockExchange.Exchange
|
||
|
||
|
||
def guess_exchange(symbol: str) -> Exchange:
|
||
"""按代码前缀判断交易所：6/68/5x→SSE，0/3/15x→SZSE"""
|
||
if symbol.startswith(("60", "68", "51", "56", "58")):
|
||
return Exchange("SSE")
|
||
if symbol.startswith(("00", "30", "15")):
|
||
return Exchange("SZSE")
|
||
return Exchange("SSE")
|
||
|
||
|
||
def run_cta_backtest(strategy_class, symbol: str, params: dict, start: str, end: str, cfg, db_path: str) -> BacktestResult:
|
||
"""
|
||
Run CTA strategy backtest using vnpy_ctastrategy BacktestingEngine.
|
||
|
||
Args:
|
||
strategy_class: CTA strategy class to backtest
|
||
symbol: Stock symbol (e.g., "600000")
|
||
params: Strategy parameters dict
|
||
start: Backtest start date (YYYY-MM-DD format)
|
||
end: Backtest end date (YYYY-MM-DD format)
|
||
cfg: Configuration object (may contain data paths)
|
||
db_path: SQLite database path for saving results
|
||
|
||
Returns:
|
||
BacktestResult: Result object with backtest statistics and status
|
||
"""
|
||
# Generate unique task ID
|
||
task_id = f"cta_{uuid.uuid4().hex[:8]}"
|
||
|
||
try:
|
||
# Lazy import of BacktestingEngine (local env may not have vnpy_ctastrategy)
|
||
from vnpy_ctastrategy.backtesting import BacktestingEngine
|
||
|
||
# Build vt_symbol for A-shares
|
||
vt_symbol = f"{symbol}.{guess_exchange(symbol).value}"
|
||
|
||
# Convert date strings to datetime objects
|
||
start_dt = datetime.strptime(start, "%Y-%m-%d")
|
||
end_dt = datetime.strptime(end, "%Y-%m-%d") if end else None
|
||
|
||
# Create and configure backtesting engine
|
||
engine = BacktestingEngine()
|
||
|
||
# Set parameters with A-share specific values
|
||
engine.set_parameters(
|
||
vt_symbol=vt_symbol,
|
||
interval="d", # Interval.DAILY.value — vnpy enum uses "d" not "1d"
|
||
start=start_dt,
|
||
end=end_dt,
|
||
rate=0.001, # Commission rate (0.1% for A-shares)
|
||
slippage=0, # No slippage for simplicity
|
||
size=1, # Contract size (1 for stocks)
|
||
pricetick=0.01, # Minimum price tick (0.01 yuan for A-shares)
|
||
capital=1_000_000 # Starting capital — 0 causes instant liquidation on first trade
|
||
)
|
||
|
||
# Add strategy
|
||
engine.add_strategy(strategy_class, params)
|
||
|
||
# Configure vnpy DB → A-share quant_trading.db. Worker process (spawn)
|
||
# doesn't inherit main-process SETTINGS, so set before engine.load_data.
|
||
try:
|
||
from vnpy.trader.setting import SETTINGS
|
||
from sanguo_data.config import load_config, find_config_path
|
||
_dcfg = load_config(find_config_path())
|
||
SETTINGS["database.name"] = "sqlite"
|
||
SETTINGS["database.database"] = _dcfg.data_paths["vnpy_db"]
|
||
except Exception:
|
||
pass
|
||
|
||
# Load historical data
|
||
engine.load_data()
|
||
|
||
# Run backtesting
|
||
engine.run_backtesting()
|
||
|
||
# Calculate statistics — calculate_result() returns a daily DataFrame,
|
||
# calculate_statistics(df) returns the stats dict (sharpe/drawdown/etc.)
|
||
daily_df = engine.calculate_result()
|
||
raw_stats = engine.calculate_statistics(daily_df, output=False) or {}
|
||
# Ensure JSON-serializable (vnpy may include Timestamp / non-numeric values)
|
||
statistics = {
|
||
k: (v if isinstance(v, (int, float, str, bool)) or v is None else str(v))
|
||
for k, v in raw_stats.items()
|
||
}
|
||
|
||
# Build equity curve DataFrame (S1.2): use the daily_df returned by
|
||
# calculate_result (index=date, has a 'balance' column). get_all_daily_results
|
||
# returns DailyResult objects (not dicts), so prefer daily_df.
|
||
if daily_df is not None and hasattr(daily_df, "empty") and not daily_df.empty:
|
||
if "balance" in daily_df.columns:
|
||
_bal = daily_df["balance"].astype(float)
|
||
elif "net_pnl" in daily_df.columns:
|
||
_bal = daily_df["net_pnl"].astype(float).cumsum() + 1_000_000
|
||
else:
|
||
_bal = None
|
||
equity_df = pd.DataFrame({
|
||
"date": daily_df.index.astype(str),
|
||
"balance": _bal.tolist(),
|
||
}) if _bal is not None else pd.DataFrame()
|
||
else:
|
||
equity_df = pd.DataFrame()
|
||
|
||
# Build trades DataFrame (S1.2): engine.trades is dict[vt_tradeid, TradeData].
|
||
trades_dict = engine.trades if isinstance(engine.trades, dict) else {}
|
||
trades_df = pd.DataFrame([
|
||
{
|
||
"datetime": str(t.datetime),
|
||
"direction": str(t.direction),
|
||
"offset": str(t.offset),
|
||
"price": t.price,
|
||
"volume": t.volume,
|
||
"vt_symbol": getattr(t, "vt_symbol", ""),
|
||
}
|
||
for t in trades_dict.values()
|
||
])
|
||
|
||
# Build result object
|
||
result = BacktestResult(
|
||
task_id=task_id,
|
||
type="cta",
|
||
status="done",
|
||
strategy=strategy_class.__name__,
|
||
symbol=symbol,
|
||
params=params,
|
||
start=start,
|
||
end=end,
|
||
statistics=statistics,
|
||
equity_curve=equity_df,
|
||
trades=trades_df,
|
||
)
|
||
|
||
except Exception as e:
|
||
# Handle any exceptions and return failed result
|
||
error_msg = f"{type(e).__name__}: {e}\n{traceback.format_exc()}"
|
||
|
||
result = BacktestResult(
|
||
task_id=task_id,
|
||
type="cta",
|
||
status="failed",
|
||
strategy=strategy_class.__name__,
|
||
symbol=symbol,
|
||
params=params,
|
||
start=start,
|
||
end=end,
|
||
statistics={},
|
||
equity_curve=None,
|
||
trades=None,
|
||
error_msg=error_msg
|
||
)
|
||
|
||
# Save result to database. file_dir = db dir so equity_curve/trades persist
|
||
# to parquet (S1.1) and reload via result.id.
|
||
save_result(result, db_path=db_path, file_dir=os.path.dirname(os.path.abspath(db_path)))
|
||
|
||
return result
|
||
|
||
|
||
# Module-level reference for mocking in tests
|
||
BacktestingEngine = None # Will be set when imported inside run_cta_backtest |