shy3130
918c7ade7e
- 策略: 引擎只加载 data/strategies/{custom,ai,composite} 与研究模板目录,
原 25 个内置策略一次性迁移为用户自定义文件(ID 不变, 引用零迁移);
研究模板移至 app/strategy/research, 打包 spec 同步; 新装环境策略库为空
- 信号: 管线不再硬编码任何信号表达式; 涨跌停判定价成为运行时列
limit_up_price/limit_down_price(生效价∓0.005 容差), 20 个信号转为
data/user_data/custom_signals 定义(显式 column 沿用 signal_* 原列名);
依赖解析/注入顺序/当日路径 prev-join 全部定义驱动; 语义统一为历史路径
口径(顺带修正当日路径 BOLL 比较符与翘板/炸板空值两处既有偏差)
- 前端: 信号库单列表(全部可编辑), SignalPicker/监控选项/信号标签全走
定义接口; 回测页新增免责声明(模拟性质/数据源准确性不作保证/不构成
投资建议)
- 测试: 25 个策略夹具与 20 个信号种子入库 tests/fixtures, 受影响测试
全部自包含化(不依赖运行目录用户数据); 77 万行 MA 死叉新旧表达式对拍
逐行一致; 回测实跑 45 笔卖点信号出场验证矩阵链路
- 同批包含工作区既有进度: 策略结果 ext 列同日投影修复(含测试)、数据源插件、fuyao/auth/api_gateway/data_integrity 调整、README 信号库
描述与 strategy.md 导入路径补充
验证: 后端 2592 passed(空数据目录 CI 模拟 2588 passed, 4 例为模拟环境
伪影复验排除); 前端 vitest 125 passed + tsc 0 错 + vite build 通过
236 lines
7.8 KiB
Python
236 lines
7.8 KiB
Python
from __future__ import annotations
|
|
|
|
import types
|
|
from datetime import date, timedelta
|
|
|
|
import polars as pl
|
|
import pytest
|
|
|
|
from app.backtest.strategy import StrategyDependencyResolver
|
|
from app.strategy.engine import StrategyDef
|
|
|
|
|
|
def _strategy(**overrides) -> StrategyDef:
|
|
values = dict(
|
|
meta={"id": "deps", "scoring": {"momentum_20d": 1.0}, "order_by": "score"},
|
|
basic_filter={"enabled": False},
|
|
entry_signals=["signal_macd_golden"],
|
|
exit_signals=["signal_ma20_breakdown"],
|
|
stop_loss=None,
|
|
trailing_stop=None,
|
|
trailing_take_profit_activate=None,
|
|
trailing_take_profit_drawdown=None,
|
|
max_hold_days=None,
|
|
filter_fn=lambda df, params: pl.col("rsi_14") < params["rsi_max"],
|
|
filter_history_fn=None,
|
|
lookback_days=20,
|
|
source="builtin",
|
|
)
|
|
values.update(overrides)
|
|
return StrategyDef(**values)
|
|
|
|
|
|
@pytest.fixture(autouse=True)
|
|
def _migrated_signal_definitions(monkeypatch):
|
|
"""注入迁移自内置的信号定义 (信号列定义驱动, 不依赖运行目录)。"""
|
|
from tests.signal_seeds import install_pipeline_caches
|
|
install_pipeline_caches(monkeypatch)
|
|
|
|
|
|
def test_resolver_merges_signals_scoring_filter_and_execution_columns():
|
|
plan = StrategyDependencyResolver().resolve(
|
|
_strategy(),
|
|
params={"rsi_max": 30},
|
|
basic_filter={"enabled": False},
|
|
entry_signals=["signal_macd_golden"],
|
|
exit_signals=["signal_ma20_breakdown"],
|
|
)
|
|
|
|
assert {"macd_dif", "macd_dea", "ma20", "momentum_20d", "rsi_14"} <= set(plan.indicator_columns)
|
|
assert {"signal_macd_golden", "signal_ma20_breakdown", "signal_limit_up", "signal_limit_down"} <= set(plan.signal_columns)
|
|
assert {"symbol", "date", "open", "high", "low", "close", "volume", "raw_close", "raw_high"} <= set(plan.base_columns)
|
|
# 涨跌停信号族统一加载不复权三价 (翘板用 raw_low 判定"曾触及跌停")
|
|
assert "raw_low" in plan.base_columns
|
|
assert "rsi_6" not in plan.indicator_columns
|
|
assert plan.full_feature_fallback is False
|
|
|
|
|
|
def test_resolver_includes_raw_low_for_limit_signal_family():
|
|
"""回归: 翘板信号 (signal_limit_down_recovery) 依赖不复权 raw_low。
|
|
|
|
旧 bug: 涨跌停基础列只声明 raw_close/raw_high, panel 加载缺 raw_low,
|
|
因子用到翘板信号时 compute_limit_signals 抛
|
|
"unable to find column raw_low" → 回测特征准备失败。
|
|
"""
|
|
plan = StrategyDependencyResolver().resolve(
|
|
_strategy(),
|
|
params={"rsi_max": 30},
|
|
basic_filter={"enabled": False},
|
|
entry_signals=["signal_limit_down_recovery"],
|
|
exit_signals=[],
|
|
)
|
|
|
|
assert "signal_limit_down_recovery" in plan.signal_columns
|
|
assert {"raw_close", "raw_high", "raw_low"} <= set(plan.base_columns)
|
|
|
|
|
|
def test_load_panel_for_backtest_supplies_raw_low_for_recovery(monkeypatch, tmp_path):
|
|
"""回归 (端到端): resolver → load_panel_for_backtest → compute_limit_signals 全链路。
|
|
|
|
旧 bug: 涨跌停基础列漏 raw_low, 因子用到翘板信号时回测特征准备抛
|
|
"unable to find column raw_low"。
|
|
"""
|
|
from app.backtest.engine import BacktestEngine
|
|
|
|
n_days = 40
|
|
start = date(2024, 1, 1)
|
|
dates = [start + timedelta(days=i) for i in range(n_days)]
|
|
px = [10.0 + 0.01 * i for i in range(n_days)]
|
|
panel_lf = pl.LazyFrame({
|
|
"symbol": ["600001.SH"] * n_days,
|
|
"date": dates,
|
|
"open": px, "high": px, "low": px, "close": px,
|
|
"volume": [100_000.0] * n_days,
|
|
"amount": [1_000_000.0] * n_days,
|
|
"raw_close": px, "raw_high": px, "raw_low": px,
|
|
})
|
|
monkeypatch.setattr("app.backtest.engine.pl.scan_parquet", lambda path, *a, **k: panel_lf)
|
|
|
|
instruments = pl.DataFrame({
|
|
"symbol": ["600001.SH"], "name": ["普通股"],
|
|
"limit_up": [11.0], "limit_down": [9.0],
|
|
})
|
|
repo = types.SimpleNamespace(
|
|
store=types.SimpleNamespace(data_dir=tmp_path),
|
|
get_enriched_range=lambda *a, **k: None,
|
|
get_instruments_asset=lambda at: instruments,
|
|
get_historical_shares=lambda: pl.DataFrame(),
|
|
)
|
|
plan = StrategyDependencyResolver().resolve(
|
|
_strategy(),
|
|
params={"rsi_max": 30},
|
|
basic_filter={"enabled": False},
|
|
entry_signals=["signal_limit_down_recovery"],
|
|
exit_signals=[],
|
|
)
|
|
|
|
df = BacktestEngine(repo).load_panel_for_backtest(
|
|
["600001.SH"], start, dates[-1], plan, asset_type="stock",
|
|
)
|
|
|
|
assert "raw_low" in df.columns
|
|
assert "signal_limit_down_recovery" in df.columns
|
|
|
|
|
|
def test_resolver_expands_virtual_scoring_dependencies():
|
|
strategy = _strategy(meta={
|
|
"id": "deps",
|
|
"scoring": {"ma20_bias": 0.6, "vol_ratio_5d": 0.4},
|
|
"order_by": "score",
|
|
})
|
|
|
|
plan = StrategyDependencyResolver().resolve(
|
|
strategy,
|
|
params={"rsi_max": 30},
|
|
basic_filter={"enabled": False},
|
|
entry_signals=[],
|
|
exit_signals=[],
|
|
)
|
|
|
|
assert {"ma20", "vol_ratio_5d"} <= set(plan.indicator_columns)
|
|
assert "close" in plan.base_columns
|
|
assert "ma20_bias" not in plan.base_columns
|
|
assert "ma20_bias" not in plan.indicator_columns
|
|
|
|
|
|
def test_resolver_honors_full_scoring_replacement():
|
|
plan = StrategyDependencyResolver().resolve(
|
|
_strategy(),
|
|
params={"rsi_max": 30},
|
|
basic_filter={"enabled": False},
|
|
entry_signals=[],
|
|
exit_signals=[],
|
|
overrides={
|
|
"scoring": {"amount_ratio_5d": 1.0},
|
|
"scoring_replace": True,
|
|
},
|
|
)
|
|
|
|
assert "amount" in plan.base_columns
|
|
assert "momentum_20d" not in plan.indicator_columns
|
|
|
|
|
|
def test_history_strategy_without_required_features_falls_back_to_full(caplog):
|
|
strategy = _strategy(
|
|
filter_fn=None,
|
|
filter_history_fn=lambda df, params: df,
|
|
required_features=frozenset(),
|
|
source="custom",
|
|
)
|
|
|
|
plan = StrategyDependencyResolver().resolve(
|
|
strategy,
|
|
params={},
|
|
basic_filter={"enabled": False},
|
|
entry_signals=[],
|
|
exit_signals=[],
|
|
)
|
|
|
|
assert plan.full_feature_fallback is True
|
|
assert "rsi_14" in plan.indicator_columns
|
|
assert "falls back to full feature computation" in caplog.text
|
|
|
|
|
|
def test_history_strategy_required_features_avoids_fallback():
|
|
strategy = _strategy(
|
|
filter_fn=None,
|
|
filter_history_fn=lambda df, params: df,
|
|
required_features=frozenset({"ma20", "momentum_20d"}),
|
|
source="custom",
|
|
)
|
|
|
|
plan = StrategyDependencyResolver().resolve(
|
|
strategy,
|
|
params={},
|
|
basic_filter={"enabled": False},
|
|
entry_signals=[],
|
|
exit_signals=[],
|
|
)
|
|
|
|
assert plan.full_feature_fallback is False
|
|
assert {"ma20", "momentum_20d"} <= set(plan.indicator_columns)
|
|
assert "rsi_14" not in plan.indicator_columns
|
|
|
|
|
|
def test_matrix_native_resolves_raw_fields_and_protocol_warmup_without_indicators():
|
|
class NativeStrategy:
|
|
def required_fields(self):
|
|
return frozenset({"open", "high", "low", "close", "volume"})
|
|
|
|
def required_warmup_bars(self, params):
|
|
return 120
|
|
|
|
def compute_signals(self, market, params): # pragma: no cover - resolver only
|
|
raise AssertionError
|
|
|
|
strategy = _strategy(
|
|
filter_fn=None,
|
|
filter_history_fn=None,
|
|
execution_backend="matrix_native",
|
|
matrix_strategy=NativeStrategy(),
|
|
required_features=frozenset(),
|
|
)
|
|
plan = StrategyDependencyResolver().resolve(
|
|
strategy,
|
|
params={},
|
|
basic_filter={"enabled": True, "amount_min": 100.0},
|
|
entry_signals=[],
|
|
exit_signals=[],
|
|
)
|
|
|
|
assert plan.execution_backend == "matrix_native"
|
|
assert plan.indicator_columns == frozenset()
|
|
assert {"open", "high", "low", "close", "volume", "amount"} <= set(plan.base_columns)
|
|
assert plan.warmup_bars == 120
|
|
assert plan.full_feature_fallback is False
|