Files
tick-stock-panel/backend/tests/test_strategy_realtime_refresh.py
T
shy3130 918c7ade7e refactor(core): 策略与信号全面去内置化, 转为用户自定义定义
- 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
2026-10-10 21:10:44 +08:00

220 lines
7.2 KiB
Python

"""策略页实时结果刷新 SSE 回归测试。"""
from __future__ import annotations
from datetime import timedelta
from pathlib import Path
from types import SimpleNamespace
from unittest.mock import patch
import polars as pl
from app.market_time import cn_today
from app.services import quote_service
from app.services.quote_service import QuoteService, QuoteSubscriber
from app.strategy.engine import StrategyEngine
from app.strategy.monitor import MonitorRuleEngine
def _strategy_rule(scope: str = "all") -> dict:
return {
"id": "strategy_rule",
"name": "策略监控",
"type": "strategy",
"asset_type": "stock",
"strategy_id": "strategy_1",
"scope": scope,
"symbols": ["600000.SH"],
"cooldown_seconds": 0,
}
def _quote_df() -> pl.DataFrame:
return pl.DataFrame({
"symbol": ["600000.SH"],
"close": [10.0],
"change_pct": [0.01],
})
def test_strategy_result_subscriber_notification_is_coalesced():
sub = QuoteSubscriber()
sub.notify_strategy_results()
sub.notify_strategy_results()
assert sub.wait(timeout=0.01) is True
data = sub.pop()
assert data["strategy_results_updated"] is True
assert data["quote_updated"] is False
assert data["depth_updated"] is False
assert sub.wait(timeout=0.01) is False
def test_strategy_result_notification_fans_out_to_all_subscribers():
service = QuoteService()
first = service.subscribe()
second = service.subscribe()
service.notify_strategy_results_updated()
assert first.pop()["strategy_results_updated"] is True
assert second.pop()["strategy_results_updated"] is True
class _EmptyResultStrategyEngine:
def get(self, strategy_id: str):
assert strategy_id == "strategy_1"
return SimpleNamespace(filter_history_fn=None, execution_backend="polars_expr")
def run(self, strategy_id: str, context, **kwargs):
assert strategy_id == "strategy_1"
assert context.current.height == 1
return SimpleNamespace(total=0, rows=[])
class _FailingStrategyEngine(_EmptyResultStrategyEngine):
def run(self, strategy_id: str, context, **kwargs):
raise RuntimeError("strategy failed")
def test_successful_zero_match_strategy_marks_result_refresh():
engine = MonitorRuleEngine()
engine.set_strategy_engine(_EmptyResultStrategyEngine())
engine.set_rules([_strategy_rule()])
assert engine.evaluate(_quote_df()) == []
assert engine.latest_strategy_results()["strategy_1"]["total"] == 0
assert engine.consume_strategy_result_updates() is True
assert engine.consume_strategy_result_updates() is False
def test_failed_or_skipped_strategy_does_not_mark_result_refresh():
failed = MonitorRuleEngine()
failed.set_strategy_engine(_FailingStrategyEngine())
failed.set_rules([_strategy_rule()])
assert failed.evaluate(_quote_df()) == []
assert failed.latest_strategy_results() == {}
assert failed.consume_strategy_result_updates() is False
skipped = MonitorRuleEngine()
skipped.set_strategy_engine(_EmptyResultStrategyEngine())
skipped.set_rules([_strategy_rule(scope="symbols")])
assert skipped.evaluate(pl.DataFrame({"symbol": ["000001.SZ"]})) == []
assert skipped.latest_strategy_results() == {}
assert skipped.consume_strategy_result_updates() is False
def test_matrix_strategy_monitor_reuses_live_matrix_and_updates_last_row():
target = cn_today()
start = target - timedelta(days=61)
rows = []
for offset in range(62):
for symbol, base in (("000001.SZ", 10.0), ("600000.SH", 20.0)):
close = base + offset * 0.05
rows.append({
"symbol": symbol,
"name": symbol,
"date": start + timedelta(days=offset),
"open": close,
"high": close * 1.01,
"low": close * 0.99,
"close": close,
"volume": 1_000_000.0,
"amount": 100_000_000.0,
"total_shares": 1_000_000_000.0,
"float_shares": 800_000_000.0,
})
panel = pl.DataFrame(rows)
history = panel.filter(pl.col("date") < target)
current = panel.filter(pl.col("date") == target)
load_calls = []
def load_history(as_of, lookback):
load_calls.append((as_of, lookback))
return history
strategy_engine = StrategyEngine(
strategy_dirs=[Path(__file__).resolve().parents[1] / "tests" / "fixtures" / "strategies"],
)
overrides = {
"params": {"require_macd_golden": False, "use_volume_filter": False},
"basic_filter": {"enabled": False},
}
monitor = MonitorRuleEngine()
monitor.set_strategy_engine(strategy_engine)
monitor.set_data_dir(Path("test-data"))
monitor.set_history_loader(load_history)
monitor.set_rules([{
"id": "matrix_macd",
"name": "MACD",
"type": "strategy",
"asset_type": "stock",
"strategy_id": "macd_golden",
"scope": "all",
"symbols": [],
"cooldown_seconds": 0,
}])
with patch("app.strategy.monitor._strategy_config.load_override", return_value=overrides):
assert monitor.evaluate(current) == []
assert monitor.latest_strategy_results()["macd_golden"]["total"] == 2
first_stats = strategy_engine.realtime_matrix_stats("monitor:stock")
assert first_stats["build_count"] == 1
assert len(load_calls) == 1
updated = current.with_columns((pl.col("close") + 1.0).alias("close"))
assert monitor.evaluate(updated) == []
second_stats = strategy_engine.realtime_matrix_stats("monitor:stock")
assert second_stats["build_count"] == 1
assert second_stats["update_count"] == 1
assert len(load_calls) == 1
class _MonitorWithUpdate:
rule_count = 1
def __init__(self, updated: bool):
self.updated = updated
def set_name_map(self, name_map):
pass
def has_rule_type(self, rtype: str) -> bool:
return False
def has_asset_rules(self, asset_type: str) -> bool:
return False
def evaluate(self, df, asset_type: str):
assert asset_type == "stock"
return []
def consume_strategy_result_updates(self) -> bool:
return self.updated
def test_quote_service_notifies_only_after_strategy_result_update():
service = QuoteService()
subscriber = service.subscribe()
service.set_app_state(SimpleNamespace(monitor_engine=_MonitorWithUpdate(updated=True)))
service.get_enriched_today = lambda: (_quote_df(), quote_service.cn_today())
with patch.object(QuoteService, "_is_continuous_trading", return_value=True):
service._evaluate_monitors(pl.DataFrame(), None)
assert subscriber.pop()["strategy_results_updated"] is True
def test_quote_service_skips_notification_without_strategy_result_update():
service = QuoteService()
subscriber = service.subscribe()
service.set_app_state(SimpleNamespace(monitor_engine=_MonitorWithUpdate(updated=False)))
service.get_enriched_today = lambda: (_quote_df(), quote_service.cn_today())
with patch.object(QuoteService, "_is_continuous_trading", return_value=True):
service._evaluate_monitors(pl.DataFrame(), None)
assert subscriber.pop()["strategy_results_updated"] is False