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GitHub 155328df8b release: v1.16.2 — 三轮审计质量加固(B6.9→A7.9)
经三轮代码审计后的综合质量加固版本,覆盖协议核心层、数据正确性、
错误处理、测试真实度与可维护性。761 单测全绿(+58),ruff/mypy 全过。

主要修复:
- 离线 .day 写入原子化(fsync + _repair_tail + 读取校验,CQS 守住)
- 回测止损前视偏差(延迟下一根开盘 + 跳空保护)
- VWAP 权重索引 / bar_time fail-fast / 绩效除零保护
- 闭包绑定 / 路径穿越 / naive datetime 跨时区 / ruff UP038

重构:
- 抽 AsyncHeartbeatMixin 收敛 4 处心跳副本(12→1)
- 统一 _RETRY_DELAYS 退避序列 / scanner 失败可观测性

新增 5 个测试文件 + 公共 API 类型契约,CI 加 Windows 矩阵 +
trusted publishing 签名 + 锁文件。

详见 CHANGELOG.md
2026-07-02 03:37:37 +08:00

267 lines
9.7 KiB
Python

"""单元测试:信号扫描引擎。
测试 SignalScanner 的并发扫描和增量扫描功能。
使用临时目录构造 .day 文件 fixture,无需真实数据。
"""
from __future__ import annotations
import struct
from pathlib import Path
import pandas as pd
import pytest
from easy_tdx.backtest.strategy import Strategy
from easy_tdx.screen.scanner import SignalScanner
class AlwaysBuyStrategy(Strategy):
"""策略:每个 bar 都产生买入信号(用于扫描测试)。"""
def init(self) -> None:
pass
def next(self) -> None:
self.buy(size=0)
def _write_day_file(
path: Path,
n_bars: int = 50,
base_price: float = 10.0,
) -> None:
"""写一个最小的 .day 文件(通达信日线格式)。
格式: date(I) open(I) high(I) low(I) close(I) amount(f) vol(I) reserved(I)
每条 32 字节, 小端序. 价格以 0.01 为系数存储.
"""
dates = pd.date_range("2024-01-01", periods=n_bars, freq="D")
with open(path, "wb") as f:
for i in range(n_bars):
dt = dates[i]
day = dt.year * 10000 + dt.month * 100 + dt.day
price = base_price + i * 0.01
f.write(
struct.pack(
"<IIIIIfII",
day,
int(price * 100),
int((price + 0.5) * 100),
int((price - 0.5) * 100),
int(price * 100),
float(1000000 + i * 100),
10000 + i * 10,
0,
)
)
@pytest.fixture
def vipdoc(tmp_path: Path) -> Path:
"""创建包含 .day 文件的临时 vipdoc 目录."""
sz_lday = tmp_path / "sz" / "lday"
sz_lday.mkdir(parents=True)
for code in ("000001", "000002", "000003"):
_write_day_file(sz_lday / f"sz{code}.day", n_bars=50)
# 指数文件 (应被过滤)
_write_day_file(sz_lday / "sz399001.day", n_bars=50)
return tmp_path
class TestConcurrentScan:
"""测试并发扫描."""
def test_scan_produces_results(self, vipdoc: Path) -> None:
"""基本扫描应返回触发信号的股票."""
scanner = SignalScanner(AlwaysBuyStrategy, vipdoc_path=vipdoc)
results = scanner.scan(universe="all")
assert len(results) >= 1, f"Expected >= 1 result, got {len(results)}"
def test_concurrent_same_as_serial(self, vipdoc: Path) -> None:
"""并发扫描结果应与串行扫描一致."""
scanner = SignalScanner(AlwaysBuyStrategy, vipdoc_path=vipdoc)
serial = scanner.scan(universe="all", workers=1)
parallel = scanner.scan(universe="all", workers=2)
serial_codes = sorted(r.code for r in serial)
parallel_codes = sorted(r.code for r in parallel)
assert serial_codes == parallel_codes
def test_scan_with_zero_workers_uses_serial(self, vipdoc: Path) -> None:
"""workers=0 应退回串行模式."""
scanner = SignalScanner(AlwaysBuyStrategy, vipdoc_path=vipdoc)
results = scanner.scan(universe="all", workers=0)
assert len(results) >= 1
def test_progress_callback(self, vipdoc: Path) -> None:
"""进度回调应被正确调用."""
scanner = SignalScanner(AlwaysBuyStrategy, vipdoc_path=vipdoc)
progress: list[tuple[int, int, str]] = []
def on_progress(current: int, total: int, name: str) -> None:
progress.append((current, total, name))
scanner.scan(universe="all", progress_callback=on_progress)
assert len(progress) >= 2
assert progress[-1][2] == "done"
class TestParallelPickleFix:
"""回归测试:并发模式从策略文件加载(修复 pickle 序列化失败)。"""
def test_parallel_with_file_strategy(self, vipdoc: Path) -> None:
"""从 .py 文件加载的策略在并发模式下应正常工作。"""
# 使用项目自带的策略文件
strategy_path = Path("strategies/macd_cross.py")
if not strategy_path.exists():
pytest.skip("strategies/macd_cross.py not found")
import importlib.util
from easy_tdx.backtest.strategy import Strategy
spec = importlib.util.spec_from_file_location("strat", strategy_path)
assert spec is not None and spec.loader is not None
mod = importlib.util.module_from_spec(spec)
spec.loader.exec_module(mod)
cls = None
for name in dir(mod):
obj = getattr(mod, name)
try:
if isinstance(obj, type) and issubclass(obj, Strategy) and obj is not Strategy:
cls = obj
break
except TypeError:
pass
assert cls is not None, "No Strategy subclass found in macd_cross.py"
scanner = SignalScanner(cls, vipdoc_path=vipdoc)
# 并发模式不应抛出异常(修复前会因为 pickle 失败而静默返回空列表)
results = scanner.scan(universe="all", workers=2)
# 结果应为列表(可能为空,取决于策略信号)
assert isinstance(results, list)
class TestIncrementalScan:
"""测试增量扫描."""
def test_second_scan_uses_cache(self, vipdoc: Path, tmp_path: Path) -> None:
"""第二次扫描应使用缓存, 不重新计算."""
cache_file = tmp_path / "scan_cache.json"
scanner = SignalScanner(
AlwaysBuyStrategy,
vipdoc_path=vipdoc,
cache_file=cache_file,
)
# 第一次扫描: 无缓存
results1 = scanner.scan(universe="all")
assert len(results1) >= 1
assert cache_file.is_file()
# 第二次扫描: 应使用缓存, 结果相同
results2 = scanner.scan(universe="all")
codes1 = sorted(r.code for r in results1)
codes2 = sorted(r.code for r in results2)
assert codes1 == codes2
def test_no_cache_file_means_full_scan(self, vipdoc: Path) -> None:
"""无缓存文件时每次都是全量扫描."""
scanner = SignalScanner(AlwaysBuyStrategy, vipdoc_path=vipdoc)
results1 = scanner.scan(universe="all")
results2 = scanner.scan(universe="all")
codes1 = sorted(r.code for r in results1)
codes2 = sorted(r.code for r in results2)
assert codes1 == codes2
def test_cache_updated_after_file_change(self, vipdoc: Path, tmp_path: Path) -> None:
"""文件变化后缓存应失效, 重新扫描."""
cache_file = tmp_path / "scan_cache.json"
scanner = SignalScanner(
AlwaysBuyStrategy,
vipdoc_path=vipdoc,
cache_file=cache_file,
)
# 第一次扫描
results1 = scanner.scan(universe="all")
assert len(results1) >= 1
# 修改文件 (touch mtime)
import time
day_file = vipdoc / "sz" / "lday" / "sz000001.day"
time.sleep(0.1)
day_file.touch()
# 第二次扫描: sz000001 应被重新扫描
results2 = scanner.scan(universe="all")
codes2 = sorted(r.code for r in results2)
# 结果可能相同 (策略没变), 但不应崩溃
assert len(codes2) >= 1
class TestScanFailureLogging:
"""扫描失败日志回归(审计复审 L2)。
首轮 #6 将扫描循环的 ``except Exception: continue`` 评为"系统性失败被静默
吞掉"。复审 L2 修复:单股失败记录 warning + 失败计数,失败率超阈值时
循环结束发出 summary。这些测试用 monkeypatch 让 ``_scan_one`` 抛错模拟
损坏 .day / 策略异常等场景,断言失败被记录(read_daily_bars 本身对短文件
容错返回 0 条,不会抛错,故用 monkeypatch 构造确定性失败)。
"""
def test_serial_scan_logs_per_stock_failure(
self, vipdoc: Path, caplog: pytest.LogCaptureFixture, monkeypatch: pytest.MonkeyPatch
) -> None:
"""单股 _scan_one 抛错时,串行扫描应记录 warning(审计复审 L2)。"""
scanner = SignalScanner(AlwaysBuyStrategy, vipdoc_path=vipdoc)
def _boom(self: SignalScanner, filepath: Path, market: str, code: str) -> None:
raise RuntimeError(f"simulated corrupt day for {code}")
monkeypatch.setattr(SignalScanner, "_scan_one", _boom)
with caplog.at_level("WARNING", logger="easy_tdx.screen.scanner"):
results = scanner.scan(universe="all", workers=0)
# 全部抛错 → 无结果,但不崩溃(容错语义:跳过继续)
assert results == []
# 每个被扫描的 A 股都应有一条 warning
warnings = [r for r in caplog.records if r.levelname == "WARNING"]
assert len(warnings) >= 1, "单股失败应触发 warning 日志"
assert any("失败" in r.getMessage() for r in warnings)
def test_serial_scan_high_failure_rate_emits_summary(
self, vipdoc: Path, caplog: pytest.LogCaptureFixture, monkeypatch: pytest.MonkeyPatch
) -> None:
"""失败率超阈值时应发出汇总告警(审计复审 L2)。
全部 A 股 _scan_one 抛错(失败率 100% > 50% 阈值),断言扫描完成后
有一条 summary warning。
"""
scanner = SignalScanner(AlwaysBuyStrategy, vipdoc_path=vipdoc)
def _boom(self: SignalScanner, filepath: Path, market: str, code: str) -> None:
raise RuntimeError(f"simulated corrupt day for {code}")
monkeypatch.setattr(SignalScanner, "_scan_one", _boom)
with caplog.at_level("WARNING", logger="easy_tdx.screen.scanner"):
scanner.scan(universe="all", workers=0)
# 应有汇总告警提到"失败率过高"
summary_msgs = [r.getMessage() for r in caplog.records if "失败率" in r.getMessage()]
assert summary_msgs, "失败率过高时应发出汇总 warning"