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im47cn
5f1c1cf0bb
test_history_strategy_monitor_keeps_live_row_with_exclude_st_enabled used date(2026,7,20) as the "today" value, but MonitorRuleEngine.evaluate() calls cn_today() internally. The date mismatch caused the basic_filter + history filter to produce 0 rows, making the test fail 8 days after it was written. Also fixes test_live_enriched_cache_keeps_instrument_metadata_without_persisting_it which used the same hardcoded date — would break on any future run. Replace all hardcoded dates with cn_today() / cn_today()-timedelta(days=3) so the tests are timeless.
105 lines
3.3 KiB
Python
105 lines
3.3 KiB
Python
from __future__ import annotations
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from datetime import timedelta
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from pathlib import Path
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import polars as pl
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from app.market_time import cn_today
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from app.strategy.engine import StrategyEngine
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from app.strategy.monitor import MonitorRuleEngine
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from app.tickflow.repository import DataStore, KlineRepository
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def _repo(tmp_path) -> KlineRepository:
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repo = KlineRepository(DataStore(tmp_path))
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repo._instruments_cache = pl.DataFrame({
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"symbol": ["600000.SH", "000001.SZ"],
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"name": ["浦发银行", "平安银行"],
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"total_shares": [29_352_080_397.0, 19_405_918_198.0],
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"float_shares": [29_352_080_397.0, 19_405_918_198.0],
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})
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return repo
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def _live_row(symbol: str, close: float) -> pl.DataFrame:
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return pl.DataFrame({
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"symbol": [symbol],
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"date": [cn_today()],
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"open": [close],
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"high": [close],
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"low": [close],
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"close": [close],
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"volume": [1000.0],
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"amount": [close * 1000.0],
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"raw_close": [close],
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"raw_high": [close],
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"raw_low": [close],
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})
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def test_live_enriched_cache_keeps_instrument_metadata_without_persisting_it(tmp_path):
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repo = _repo(tmp_path)
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repo.flush_live_enriched_asset("stock", _live_row("600000.SH", 10.0))
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repo.merge_live_enriched_asset("stock", _live_row("000001.SZ", 12.0))
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cached, cached_date = repo.get_enriched_latest()
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assert cached_date == cn_today()
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assert cached.select("symbol", "name").sort("symbol").to_dicts() == [
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{"symbol": "000001.SZ", "name": "平安银行"},
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{"symbol": "600000.SH", "name": "浦发银行"},
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]
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assert cached["total_shares"].null_count() == 0
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assert cached["float_shares"].null_count() == 0
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persisted = pl.read_parquet(
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tmp_path / "kline_daily_enriched" / f"date={cn_today().isoformat()}" / "part.parquet"
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)
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assert "name" not in persisted.columns
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assert "total_shares" not in persisted.columns
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assert "float_shares" not in persisted.columns
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def test_history_strategy_monitor_keeps_live_row_with_exclude_st_enabled(tmp_path):
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strategy_dir = tmp_path / "strategies"
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strategy_dir.mkdir()
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(strategy_dir / "history_strategy.py").write_text(
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"""import polars as pl
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META = {
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"id": "history_strategy",
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"name": "历史策略",
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"basic_filter": {"exclude_st": True},
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}
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LOOKBACK_DAYS = 2
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def filter_history(df: pl.DataFrame, params: dict) -> pl.DataFrame:
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return df
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""",
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encoding="utf-8",
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)
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repo = _repo(tmp_path / "data")
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live = _live_row("600000.SH", 10.0).with_columns(
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pl.lit(30_000_000.0).alias("amount")
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)
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repo.flush_live_enriched_asset("stock", live)
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current, _ = repo.get_enriched_latest()
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history = current.with_columns(pl.lit(cn_today() - timedelta(days=3)).alias("date"))
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monitor = MonitorRuleEngine()
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monitor.set_strategy_engine(StrategyEngine([Path(strategy_dir)]))
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monitor.set_history_loader(lambda _as_of, _lookback: history)
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monitor.set_rules([{
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"id": "history_strategy_monitor",
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"name": "历史策略监控",
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"type": "strategy",
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"asset_type": "stock",
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"strategy_id": "history_strategy",
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"scope": "all",
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}])
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monitor.evaluate(current)
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assert monitor.latest_strategy_results()["history_strategy"]["total"] == 1
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