claude_dev
45bc8df46f
NAS 实证: 09-22 晚生成的 universe_cache_0214_0922 止于库内 09-21, 次晨库已 同步 09-22 但同窗补跑命中旧缓存 → 截面缺 09-22 行(section_sanity fail-loud 守卫立功)。生产场景每日新窗=新 key 天然免疫, 补跑场景必中。修=universe. cache_path_for 公式单点 + purge_cache 删除;daily_section 跑批前必清同窗 缓存(vnpy_db=None 时走 cfg 解析同款路径)。 Co-Authored-By: Claude Code <notify@anthropic.com>
182 lines
7.2 KiB
Python
182 lines
7.2 KiB
Python
# tests/factor/test_daily_section.py
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"""每日截面增量生产器(影子盘数据契约): 幂等 merge + sanity + 窗推导."""
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import os
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import sys
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
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import pandas as pd
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import pytest
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from sanguo_factor import daily_section
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def _wide(days, base=1.0):
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"""days(list[str]) × 3 股宽表, 值=base 递增可区分."""
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cols = ["600000.SSE", "000001.SZSE", "300001.SZSE"]
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idx = pd.to_datetime(days)
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return pd.DataFrame({c: [base + i for _ in range(len(days))]
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for i, c in enumerate(cols)}, index=idx)
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def test_merge_appends_new_date(tmp_path):
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main_p = tmp_path / "main.parquet"
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new_p = tmp_path / "new.parquet"
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_wide(["2026-09-10", "2026-09-11"]).to_parquet(main_p)
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_wide(["2026-09-14"], base=9.0).to_parquet(new_p)
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out = daily_section.merge_section(str(main_p), str(new_p))
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got = pd.read_parquet(main_p)
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assert list(got.index.strftime("%Y-%m-%d")) == \
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["2026-09-10", "2026-09-11", "2026-09-14"]
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assert (got.loc["2026-09-14"].to_numpy() == [9.0, 10.0, 11.0]).all()
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assert out["added_dates"] == 1 and out["replaced_dates"] == 0
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def test_merge_replaces_existing_date(tmp_path):
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main_p = tmp_path / "main.parquet"
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_wide(["2026-09-10", "2026-09-11"]).to_parquet(main_p)
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_wide(["2026-09-11"], base=7.0).to_parquet(tmp_path / "new.parquet")
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out = daily_section.merge_section(str(main_p), str(tmp_path / "new.parquet"))
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got = pd.read_parquet(main_p)
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assert len(got) == 2 # 不增行
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assert (got.loc["2026-09-11"].to_numpy() == [7.0, 8.0, 9.0]).all()
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assert out["added_dates"] == 0 and out["replaced_dates"] == 1
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def test_merge_idempotent_rerun_same_day(tmp_path):
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"""同日重跑: 第二次 merge 无新增日期(added=0, replaced=同日覆盖计数),
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值不变(幂等)."""
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main_p = tmp_path / "main.parquet"
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new_p = tmp_path / "new.parquet"
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_wide(["2026-09-10"]).to_parquet(main_p)
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_wide(["2026-09-11"], base=5.0).to_parquet(new_p)
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daily_section.merge_section(str(main_p), str(new_p))
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snap = pd.read_parquet(main_p)
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out2 = daily_section.merge_section(str(main_p), str(new_p))
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assert out2["added_dates"] == 0 and out2["rows_after"] == len(snap)
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pd.testing.assert_frame_equal(pd.read_parquet(main_p), snap)
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def test_sanity_counts_and_turnover(tmp_path):
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"""sanity: 当日行非空数 + 与前一行的进出股票数."""
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main_p = tmp_path / "main.parquet"
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d1 = _wide(["2026-09-10"])
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d1["600000.SSE"] = float("nan") # 当日缺值
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d1["688001.SSE"] = 1.0 # 新上市列
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d2 = _wide(["2026-09-11"])
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d2 = d2.drop(columns=["300001.SZSE"]) # 退市消失
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pd.concat([d1, d2]).to_parquet(main_p)
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s = daily_section.section_sanity(str(main_p), "2026-09-11")
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assert s["date"] == "2026-09-11"
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assert s["non_null"] == 2 # 600000/000001
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# vs 09-10 的非空集: 688001(昨有今无)+300001(退市消失)出,
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# 600000 昨 NaN 今有值 → 视为进(在场=非空口径)
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assert set(s["entered"]) == {"600000.SSE"}
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assert set(s["exited"]) == {"688001.SSE", "300001.SZSE"}
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def test_lookback_window_dates():
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"""窗推导: end 往前 lookback 历史日, 覆盖 WARMUP_BARS(120 交易日)预热."""
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start, end = daily_section.lookback_window("2026-09-22", lookback_days=220)
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assert end == "2026-09-22"
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span = (pd.Timestamp(end) - pd.Timestamp(start)).days
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assert 218 <= span <= 222
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# 默认 lookback 足够 120 交易日预热(~170 历史日)
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assert span >= 170
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def test_purge_cache_formula_and_delete(tmp_path):
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"""universe 缓存: 公式单点 + purge 删除(补跑截数据防线, NAS 09-22 实证)."""
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from sanguo_factor import universe
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db = str(tmp_path / "qt.db")
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p = universe.cache_path_for(db, "2026-02-14", "2026-09-22")
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assert p.endswith("universe_cache_2026-02-14_2026-09-22_all.parquet")
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assert universe.purge_cache(db, "2026-02-14", "2026-09-22") is False # 无文件
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from pathlib import Path
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Path(p).write_bytes(b"x")
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assert universe.purge_cache(db, "2026-02-14", "2026-09-22") is True
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assert not Path(p).exists()
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def test_run_daily_section_purges_universe_cache(db_stock_small, tmp_path, monkeypatch):
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"""跑批前必清同窗 universe 缓存(旧缓存截新数据,09-22 NAS 补跑实证)."""
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from sanguo_factor import universe
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called: list[tuple[str, str]] = []
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monkeypatch.setattr(universe, "purge_cache",
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lambda db, s, e: called.append((s, e)) or True)
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main_p = tmp_path / "sections" / "vma_60.parquet"
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main_p.parent.mkdir(parents=True)
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_wide(["2026-07-09"]).to_parquet(main_p)
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daily_section.run_daily_section(
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"vma_60", end_date="2026-07-10", out_dir=str(tmp_path / "sections"),
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vnpy_db=db_stock_small, eval_db=str(tmp_path / "e.db"),
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tmp_dir=str(tmp_path / "tmpcs"))
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start, end = daily_section.lookback_window("2026-07-10")
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assert (start, end) in called
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def test_run_daily_section_end_to_end(db_stock_small, tmp_path, monkeypatch):
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"""端到端: 合成 5 股 sqlite → 短窗跑批导出 → merge 主 parquet → sanity 齐."""
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from sanguo_factor.batch_eval import run_batch_eval # noqa: F401 导入链可用性
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main_p = tmp_path / "sections" / "vma_60.parquet"
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main_p.parent.mkdir(parents=True)
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_wide(["2026-07-09"]).to_parquet(main_p) # 既有主截面(生产日前一交易日)
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# 合成库 bar 终点 ~2026-07(400 个工作日), 截面日取 bar 内最后交易日
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out = daily_section.run_daily_section(
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"vma_60", end_date="2026-07-10", out_dir=str(tmp_path / "sections"),
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vnpy_db=db_stock_small, eval_db=str(tmp_path / "e.db"),
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tmp_dir=str(tmp_path / "tmpcs"))
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assert out["ok"] is True
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got = pd.read_parquet(main_p)
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dates = list(got.index.strftime("%Y-%m-%d"))
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assert dates[-1] == "2026-07-10" and len(dates) > 1
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assert out["sanity"]["date"] == "2026-07-10"
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assert out["sanity"]["non_null"] > 0
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# ---------------- 合成小库: 5 股 × ~400 bar(覆盖 warmup) ----------------
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@pytest.fixture(scope="module")
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def db_stock_small(tmp_path_factory):
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import numpy as np
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import sqlite3
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ddl = """
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CREATE TABLE dbbardata(
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symbol TEXT, exchange TEXT, datetime TEXT, interval TEXT,
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volume REAL, turnover REAL, open_interest REAL,
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open_price REAL, high_price REAL, low_price REAL, close_price REAL)
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"""
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p = tmp_path_factory.mktemp("dsec")
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db = str(p / "qt.db")
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conn = sqlite3.connect(db)
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conn.execute(ddl)
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days = pd.bdate_range("2025-01-01", periods=400)
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rng = np.random.default_rng(11)
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for j, (sym, ex) in enumerate([("600000", "SSE"), ("000001", "SZSE"),
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("300001", "SZSE"), ("600004", "SSE"),
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("000333", "SZSE")]):
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px = 10.0 + j
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for day in days:
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px = max(px * (1 + rng.normal(0, 0.015)), 0.5)
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conn.execute(
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"INSERT INTO dbbardata VALUES(?,?,?,?,?,?,?,?,?,?,?)",
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(sym, ex, f"{day.date()} 00:00:00", "d", float(rng.integers(1e5, 9e5)),
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px * 1e5, 0, px, px * 1.01, px * 0.99, px))
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conn.commit()
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conn.close()
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return db
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