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https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
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shy3130
d0a14b5c1b
上修复 (keep_strategy_cache 沿数据写入链放行) 后线上复现: 每轮拉取 成功后 12ms 缓存仍被清空。clear_cache 新增调用链日志抓到真凶 — ExtConfigStore.upsert 无条件触发 _invalidate_ext_derived: 调度器每轮 拉取要回写 last_run/last_status/next_run 共 2-3 次配置, 每次都全清 策略结果缓存, 绕过了已放行的数据写入链路。 upsert 增加 keep_strategy_cache 参数 (默认 False 保持 UI 保存配置/ 手动变更的全清语义), 拉取循环内 4 处例行回写全部传 True。
487 lines
20 KiB
Python
487 lines
20 KiB
Python
"""扩展表字段 → 因子/信号接入测试。
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覆盖: 命名与数值过滤 / 注册表惰性同步 / 时序按日 PIT 对齐 / 快照仅单日帧
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门控 / 自定义信号消费 / 评分引用 / 写入后缓存失效 / compute_signals 集成。
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"""
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from __future__ import annotations
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from datetime import date
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import polars as pl
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import pytest
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from app.factors import ext_factors
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from app.factors.ext_factors import ext_factor_specs
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from app.factors.registry import all_factors, get_factor
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from app.services.ext_data import (
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ExtConfig,
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ExtConfigStore,
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ExtField,
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_load_all_cache,
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write_ext_parquet,
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)
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from app.strategy import custom_signals
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COL = "ext_tags_hot" # config_id=tags, field=hot
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@pytest.fixture(autouse=True)
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def _clean_caches():
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_load_all_cache.clear()
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ext_factors._frame_cache.clear()
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ext_factors._sync_state = None
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yield
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_load_all_cache.clear()
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ext_factors._frame_cache.clear()
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ext_factors._sync_state = None
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# 清理注册表里残留的 ext_ 条目, 不污染其他测试。
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# 直接遍历 _REGISTRY 而不经 all_factors() — 后者会触发惰性同步,
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# 在 monkeypatch 已还原后把真实数据目录的配置注册进来。
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from app.factors import registry as _registry
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for fid in [k for k in list(_registry._REGISTRY) if k.startswith(ext_factors.EXT_PREFIX)]:
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_registry.unregister_factor(fid)
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@pytest.fixture
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def data_dir(tmp_path, monkeypatch):
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"""统一把 settings.data_dir 指向 tmp (ext_factors/registry 默认目录解析)。"""
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from app import config as app_config
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monkeypatch.setattr(app_config.settings, "data_dir", tmp_path)
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return tmp_path
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def _mk_config(data_dir, cid="tags", mode="timeseries", fields=None):
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cfg = ExtConfig(
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id=cid, label="题材标签", mode=mode,
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fields=fields or [
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ExtField(name="hot", dtype="float"),
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ExtField(name="cnt", dtype="int"),
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ExtField(name="name", dtype="string"), # 非数值: 不应暴露
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],
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)
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ExtConfigStore(data_dir).upsert(cfg)
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return cfg
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def _frame(rows) -> pl.DataFrame:
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return pl.DataFrame(
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rows,
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schema={"symbol": pl.Utf8, "date": pl.Utf8, "close": pl.Float64},
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orient="row",
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).sort(["symbol", "date"])
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# ── 命名与注册 ────────────────────────────────────────────
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def test_column_name_sanitization():
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assert ext_factors.ext_column_name("tags", "hot") == "ext_tags_hot"
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assert ext_factors.ext_column_name("tags", "a-b c") == "ext_tags_a_b_c" # 非单词字符转下划线
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# 中文字段名保留 (预设表字段多为中文, 折叠会互相碰撞)
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assert ext_factors.ext_column_name("tags", "所属概念") == "ext_tags_所属概念"
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assert ext_factors.ext_column_name("tags", "所属概念") != ext_factors.ext_column_name("tags", "股票简称")
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def test_numeric_only_specs(data_dir):
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_mk_config(data_dir)
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specs = ext_factors.ext_factor_specs(data_dir)
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ids = {s.id for s in specs}
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assert "ext_tags_hot" in ids and "ext_tags_cnt" in ids
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assert "ext_tags_name" not in ids # string 字段不进入数值口径
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# 中文名的数值字段: 列照常 join, 但不注册因子 (DSL 标识符 ASCII-only)
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_mk_config(data_dir, cid="cn1", mode="snapshot",
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fields=[ExtField(name="涨停数", dtype="int")])
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cn_specs = {s.id for s in ext_factors.ext_factor_specs(data_dir)}
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assert ext_factors.ext_column_name("cn1", "涨停数") == "ext_cn1_涨停数"
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assert "ext_cn1_涨停数" not in cn_specs
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spec = next(s for s in specs if s.id == "ext_tags_hot")
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assert spec.kind == "base" and not spec.dependencies # 已物化列自身
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assert spec.group == "扩展数据"
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def test_ensure_synced_registers_and_unregisters(data_dir):
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_mk_config(data_dir)
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assert get_factor(COL) is None
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ext_factors.ensure_synced(data_dir)
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assert get_factor(COL) is not None
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assert COL in custom_signals.allowed_fields() # 信号字段白名单自动并入
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# 删除配置 → 下次同步注销
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ExtConfigStore(data_dir).delete("tags")
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ext_factors.invalidate_ext_caches(data_dir)
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ext_factors.ensure_synced(data_dir)
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assert get_factor(COL) is None
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assert COL not in custom_signals.allowed_fields()
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def test_all_factors_lazy_sync(data_dir):
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_mk_config(data_dir)
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assert COL in {s.id for s in all_factors()} # all_factors 内部惰性同步
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# ── 时序按日对齐 (PIT) ────────────────────────────────────
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def test_timeseries_exact_date_alignment(data_dir):
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cfg = _mk_config(data_dir, mode="timeseries")
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [0.9]}),
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cfg, data_dir, snapshot_date=date(2026, 1, 5),
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)
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH", "000001.SZ"], "hot": [0.2, 0.7]}),
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cfg, data_dir, snapshot_date=date(2026, 1, 6),
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)
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frame = _frame([
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("600000.SH", "2026-01-05", 10.0),
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("600000.SH", "2026-01-06", 11.0),
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("600000.SH", "2026-01-07", 12.0), # 无分区 → null
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("000001.SZ", "2026-01-06", 20.0),
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("000001.SZ", "2026-01-07", 21.0), # 无分区 → null
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])
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out = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
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assert COL in out.columns
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by_key = {(r[0], r[1]): r[2] for r in out.select("symbol", "date", COL).rows()}
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assert by_key[("600000.SH", "2026-01-05")] == 0.9
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assert by_key[("600000.SH", "2026-01-06")] == 0.2
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assert by_key[("000001.SZ", "2026-01-06")] == 0.7
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assert by_key[("600000.SH", "2026-01-07")] is None # 缺分区 → null, 不前视填充
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assert by_key[("000001.SZ", "2026-01-07")] is None
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def test_timeseries_no_lookahead_across_dates(data_dir):
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"""历史帧只能看到各日期自己的值: d2 的高值不得泄露到 d1 行。"""
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cfg = _mk_config(data_dir, mode="timeseries")
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [0.1]}),
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cfg, data_dir, snapshot_date=date(2026, 1, 5),
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)
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [9.9]}),
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cfg, data_dir, snapshot_date=date(2026, 1, 6),
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)
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frame = _frame([
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("600000.SH", "2026-01-05", 10.0),
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("600000.SH", "2026-01-06", 11.0),
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])
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out = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
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assert out[COL].to_list() == [0.1, 9.9]
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# ── 快照门控 ──────────────────────────────────────────────
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def test_snapshot_gated_off_history_frames(data_dir):
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cfg = _mk_config(data_dir, mode="snapshot")
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [1.5]}),
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cfg, data_dir, snapshot_date=date(2026, 1, 6),
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)
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hist = _frame([
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("600000.SH", "2026-01-05", 10.0),
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("600000.SH", "2026-01-06", 11.0),
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])
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out = ext_factors.attach_ext_columns(hist, include_snapshot=False, data_dir=data_dir)
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assert COL not in out.columns # 多日历史帧禁止注入快照 (未来函数)
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today = _frame([("600000.SH", "2026-01-06", 11.0)])
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out2 = ext_factors.attach_ext_columns(today, include_snapshot=True, data_dir=data_dir)
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assert COL in out2.columns and out2[COL].to_list() == [1.5]
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# ── 信号消费 / 评分引用 ───────────────────────────────────
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def _save_signal(data_dir, sid="ext_hot", left=COL):
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custom_signals.save_one(data_dir, {
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"id": sid, "name": "题材热度", "kind": "entry", "enabled": True,
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"conditions": [{"left": left, "op": ">", "right": "0.5", "leftDays": 0, "rightDays": 0}],
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})
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def test_signal_validate_and_inject_with_ext_field(data_dir):
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_mk_config(data_dir, mode="timeseries")
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_save_signal(data_dir)
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sig = custom_signals.load_all(data_dir)[0]
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custom_signals.validate(sig) # ext 字段在白名单 → 不抛错
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH", "000001.SZ"], "hot": [0.9, 0.2]}),
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ExtConfigStore(data_dir).get("tags"), data_dir, snapshot_date=date(2026, 1, 5),
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)
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frame = _frame([
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("600000.SH", "2026-01-05", 10.0),
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("000001.SZ", "2026-01-05", 20.0),
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])
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# 与 compute_signals 相同顺序: 先 attach 扩展列, 再编译注入
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frame = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
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exprs = custom_signals.build_expressions([sig])
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out = custom_signals.inject(frame, exprs)
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# 排序后 000001.SZ (hot=0.2) 在前, 600000.SH (hot=0.9) 在后
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assert out["csg_ext_hot"].to_list() == [False, True]
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def test_scoring_value_expr_resolves_ext_column():
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from app.strategy.scoring import scoring_value_expr
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assert scoring_value_expr(["symbol", COL], COL) is not None # 列存在 → 直接引用
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assert scoring_value_expr(["symbol"], COL) is None # 缺列 → 不可计算 (非伪装零分)
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# ── 失效链路 ──────────────────────────────────────────────
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def test_write_invalidates_frame_cache(data_dir):
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cfg = _mk_config(data_dir, mode="timeseries")
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frame = _frame([("600000.SH", "2026-01-05", 10.0)])
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out1 = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
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assert COL not in out1.columns # 尚无数据 → 不产列 (引用方按缺列优雅降级)
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# write_ext_parquet 内部调用 _invalidate_ext_derived → 帧缓存失效
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [0.8]}),
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cfg, data_dir, snapshot_date=date(2026, 1, 5),
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)
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out2 = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
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assert out2[COL].to_list() == [0.8]
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def test_routine_pull_keeps_strategy_cache_but_default_clears(data_dir):
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"""定时拉取 (keep_strategy_cache=True) 只失效扩展帧缓存, 不销毁策略结果。
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策略页依赖 strategy_cache 秒加载; 周期性拉取每轮全清会让页面在两次
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全量重算之间整页空白。手动上传/配置变更 (默认路径) 保持全清旧行为。
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"""
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from app.services import strategy_cache
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cfg = _mk_config(data_dir, mode="timeseries")
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strategy_cache.write_cache(
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data_dir, "2026-01-05",
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{"s1": {"total": 1, "as_of": "2026-01-05", "rows": []}},
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)
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [0.8]}),
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cfg, data_dir, snapshot_date=date(2026, 1, 5),
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keep_strategy_cache=True,
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)
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# 策略结果保留; 扩展帧缓存仍失效 → 新值立即可见
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cached = strategy_cache.read_cache(data_dir) or {}
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assert cached.get("results", {}).get("s1", {}).get("total") == 1
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frame = _frame([("600000.SH", "2026-01-05", 10.0)])
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out = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
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assert out[COL].to_list() == [0.8]
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# 默认路径 (手动写入): 全清
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [0.9]}),
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cfg, data_dir, snapshot_date=date(2026, 1, 5),
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)
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assert strategy_cache.read_cache(data_dir) is None
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def test_scheduler_status_upsert_keeps_strategy_cache(data_dir):
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"""定时拉取循环的 last_run/next_run 例行回写 (keep_strategy_cache=True)
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不清策略结果缓存; UI 保存配置 (默认) 仍全清。
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线上事故: 每轮拉取成功后 store.upsert(fresh) 状态回写触发全清, 数据
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写入链路放行后 12ms 缓存仍被清空 —— 拉取循环内所有回写都须放行。
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"""
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from app.services import strategy_cache
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from app.services.ext_data import ExtConfigStore
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cfg = _mk_config(data_dir, mode="timeseries")
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store = ExtConfigStore(data_dir)
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strategy_cache.write_cache(
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data_dir, "2026-01-05",
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{"s1": {"total": 1, "as_of": "2026-01-05", "rows": []}},
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)
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# 调度器例行回写 (last_run/next_run): 保留策略结果
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store.upsert(cfg, keep_strategy_cache=True)
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cached = strategy_cache.read_cache(data_dir) or {}
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assert cached.get("results", {}).get("s1", {}).get("total") == 1
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# UI 保存配置 (字段集可能变化): 默认全清
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store.upsert(cfg)
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assert strategy_cache.read_cache(data_dir) is None
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def test_config_field_change_invalidates_sync(data_dir):
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_mk_config(data_dir)
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ext_factors.ensure_synced(data_dir)
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assert get_factor(COL) is not None
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# 改字段集 (去掉 hot): upsert 触发失效, 再同步后注销
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cfg2 = ExtConfig(
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id="tags", label="题材标签", mode="timeseries",
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fields=[ExtField(name="cnt", dtype="int")],
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)
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ExtConfigStore(data_dir).upsert(cfg2)
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ext_factors.ensure_synced(data_dir)
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assert get_factor(COL) is None
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assert get_factor("ext_tags_cnt") is not None
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# ── compute_signals 集成 (历史路径) ───────────────────────
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def test_compute_signals_attaches_ext_columns(data_dir):
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from app.indicators import pipeline
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pipeline.invalidate_custom_signals()
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_mk_config(data_dir, mode="timeseries")
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [0.9]}),
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ExtConfigStore(data_dir).get("tags"), data_dir, snapshot_date=date(2026, 1, 5),
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)
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_save_signal(data_dir)
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# 快照配置即使存在也不得进入历史帧
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snap = _mk_config(data_dir, cid="snap1", mode="snapshot")
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write_ext_parquet(
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pl.DataFrame({"symbol": ["600000.SH"], "hot": [1.5]}),
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snap, data_dir, snapshot_date=date(2026, 1, 6),
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)
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frame = _frame([("600000.SH", "2026-01-05", 10.0)])
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try:
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out = pipeline.compute_signals(frame, needed={"csg_ext_hot"})
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finally:
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pipeline.invalidate_custom_signals()
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assert COL in out.columns
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assert "ext_snap1_hot" not in out.columns # 历史帧快照门控
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assert out["csg_ext_hot"].to_list() == [True]
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# ── string 扩展字段 (概念/行业归属) ───────────────────────
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STR_COL = "ext_tags_cat" # config_id=tags, string 字段 cat
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def _mk_str_config(data_dir):
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return _mk_config(data_dir, fields=[
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ExtField(name="hot", dtype="float"),
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ExtField(name="cat", dtype="string"), # 归属字段, 分号拼接
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])
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def test_string_fields_exposed_for_signals_only(data_dir):
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_mk_str_config(data_dir)
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entries = ext_factors.ext_string_field_entries(data_dir)
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assert {e["key"] for e in entries} == {STR_COL}
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assert STR_COL in ext_factors.ext_string_fields(data_dir)
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assert STR_COL in custom_signals.allowed_fields()
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# 不注册为因子: IC/排序是数值口径
|
|
assert get_factor(STR_COL) is None
|
|
assert STR_COL not in {s.id for s in ext_factor_specs(data_dir)}
|
|
|
|
|
|
def test_string_validate_accepts_and_rejects(data_dir):
|
|
_mk_str_config(data_dir)
|
|
ok = {
|
|
"id": "t_cat", "name": "概念归属", "kind": "entry",
|
|
"conditions": [{"left": STR_COL, "op": "contains", "right": "AI", "leftDays": 0, "rightDays": 0}],
|
|
}
|
|
custom_signals.validate(ok) # contains + 字符串字面量
|
|
|
|
def _bad(**patch):
|
|
c = dict(left=STR_COL, op="contains", right="AI", leftDays=0, rightDays=0)
|
|
c.update(patch)
|
|
return {"id": "t_bad", "name": "x", "kind": "entry", "conditions": [c]}
|
|
|
|
with pytest.raises(ValueError, match="仅支持"):
|
|
custom_signals.validate(_bad(op=">")) # 字符串字段禁用数值运算符
|
|
with pytest.raises(ValueError, match="非空字符串"):
|
|
custom_signals.validate(_bad(right=" "))
|
|
with pytest.raises(ValueError, match="不支持字段引用"):
|
|
custom_signals.validate(_bad(right="field:close"))
|
|
with pytest.raises(ValueError, match="contains 仅用于字符串"):
|
|
custom_signals.validate({ # 数值字段禁用 contains
|
|
"id": "t_bad2", "name": "x", "kind": "entry",
|
|
"conditions": [{"left": "close", "op": "contains", "right": "AI", "leftDays": 0, "rightDays": 0}],
|
|
})
|
|
|
|
|
|
def test_string_contains_inject_semantics(data_dir):
|
|
_mk_str_config(data_dir)
|
|
write_ext_parquet(
|
|
pl.DataFrame({
|
|
"symbol": ["600000.SH", "000001.SZ", "300750.SZ"],
|
|
"cat": ["AI;芯片", "半导体", None], # null: 无归属
|
|
}),
|
|
ExtConfigStore(data_dir).get("tags"), data_dir, snapshot_date=date(2026, 1, 5),
|
|
)
|
|
sig = {
|
|
"id": "cat_ai", "name": "AI题材", "kind": "entry", "enabled": True,
|
|
"conditions": [{"left": STR_COL, "op": "contains", "right": "AI", "leftDays": 0, "rightDays": 0}],
|
|
}
|
|
frame = _frame([
|
|
("300750.SZ", "2026-01-05", 10.0), # null 归属 → 不命中
|
|
("600000.SH", "2026-01-05", 11.0),
|
|
("000001.SZ", "2026-01-05", 20.0),
|
|
])
|
|
frame = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
|
|
out = custom_signals.inject(frame, custom_signals.build_expressions([sig]))
|
|
got = dict(zip(out["symbol"], out["csg_cat_ai"], strict=True))
|
|
assert got["600000.SH"] is True # "AI;芯片" 包含 AI
|
|
assert not got["000001.SZ"] # "半导体" 不含
|
|
assert not got["300750.SZ"] # null → 不误报
|
|
|
|
|
|
def test_string_contains_is_literal_not_regex(data_dir):
|
|
"""右值按字面量匹配: '.' 不当正则万能匹配。"""
|
|
_mk_str_config(data_dir)
|
|
write_ext_parquet(
|
|
pl.DataFrame({"symbol": ["600000.SH"], "cat": ["AI;芯片"]}),
|
|
ExtConfigStore(data_dir).get("tags"), data_dir, snapshot_date=date(2026, 1, 5),
|
|
)
|
|
sig_dot = {
|
|
"id": "cat_dot", "name": "x", "kind": "entry", "enabled": True,
|
|
"conditions": [{"left": STR_COL, "op": "contains", "right": ".", "leftDays": 0, "rightDays": 0}],
|
|
}
|
|
frame = _frame([("600000.SH", "2026-01-05", 10.0)])
|
|
frame = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
|
|
out = custom_signals.inject(frame, custom_signals.build_expressions([sig_dot]))
|
|
assert out["csg_cat_dot"].to_list() == [False] # 正则下 '.' 会匹配任意字符
|
|
|
|
|
|
def test_string_equals_and_mixed_conditions(data_dir):
|
|
_mk_str_config(data_dir)
|
|
write_ext_parquet(
|
|
pl.DataFrame({"symbol": ["600000.SH", "000001.SZ"], "cat": ["半导体", "银行"], "hot": [0.9, 0.2]}),
|
|
ExtConfigStore(data_dir).get("tags"), data_dir, snapshot_date=date(2026, 1, 5),
|
|
)
|
|
sig = {
|
|
"id": "semi_strong", "name": "强势半导体", "kind": "entry", "enabled": True,
|
|
"conditions": [
|
|
{"left": STR_COL, "op": "==", "right": "半导体", "leftDays": 0, "rightDays": 0},
|
|
{"left": COL, "op": ">", "right": "0.5", "leftDays": 0, "rightDays": 0}, # 混合: 归属且热度
|
|
],
|
|
}
|
|
frame = _frame([
|
|
("600000.SH", "2026-01-05", 10.0),
|
|
("000001.SZ", "2026-01-05", 20.0),
|
|
])
|
|
frame = ext_factors.attach_ext_columns(frame, include_snapshot=False, data_dir=data_dir)
|
|
out = custom_signals.inject(frame, custom_signals.build_expressions([sig]))
|
|
got = dict(zip(out["symbol"], out["csg_semi_strong"], strict=True))
|
|
assert got["600000.SH"] is True
|
|
assert not got["000001.SZ"]
|
|
|
|
|
|
def test_cjk_string_field_end_to_end(data_dir):
|
|
"""预设表场景: 中文字段名 (所属概念) 列名保留中文, 信号全链路可用。"""
|
|
ExtConfigStore(data_dir).upsert(ExtConfig(
|
|
id="ths_concepts", label="扩展概念", mode="snapshot",
|
|
fields=[ExtField(name="所属概念", dtype="string")],
|
|
))
|
|
write_ext_parquet(
|
|
pl.DataFrame({"symbol": ["600000.SH"], "所属概念": ["AI芯片;机器人"]}),
|
|
ExtConfigStore(data_dir).get("ths_concepts"), data_dir, snapshot_date=date(2026, 1, 6),
|
|
)
|
|
col = "ext_ths_concepts_所属概念"
|
|
assert col in custom_signals.allowed_fields()
|
|
sig = {
|
|
"id": "robot", "name": "机器人题材", "kind": "entry", "enabled": True,
|
|
"conditions": [{"left": col, "op": "contains", "right": "机器人", "leftDays": 0, "rightDays": 0}],
|
|
}
|
|
custom_signals.validate(sig)
|
|
frame = _frame([("600000.SH", "2026-01-06", 10.0)])
|
|
frame = ext_factors.attach_ext_columns(frame, include_snapshot=True, data_dir=data_dir)
|
|
assert col in frame.columns
|
|
out = custom_signals.inject(frame, custom_signals.build_expressions([sig]))
|
|
assert out["csg_robot"].to_list() == [True]
|