rebuild(stage-9): deliver deterministic intelligent screening
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leefer
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from __future__ import annotations
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import json
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import pytest
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from backend.database.connection import Database
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from backend.database.migrations import MIGRATIONS, MigrationRunner
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from backend.features.screener.catalog import (
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CatalogError,
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factor_catalog,
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strategy_catalog,
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validate_formula,
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)
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from backend.features.screener.engine import execute_formula
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from backend.features.screener.repository import ScreenerRepository, decode_track
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from backend.features.screener.service import automatic_strategies
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def _formula(field: str = "close", *, minimum: float = 0) -> dict:
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return {
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"universe": {"exclude_st": True, "listed_days_min": 120},
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"filters": [{"field": field, "op": ">", "value": minimum}],
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"score": [{"field": field, "weight": 1.0, "direction": "desc"}],
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"limit": 10,
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"min_score": 0,
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}
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def _row(identifier: str, close: float | None) -> dict:
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return {
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"identifier": identifier,
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"code": identifier.split(".")[0],
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"name": identifier,
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"sector": "测试行业",
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"listed_days": 500,
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"is_st": False,
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"close": close,
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"pct_chg": 1,
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"amount_billion": 2,
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}
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def _users(database: Database) -> None:
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with database.transaction() as connection:
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connection.executemany(
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"""
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INSERT INTO users (
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id, username, username_key, password_hash, is_admin,
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status, created_at, updated_at
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) VALUES (?, ?, ?, 'hash', 0, 'active', '2026-07-30', '2026-07-30')
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""",
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((1, "account-a", "account-a"), (2, "account-b", "account-b")),
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)
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def _snapshot(database: Database, repository: ScreenerRepository) -> int:
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with database.transaction() as connection:
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return repository.save_factor_snapshot(
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connection,
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trade_date="2026-07-30",
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version="fixture-v1",
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observed_at="2026-07-30T15:10:00+08:00",
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state="final",
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sources=["fixture"],
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coverage={"market": 1},
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rows=[_row("000001.SZ", 10)],
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)
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def test_catalog_has_the_exact_reviewed_scope() -> None:
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factors = factor_catalog()
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strategies = strategy_catalog()
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assert len(factors["factors"]) == 109
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assert len(strategies) == 36
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assert sum(item["kind"] == "stage" for item in strategies) == 7
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assert sum(item["kind"] == "curated" for item in strategies) == 29
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assert {item["id"] for item in strategies if item["kind"] == "curated"} == {
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f"curated-{index:02d}" for index in range(1, 30)
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}
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def test_curated_strategies_run_independently_of_emotion_phase() -> None:
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for regime in ("ice", "repair", "fermentation", "climax", "divergence", "retreat"):
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_stage, curated = automatic_strategies(regime)
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assert len(curated) == 29
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assert {item["id"] for item in curated} == {
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f"curated-{index:02d}" for index in range(1, 30)
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}
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def test_formula_is_deterministic_and_best_value_scores_first() -> None:
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rows = [_row("000002.SZ", 20), _row("000001.SZ", 20), _row("000003.SZ", 10)]
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first = execute_formula(rows, _formula(), {"market": 1})
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second = execute_formula(list(reversed(rows)), _formula(), {"market": 1})
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assert first == second
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assert [item["identifier"] for item in first["items"]] == [
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"000001.SZ",
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"000002.SZ",
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"000003.SZ",
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]
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assert first["items"][0]["score"] == 1
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assert first["items"][-1]["score"] == 0
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def test_missing_required_factor_and_complete_no_match_are_distinct() -> None:
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incomplete = execute_formula(
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[{**_row("000001.SZ", 10), "roic": None}],
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_formula("roic"),
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{"financial": 1},
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)
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no_signal = execute_formula(
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[_row("000001.SZ", 10)],
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_formula(minimum=100),
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{"market": 1},
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)
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assert incomplete["status"] == "data_incomplete"
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assert incomplete["missing_fields"] == ["roic"]
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assert no_signal["status"] == "no_signal"
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assert no_signal["missing_fields"] == []
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def test_formula_weights_must_total_one_hundred_percent() -> None:
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formula = _formula()
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formula["score"][0]["weight"] = 0.9
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with pytest.raises(CatalogError, match="100%"):
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validate_formula(formula)
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def test_formula_rejects_invalid_comparisons_and_duplicate_scores() -> None:
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malformed = _formula()
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malformed["filters"][0] = {"field": "close", "op": "between", "value": [20]}
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with pytest.raises(CatalogError, match="两个边界"):
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validate_formula(malformed)
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duplicate = _formula()
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duplicate["score"].append({"field": "close", "weight": 0.5, "direction": "desc"})
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duplicate["score"][0]["weight"] = 0.5
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with pytest.raises(CatalogError, match="不能重复"):
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validate_formula(duplicate)
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def test_custom_strategies_and_tracks_are_account_isolated(tmp_path) -> None:
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database = Database(tmp_path / "screener.db")
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MigrationRunner(database).upgrade(MIGRATIONS)
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repository = ScreenerRepository()
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_users(database)
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snapshot_id = _snapshot(database, repository)
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with database.transaction() as connection:
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first = repository.save_custom_strategy(connection, 1, "我的策略", _formula())
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repository.save_custom_strategy(connection, 2, "我的策略", _formula())
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run = repository.begin_run(
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connection,
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owner_user_id=None,
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mode="curated",
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strategy_id="curated-01",
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strategy_name="测试策略",
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strategy_version=1,
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selection_date="2026-07-30",
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factor_snapshot_id=snapshot_id,
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)
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repository.finish_run(
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connection,
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int(run["id"]),
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status="completed",
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coverage=1,
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missing_fields=[],
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result=[{**_row("000001.SZ", 10), "score": 1}],
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)
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repository.add_track(
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connection,
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user_id=1,
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run=run,
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candidate={**_row("000001.SZ", 10), "score": 1},
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)
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with database.read() as connection:
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assert [row["id"] for row in repository.custom_strategies(connection, 1)] == [first["id"]]
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assert len(repository.custom_strategies(connection, 2)) == 1
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assert len(repository.tracks(connection, 1)) == 1
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assert repository.tracks(connection, 2) == ()
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def test_running_a_strategy_never_creates_tracking_rows(tmp_path) -> None:
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database = Database(tmp_path / "runs.db")
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MigrationRunner(database).upgrade(MIGRATIONS)
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repository = ScreenerRepository()
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_users(database)
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snapshot_id = _snapshot(database, repository)
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with database.transaction() as connection:
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run = repository.begin_run(
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connection,
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owner_user_id=None,
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mode="curated",
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strategy_id="curated-01",
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strategy_name="测试策略",
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strategy_version=1,
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selection_date="2026-07-30",
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factor_snapshot_id=snapshot_id,
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)
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repository.finish_run(
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connection,
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int(run["id"]),
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status="completed",
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coverage=1,
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missing_fields=[],
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result=[{**_row("000001.SZ", 10), "score": 1}],
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)
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with database.read() as connection:
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assert repository.tracks(connection, 1) == ()
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stored = connection.execute(
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"SELECT result_json FROM screener_runs WHERE id = ?", (run["id"],)
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).fetchone()
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assert len(json.loads(stored["result_json"])) == 1
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def test_tracking_statistics_and_milestone_events_are_persistent_and_idempotent(tmp_path) -> None:
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database = Database(tmp_path / "tracking.db")
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MigrationRunner(database).upgrade(MIGRATIONS)
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repository = ScreenerRepository()
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_users(database)
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snapshot_id = _snapshot(database, repository)
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with database.transaction() as connection:
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run = repository.begin_run(
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connection,
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owner_user_id=None,
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mode="curated",
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strategy_id="curated-01",
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strategy_name="测试策略",
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strategy_version=1,
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selection_date="2026-07-30",
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factor_snapshot_id=snapshot_id,
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)
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repository.finish_run(
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connection,
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int(run["id"]),
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status="completed",
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coverage=1,
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missing_fields=[],
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result=[{**_row("000001.SZ", 10), "score": 1}],
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)
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track_id = repository.add_track(
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connection,
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user_id=1,
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run=run,
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candidate={**_row("000001.SZ", 10), "score": 1},
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)
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bars = (
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("2026-07-31", 10.5, 11.2, 9.5, 11.0),
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("2026-08-03", 11.0, 11.5, 10.0, 10.5),
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("2026-08-04", 10.5, 12.5, 10.2, 12.0),
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("2026-08-05", 12.0, 12.2, 9.0, 11.5),
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("2026-08-06", 11.5, 14.0, 11.0, 13.0),
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)
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for trade_date, open_price, high, low, close in bars:
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repository.save_track_bar(
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connection,
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track_id,
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trade_date,
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{"open": open_price, "high": high, "low": low, "close": close},
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)
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assert repository.record_track_event(connection, track_id, "t1") is True
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assert repository.record_track_event(connection, track_id, "t1") is False
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assert repository.record_track_event(connection, track_id, "t5") is True
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assert repository.record_track_event(connection, track_id, "t5") is False
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with database.read() as connection:
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track = repository.tracks(connection, 1)[0]
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decoded = decode_track(track, repository.track_bars(connection, track_id))
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events = connection.execute(
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"SELECT milestone FROM strategy_track_events WHERE track_id = ? ORDER BY milestone",
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(track_id,),
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).fetchall()
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assert decoded["t1_open_return"] == 5
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assert decoded["t1_return"] == 10
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assert decoded["t3_return"] == 20
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assert decoded["t5_return"] == 30
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assert decoded["max_gain"] == 40
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assert decoded["max_drawdown"] == -10
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assert decoded["observed_days"] == 5
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assert [row["milestone"] for row in events] == ["t1", "t5"]
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def test_repeated_after_close_run_uses_one_persistent_run(tmp_path) -> None:
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database = Database(tmp_path / "idempotent.db")
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MigrationRunner(database).upgrade(MIGRATIONS)
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repository = ScreenerRepository()
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_users(database)
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snapshot_id = _snapshot(database, repository)
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with database.transaction() as connection:
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first = repository.begin_run(
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connection,
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owner_user_id=None,
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mode="curated",
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strategy_id="curated-01",
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strategy_name="测试策略",
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strategy_version=1,
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selection_date="2026-07-30",
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factor_snapshot_id=snapshot_id,
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)
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repository.finish_run(
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connection,
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int(first["id"]),
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status="no_signal",
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coverage=1,
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missing_fields=[],
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result=[],
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)
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repeated = repository.begin_run(
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connection,
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owner_user_id=None,
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mode="curated",
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strategy_id="curated-01",
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strategy_name="测试策略",
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strategy_version=1,
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selection_date="2026-07-30",
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factor_snapshot_id=snapshot_id,
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)
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count = connection.execute("SELECT COUNT(*) AS total FROM screener_runs").fetchone()
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assert repeated["id"] == first["id"]
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assert count["total"] == 1
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