按「测试腐化(a)/ 源码缺陷(b)/ 测试污染(c)」逐项定性,仅改 tests/: - 外机绝对路径(4): 迁移文件路径改为相对仓库根解析(沿用 test_regressions._read 约定),断言内容保持不变。 - cutoff 用例(4+1): mock 未生效的真因是 _agent_provider 被换成同步 lambda,await 抛 TypeError 被生产代码吞掉后 IndexError;改为 async mock 并按 run_specialists/load_match_header/_agent_provider 的真实契约 打补丁。degraded 用例再加 _upsert_prediction 顶层 kwargs(model)采集。 - 陈旧断言(3): agent 键按现契约断言中文映射;h2h mock 改 async; Match.stats 按设计为 lazy="select",从 MATCH_RELATIONS 移出并单独 固化该设计决定。 - P0-3 守卫(1): seg 越界扫到下游 stats 管线导致误报,改为按缩进收口; 合法形状含经 raw 派生变量中转的写法,并补元测试确保守卫仍能抓到回归。 - 交叉污染(6): test_multi_agent_cutoff 用 patch.object 精确还原,消除 裸赋值泄漏的同步 mock;现已验证顺序无关。
124 lines
4.8 KiB
Python
124 lines
4.8 KiB
Python
"""回归测试: 预测唯一约束修复 —— live 与 backtest 可共存。
|
|
|
|
验证:
|
|
1. 唯一约束包含 mode + run_type
|
|
2. 同一场比赛 live 与 backtest 预测可共存,互不覆盖
|
|
3. _upsert_prediction 正确区分 run_type
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
import inspect
|
|
from pathlib import Path
|
|
|
|
from pydantic import BaseModel
|
|
import pytest
|
|
|
|
from src.db.models import Prediction, UniqueConstraint, CheckConstraint
|
|
|
|
# 仓库根目录下的 alembic 迁移目录 —— 相对本测试文件解析,
|
|
# 避免硬编码某台机器/CI 上的绝对路径(见 tests/test_regressions.py 的 _read 约定)。
|
|
REPO_ROOT = Path(__file__).resolve().parent.parent
|
|
MIGRATION_PATH = REPO_ROOT / "alembic" / "versions" / "0013_predictions_unique_constraint_mode_run_type.py"
|
|
|
|
|
|
class TestUniqueConstraint:
|
|
"""验证唯一约束包含 mode + run_type。"""
|
|
|
|
def test_constraint_columns(self):
|
|
"""唯一约束应包含 match_id, provider, model, mode, run_type。"""
|
|
uc = [
|
|
c for c in Prediction.__table__.constraints
|
|
if isinstance(c, UniqueConstraint) and "match" in c.name
|
|
]
|
|
assert len(uc) == 1
|
|
cols = [c.name for c in uc[0].columns]
|
|
assert cols == ["match_id", "provider", "model", "mode", "run_type"]
|
|
|
|
def test_run_type_check_constraint(self):
|
|
"""应有 run_type 的 check constraint。"""
|
|
cc = [
|
|
c for c in Prediction.__table__.constraints
|
|
if isinstance(c, CheckConstraint) and "run_type" in c.name
|
|
]
|
|
assert len(cc) == 1
|
|
|
|
def test_run_type_column_exists(self):
|
|
"""run_type 列应存在且 NOT NULL,默认 'live'。"""
|
|
cols = {c.name: c for c in Prediction.__table__.columns}
|
|
assert "run_type" in cols
|
|
assert cols["run_type"].nullable is False
|
|
# 默认值
|
|
assert cols["run_type"].default.arg == "live" if cols["run_type"].default else True
|
|
|
|
|
|
class TestUpsertPredictionSignature:
|
|
"""验证 _upsert_prediction 函数签名包含 run_type。"""
|
|
|
|
def test_signature_has_run_type(self):
|
|
from src.llm.predict import _upsert_prediction
|
|
|
|
sig = inspect.signature(_upsert_prediction)
|
|
assert "run_type" in sig.parameters
|
|
|
|
def test_signature_has_backtest_in_predict_match(self):
|
|
from src.llm.predict import predict_match
|
|
|
|
sig = inspect.signature(predict_match)
|
|
assert "backtest" in sig.parameters
|
|
|
|
def test_signature_has_backtest_in_predict_multi(self):
|
|
from src.llm.agents.orchestrator import predict_match_multi
|
|
|
|
sig = inspect.signature(predict_match_multi)
|
|
assert "backtest" in sig.parameters
|
|
|
|
|
|
class TestMigration:
|
|
"""验证迁移文件存在且内容正确。"""
|
|
|
|
def test_migration_exists(self):
|
|
assert MIGRATION_PATH.is_file(), f"迁移文件不存在: {MIGRATION_PATH}"
|
|
|
|
def test_migration_adds_column_and_constraint(self):
|
|
content = MIGRATION_PATH.read_text(encoding="utf-8")
|
|
|
|
assert 'run_type' in content
|
|
assert 'uq_predictions_match_provider_model_mode_run_type' in content
|
|
assert 'backtest' in content
|
|
assert 'live' in content
|
|
# 验证数据回填逻辑
|
|
assert "UPDATE predictions SET run_type = 'live'" in content
|
|
|
|
|
|
class TestLiveBacktestCoexist:
|
|
"""验证 live 与 backtest 可共存(逻辑验证,无需数据库)。"""
|
|
|
|
def test_different_run_type_allow_coexistence(self):
|
|
"""同一 match_id + provider + model + mode,不同 run_type 应可共存。
|
|
|
|
这是核心修复:之前唯一约束只有 (match_id, provider, model),
|
|
backtest 会覆盖 live 预测。
|
|
"""
|
|
# 模拟两行数据
|
|
class FakeRow:
|
|
def __init__(self, **kw):
|
|
for k, v in kw.items():
|
|
setattr(self, k, v)
|
|
|
|
live = FakeRow(match_id=1, provider="openai", model="gpt-4o", mode="single", run_type="live")
|
|
backtest = FakeRow(match_id=1, provider="openai", model="gpt-4o", mode="single", run_type="backtest")
|
|
|
|
# 两者唯一键不同(因为 run_type 不同)
|
|
live_key = (live.match_id, live.provider, live.model, live.mode, live.run_type)
|
|
backtest_key = (backtest.match_id, backtest.provider, backtest.model, backtest.mode, backtest.run_type)
|
|
|
|
assert live_key != backtest_key, "live 与 backtest 应有不同的唯一键"
|
|
assert live_key == (1, "openai", "gpt-4o", "single", "live")
|
|
assert backtest_key == (1, "openai", "gpt-4o", "single", "backtest")
|
|
|
|
def test_same_run_type_prevents_duplicate(self):
|
|
"""相同 run_type 的重复预测仍应被约束阻止。"""
|
|
key1 = (1, "openai", "gpt-4o", "single", "live")
|
|
key2 = (1, "openai", "gpt-4o", "single", "live")
|
|
assert key1 == key2, "相同 run_type 应有相同唯一键,应被约束阻止"
|