314 lines
12 KiB
Python
314 lines
12 KiB
Python
"""profile_l3 单测（B3 · 最高档合并防降级 / AML 后大额不回落 / 并发首单）。
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sqlite StaticPool 单连接共享内存库（同 test_alert_service 模式）；
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IntegrityError / 乐观锁丢竞态用 monkeypatch 模拟跨进程交错。
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risk_score 口径：一期不写（恒 NULL，归 R-05 评分模型首写，评审 P3-4 用户拍板）。
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"""
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from datetime import datetime
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import pytest
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from sqlalchemy import create_engine, text
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from sqlalchemy.pool import StaticPool
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from app.repository.risk_repository import RiskRepository
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from app.service.risk.profile_l3 import (
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AML_PENDING_TAG,
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ALERT_TYPE_TIER,
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get_profile_l3,
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highest_tier,
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merge_l3,
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tier_of,
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upsert_profile_l3,
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)
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@pytest.fixture()
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def env():
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engine = create_engine(
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"sqlite://",
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poolclass=StaticPool,
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connect_args={"check_same_thread": False},
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)
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# 口径（评审 P3-3）：以 VARCHAR/TEXT 近似真实 DDL 的 ENUM/SMALLINT/JSON，
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# ENUM 档位防线不在测试 DB 层，由 tier_of 白名单 + highest_tier 保证。
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with engine.begin() as conn:
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conn.execute(
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text(
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"""
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CREATE TABLE customer_profile_l3 (
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customer_id VARCHAR(64) PRIMARY KEY,
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monitor_tier VARCHAR(16) NOT NULL,
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risk_score INTEGER,
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score_dimensions TEXT,
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monitor_tags TEXT,
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last_alert_id VARCHAR(64),
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computed_at TIMESTAMP NOT NULL,
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updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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)
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"""
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)
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)
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repo = RiskRepository(engine=engine)
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yield repo, engine
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engine.dispose()
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def _upsert(repo, cid, alert_type, alert_id=None, tags=None, dims=None, computed_at=None):
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return upsert_profile_l3(
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cid,
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alert_type,
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monitor_tags=tags,
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last_alert_id=alert_id,
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score_dimensions=dims,
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computed_at=computed_at,
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risk_repo=repo,
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)
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def _row(engine, cid):
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with engine.connect() as conn:
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return conn.execute(
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text(
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"SELECT monitor_tier, risk_score, monitor_tags, last_alert_id, computed_at"
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" FROM customer_profile_l3 WHERE customer_id = :cid"
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),
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{"cid": cid},
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).mappings().one()
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# ---------- 映射与纯函数 ----------
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@pytest.mark.parametrize(("alert_type", "tier"), sorted(ALERT_TYPE_TIER.items()))
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def test_alert_type_tier_mapping(alert_type, tier):
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assert tier_of(alert_type) == tier
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def test_unknown_alert_type_rejected(env):
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repo, _ = env
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with pytest.raises(ValueError):
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_upsert(repo, "C1", "unknown_type")
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def test_highest_tier_order():
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assert highest_tier("normal", "watch") == "watch"
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assert highest_tier("watch", "high") == "high"
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assert highest_tier("high", "normal") == "high"
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assert highest_tier("normal", "normal") == "normal"
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def test_merge_new_customer():
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merged = merge_l3(None, mapped_tier="watch", monitor_tags=["t1"], last_alert_id="ALT-1")
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assert merged["monitor_tier"] == "watch"
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assert merged["risk_score"] is None # 一期不写（P3-4 口径）
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assert merged["monitor_tags"] == ["t1"]
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assert merged["last_alert_id"] == "ALT-1"
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assert merged["computed_at"] is not None
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def test_merge_risk_score_stays_null_even_if_existing_has_value():
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"""历史行若已有 score（异常数据），合并时也不维护/不传播。"""
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existing = {"monitor_tier": "watch", "risk_score": 90, "monitor_tags": [],
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"score_dimensions": {}}
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merged = merge_l3(existing, mapped_tier="watch", monitor_tags=[], last_alert_id="ALT-2")
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assert merged["risk_score"] is None
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# ---------- upsert：首写与合并 ----------
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def test_first_event_inserts(env):
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repo, engine = env
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merged = _upsert(repo, "C1", "large_amount", alert_id="ALT-1")
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assert merged["monitor_tier"] == "watch" and merged["customer_id"] == "C1"
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row = _row(engine, "C1")
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assert row["monitor_tier"] == "watch" and row["risk_score"] is None
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assert row["last_alert_id"] == "ALT-1" and row["computed_at"] is not None
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assert get_profile_l3("C1", risk_repo=repo)["monitor_tier"] == "watch"
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def test_normal_upgrades_to_watch(env):
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repo, _ = env
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_upsert(repo, "C1", "suitability", alert_id="ALT-0")
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merged = _upsert(repo, "C1", "pattern", alert_id="ALT-1")
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assert merged["monitor_tier"] == "watch" # normal → watch 升档
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def test_watch_does_not_degrade_to_normal(env):
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"""suitability 映射 normal：已 watch 的客户不被 suitability 事件拉低。"""
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repo, engine = env
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_upsert(repo, "C1", "pattern", alert_id="ALT-1")
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merged = _upsert(repo, "C1", "suitability", alert_id="ALT-2")
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assert merged["monitor_tier"] == "watch"
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assert _row(engine, "C1")["monitor_tier"] == "watch"
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def test_aml_marks_high_with_pending_review_tag(env):
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repo, engine = env
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merged = _upsert(repo, "C1", "aml", alert_id="ALT-1")
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assert merged["monitor_tier"] == "high"
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assert AML_PENDING_TAG in merged["monitor_tags"]
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assert AML_PENDING_TAG in _row(engine, "C1")["monitor_tags"]
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def test_high_does_not_degrade_to_normal(env):
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"""B3 验收（评审 P2-4）：aml 后 suitability（映射 normal）不回落。"""
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repo, engine = env
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_upsert(repo, "C1", "aml", alert_id="ALT-1")
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merged = _upsert(repo, "C1", "suitability", alert_id="ALT-2")
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assert merged["monitor_tier"] == "high"
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assert _row(engine, "C1")["monitor_tier"] == "high"
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def test_large_amount_after_aml_does_not_fall_back(env):
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"""B3 验收：AML 后大额 → tier 仍 high、tags 并集、risk_score 保持 NULL。"""
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repo, engine = env
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_upsert(repo, "C1", "aml", alert_id="ALT-1")
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merged = _upsert(repo, "C1", "large_amount", alert_id="ALT-2", tags=["manual_review"])
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assert merged["monitor_tier"] == "high"
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assert merged["risk_score"] is None
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assert set(merged["monitor_tags"]) == {AML_PENDING_TAG, "manual_review"}
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assert merged["last_alert_id"] == "ALT-2" # 联动最新
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row = _row(engine, "C1")
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assert row["monitor_tier"] == "high" and row["risk_score"] is None
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def test_tags_accumulate_not_overwrite(env):
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repo, _ = env
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_upsert(repo, "C1", "pattern", alert_id="ALT-1", tags=["freq"])
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merged = _upsert(repo, "C1", "pattern", alert_id="ALT-2", tags=["manual_review"])
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assert merged["monitor_tags"] == ["freq", "manual_review"] # 不同 tag 跨事件追加
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def test_last_alert_id_kept_when_not_passed(env):
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"""评审 P2-2：漏传 last_alert_id 不抹掉旧值（FR-7 联动语义防御）。"""
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repo, engine = env
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_upsert(repo, "C1", "aml", alert_id="ALT-1")
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merged = upsert_profile_l3("C1", "large_amount", risk_repo=repo)
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assert merged["last_alert_id"] == "ALT-1"
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assert _row(engine, "C1")["last_alert_id"] == "ALT-1"
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def test_computed_at_refreshed_on_each_write(env):
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"""评审 P3-2：每次写 computed_at 均刷新（FR-7）。"""
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repo, engine = env
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_upsert(repo, "C1", "pattern", alert_id="ALT-1")
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upsert_profile_l3("C1", "large_amount", last_alert_id="ALT-2",
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computed_at=datetime(2027, 1, 1, 8, 0, 0), risk_repo=repo)
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# sqlite 读回为字符串，格式无关断言（核心是值已从首写的 now 刷新为传入时间）
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assert str(_row(engine, "C1")["computed_at"]).startswith("2027-01-01 08:00")
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def test_score_dimensions_replaced_only_when_passed(env):
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repo, _ = env
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_upsert(repo, "C1", "aml", alert_id="ALT-1", dims={"amount": 1})
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merged = _upsert(repo, "C1", "large_amount", alert_id="ALT-2")
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assert merged["score_dimensions"] == {"amount": 1} # 未传保留旧值
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merged = _upsert(repo, "C1", "large_amount", alert_id="ALT-3", dims={"amount": 2})
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assert merged["score_dimensions"] == {"amount": 2} # 传入则替换
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# ---------- 并发与竞态 ----------
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def test_concurrent_first_upsert_single_row(env):
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"""并发冒烟：两线程同客户首单（aml + 大额）→ 1 行、high、tags 并集。"""
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import json
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from threading import Thread
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repo, engine = env
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errors = []
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def worker(alert_type, alert_id):
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try:
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_upsert(repo, "C1", alert_type, alert_id=alert_id)
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except Exception as exc: # pragma: no cover
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errors.append(exc)
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threads = [
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Thread(target=worker, args=("aml", "ALT-A")),
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Thread(target=worker, args=("large_amount", "ALT-B")),
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]
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for t in threads:
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t.start()
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for t in threads:
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t.join()
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assert not errors, errors
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with engine.connect() as conn:
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count, payload = conn.execute(
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text(
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"SELECT COUNT(*), GROUP_CONCAT(monitor_tags) FROM customer_profile_l3"
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" WHERE customer_id = 'C1'"
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)
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).fetchone()
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assert count == 1
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tags = json.loads(payload)
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assert AML_PENDING_TAG in tags
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def test_integrity_error_falls_back_to_remerge(env, monkeypatch):
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"""跨进程竞态（评审 P2-7③）：首读 None、insert 撞主键 → 重读合并转更新，不丢对方写入。"""
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repo, engine = env
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# 对方进程已写入 high（模拟 AML 先落库）
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repo.insert_l3("C1", "high", None, {}, [AML_PENDING_TAG], "ALT-AML", datetime.now())
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calls = {"n": 0}
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orig_get = type(repo).get_l3
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def racing_get(self, cid):
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calls["n"] += 1
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if calls["n"] == 1:
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return None # 本进程读写在对方 insert 之前发生
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return orig_get(self, cid)
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monkeypatch.setattr(type(repo), "get_l3", racing_get)
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try:
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merged = _upsert(repo, "C1", "large_amount", alert_id="ALT-2")
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finally:
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monkeypatch.undo()
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assert merged["monitor_tier"] == "high" # 重读后合并，不降级
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assert merged["last_alert_id"] == "ALT-2"
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row = _row(engine, "C1")
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assert row["monitor_tier"] == "high" and row["last_alert_id"] == "ALT-2"
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def test_update_lost_race_retries_and_converges(env, monkeypatch):
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"""评审 P1-1：update 路径丢更新——本进程读旧值后对方先写 high，乐观锁未命中
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触发重读重试，最终收敛 high（修复前会被覆盖回退 watch）。"""
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repo, engine = env
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repo.insert_l3("C1", "watch", None, {}, [], "ALT-1", datetime.now())
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calls = {"n": 0}
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orig_update = type(repo).update_l3
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def racing_update(self, *args, **kwargs):
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calls["n"] += 1
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if calls["n"] == 1:
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orig_update(self, "C1", "high", None, {}, [AML_PENDING_TAG], "ALT-AML", datetime.now())
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return False # 对方抢先提交，本进程乐观锁未命中
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return orig_update(self, *args, **kwargs)
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monkeypatch.setattr(type(repo), "update_l3", racing_update)
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merged = _upsert(repo, "C1", "large_amount", alert_id="ALT-2")
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assert calls["n"] >= 2 # 确实走了重试
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assert merged["monitor_tier"] == "high"
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assert AML_PENDING_TAG in merged["monitor_tags"]
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row = _row(engine, "C1")
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assert row["monitor_tier"] == "high"
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assert row["last_alert_id"] == "ALT-2"
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def test_persistent_conflict_raises_not_silent(env, monkeypatch):
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"""重试耗尽抛错（宁失败不静默覆盖），不留半写状态。"""
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repo, engine = env
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repo.insert_l3("C1", "watch", None, {}, [], "ALT-1", datetime.now())
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monkeypatch.setattr(type(repo), "update_l3", lambda self, *a, **k: False)
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with pytest.raises(RuntimeError, match="conflicted"):
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_upsert(repo, "C1", "large_amount", alert_id="ALT-2")
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row = _row(engine, "C1")
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assert row["monitor_tier"] == "watch" # 未被静默改写
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