165 lines
5.8 KiB
Python
165 lines
5.8 KiB
Python
"""L3 监测画像写入（B3 · PRD FR-7 / R-05 最小写入）。
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合并规则（防降级，PRD FR-7）：monitor_tier 取最高档（normal < watch < high），
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monitor_tags 追加合并不覆盖，risk_score 取 max，computed_at 每次写当前时间
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（列 NOT NULL 必须显式赋值），last_alert_id 联动最新预警。
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并发：进程内锁按 customer_id 串行（多进程部署换 Redis SET NX，接口不变）；
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锁超时降级与跨进程竞态由 IntegrityError 兜底——重读合并后再 update，不丢更新。
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"""
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from __future__ import annotations
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import logging
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from datetime import datetime
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from typing import Any
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from sqlalchemy.exc import IntegrityError
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from app.repository.risk_repository import RiskRepository
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from app.service.risk.alert_service import _run_locked # 同包复用聚合锁；B7 收敛至公共原语
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logger = logging.getLogger(__name__)
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TIER_ORDER = ("normal", "watch", "high")
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ALERT_TYPE_TIER = {
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"aml": "high",
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"pattern": "watch",
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"large_amount": "watch",
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"freq_trade": "watch",
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"suitability": "normal",
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}
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AML_PENDING_TAG = "aml_hit_pending_review"
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def tier_of(alert_type: str) -> str:
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"""alert_type → L3 档位映射（PRD FR-7 固定映射；未知类型拒绝写入）。"""
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tier = ALERT_TYPE_TIER.get(alert_type)
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if tier is None:
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raise ValueError(f"unknown alert_type for L3 mapping: {alert_type}")
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return tier
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def highest_tier(a: str, b: str) -> str:
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"""取最高档（防降级核心原语）。"""
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return a if TIER_ORDER.index(a) >= TIER_ORDER.index(b) else b
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def merge_l3(
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existing: dict[str, Any] | None,
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*,
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mapped_tier: str,
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risk_score: int | None,
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monitor_tags: list[str],
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last_alert_id: str | None,
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score_dimensions: dict[str, Any] | None = None,
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computed_at: datetime | None = None,
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) -> dict[str, Any]:
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"""纯函数：existing 行（repo.get_l3 输出）与新事件合并后的 L3 行。
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existing 为 None 表示新客户首写；risk_score 双方均空时保持 NULL。
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"""
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if existing is None:
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tier, old_score, old_tags, old_dims = "normal", None, [], {}
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else:
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tier = existing.get("monitor_tier") or "normal"
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old_score = existing.get("risk_score")
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old_tags = existing.get("monitor_tags") or []
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old_dims = existing.get("score_dimensions") or {}
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scores = [int(s) for s in (old_score, risk_score) if s is not None]
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return {
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"monitor_tier": highest_tier(tier, mapped_tier),
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"risk_score": max(scores) if scores else None,
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"monitor_tags": sorted(set(old_tags) | set(monitor_tags)),
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"score_dimensions": score_dimensions if score_dimensions is not None else old_dims,
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"last_alert_id": last_alert_id,
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"computed_at": computed_at or datetime.now(),
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}
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def upsert_profile_l3(
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customer_id: str,
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alert_type: str,
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risk_score: int | None = None,
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monitor_tags: list[str] | None = None,
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last_alert_id: str | None = None,
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score_dimensions: dict[str, Any] | None = None,
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risk_repo: RiskRepository | None = None,
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computed_at: datetime | None = None,
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) -> dict[str, Any]:
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"""预警事件 → L3 upsert（B2 预警落库后调用；aml 自动追加待复核标签）。
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返回合并后的 L3 行（含 customer_id）。
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"""
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repo = risk_repo or RiskRepository()
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mapped_tier = tier_of(alert_type)
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tags = list(monitor_tags or [])
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if alert_type == "aml" and AML_PENDING_TAG not in tags:
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tags.append(AML_PENDING_TAG)
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def _write(locked: bool) -> dict[str, Any]:
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existing = repo.get_l3(customer_id)
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merged = merge_l3(
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existing,
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mapped_tier=mapped_tier,
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risk_score=risk_score,
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monitor_tags=tags,
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last_alert_id=last_alert_id,
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score_dimensions=score_dimensions,
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computed_at=computed_at,
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)
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try:
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if existing is None:
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repo.insert_l3(
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customer_id,
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merged["monitor_tier"],
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merged["risk_score"],
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merged["score_dimensions"],
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merged["monitor_tags"],
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merged["last_alert_id"],
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merged["computed_at"],
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)
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else:
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repo.update_l3(
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customer_id,
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merged["monitor_tier"],
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merged["risk_score"],
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merged["score_dimensions"],
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merged["monitor_tags"],
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merged["last_alert_id"],
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merged["computed_at"],
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)
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except IntegrityError:
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# 首写竞态（锁超时降级/跨进程）：另一线程已 insert，重读合并转更新
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if existing is not None:
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raise
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raced = repo.get_l3(customer_id)
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merged = merge_l3(
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raced,
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mapped_tier=mapped_tier,
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risk_score=risk_score,
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monitor_tags=tags,
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last_alert_id=last_alert_id,
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score_dimensions=score_dimensions,
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computed_at=computed_at,
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)
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repo.update_l3(
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customer_id,
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merged["monitor_tier"],
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merged["risk_score"],
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merged["score_dimensions"],
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merged["monitor_tags"],
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merged["last_alert_id"],
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merged["computed_at"],
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)
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merged["customer_id"] = customer_id
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return merged
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return _run_locked(f"l3:{customer_id}", _write)
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def get_profile_l3(customer_id: str, risk_repo: RiskRepository | None = None) -> dict[str, Any] | None:
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"""L3 只读薄封装（对话线/引擎复用；Redis 缓存待 B7 lifespan 一并接入）。"""
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return (risk_repo or RiskRepository()).get_l3(customer_id)
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