Hermes CI Fix
9822fbd9ba
- alert_rules: 新增 rule_type=customer_concentration（单一/前N客户收入占比超阈值触发，黄=超阈值/红=阈值x倍数） 数据源 zxt_masterbill 客户(往来单位)收入聚合，unit_id<=0 占位剔除；无客户数据可回退 KPI 口径 复用现有 KPIAlert 生成链路：check-all 内联分支 + 专用端点 POST /run-customer-concentration - alert_generator(每日9:00): 新增规则引擎步骤，复用上述检查函数跑 forecast_deviation/customer_concentration - AlertList.vue: 规则类型筛选/编辑项 + 参数表单 + 客户集中度检查按钮 - 测试: tests/test_customer_concentration_rule.py 17 条（规则注册/聚合/双数据源/黄红灯/去重/check-all） - 验证脚本: scripts/verify_forecast_deviation_rules_e2e.py / verify_customer_concentration_rule_e2e.py
270 lines
10 KiB
Python
270 lines
10 KiB
Python
"""
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预警自动生成 — 管理会计OS
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比对 KPI 实际值与阈值配置（threshold_green/yellow/red），超出则写入 kpi_alerts
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在 daily_sync 之后运行
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"""
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import sys
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import os
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import re
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import json
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import logging
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from datetime import datetime, timedelta
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from app.database import get_session_local
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from app.models import KPIDefinition, KPIValue, KPIAlert, ActionPlan
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logger = logging.getLogger("cma.alert_gen")
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def _parse_threshold(expr: str) -> tuple:
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"""解析阈值表达式，返回 (operator, value)
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示例:
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>=32000000 -> ('>=', 32000000)
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<20 -> ('<', 20)
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<=55 -> ('<=', 55)
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>60 -> ('>', 60)
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"""
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m = re.match(r"(>=|<=|>|<|=|!=)\s*([\d.]+)", str(expr).strip())
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if m:
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return m.group(1), float(m.group(2))
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return None, None
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def cleanup_green_alerts(db_session) -> int:
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"""Bug1修复: 清理历史遗留的green级别pending预警（正常值不应出现在待办）"""
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greens = db_session.query(KPIAlert).filter(
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KPIAlert.alert_level == "green",
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KPIAlert.status.in_(["pending", "processing"]),
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).all()
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count = 0
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for g in greens:
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g.status = "resolved"
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g.resolution = "自动清理: green(正常)级别不生成待处理预警"
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g.resolved_at = datetime.now()
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count += 1
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if count:
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db_session.commit()
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logger.info(f" 清理历史green预警 {count} 条 → resolved")
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return count
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def _check_threshold(actual: float, threshold_expr: str, level: str) -> tuple:
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"""检查实际值是否触发阈值，返回 (触发, 消息)"""
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if not threshold_expr or actual is None:
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return False, ""
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op, val = _parse_threshold(threshold_expr)
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if op is None:
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return False, ""
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triggered = False
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if op == ">=" and actual >= val:
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triggered = True
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elif op == "<=" and actual <= val:
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triggered = True
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elif op == ">" and actual > val:
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triggered = True
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elif op == "<" and actual < val:
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triggered = True
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elif op == "=" and actual == val:
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triggered = True
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if triggered:
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level_names = {"green": "正常", "yellow": "预警", "red": "紧急"}
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msg = (f"KPI当前值 {actual:.2f}，触发{level_names.get(level, level)}阈值 "
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f"({threshold_expr})")
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return True, msg
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return False, ""
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def run_alert_check(db_session, period: str = None) -> int:
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"""检查所有KPI的实际值是否触发预警，返回新生成的预警数"""
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if period is None:
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period = datetime.now().strftime("%Y-%m")
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kpis = db_session.query(KPIDefinition).filter(
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KPIDefinition.status == "active"
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).all()
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new_count = 0
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for kpi in kpis:
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# 跳过无阈值的KPI
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thr = {
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"red": kpi.threshold_red,
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"yellow": kpi.threshold_yellow,
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"green": kpi.threshold_green,
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}
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if not any(thr.values()):
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continue
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# 获取该KPI当前期间的最新值
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latest = db_session.query(KPIValue).filter(
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KPIValue.kpi_id == kpi.id,
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KPIValue.period == period,
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).order_by(KPIValue.calculated_at.desc()).first()
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if not latest or latest.actual_value is None:
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continue
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actual = latest.actual_value
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# 从绿到红检查（绿灯最高优先级——满足即止）
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# Bug1修复: green(正常)不生成pending预警，只对yellow/red落库
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for level in ["green", "yellow", "red"]:
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expr = thr[level]
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if not expr:
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continue
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triggered, msg = _check_threshold(actual, expr, level)
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if triggered:
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if level == "green":
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# 正常状态：不生成待处理预警（如有旧的red/yellow预警自动解除）
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break
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# 检查是否已有该期间该KPI同级别的预警
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existing = db_session.query(KPIAlert).filter(
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KPIAlert.kpi_id == kpi.id,
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KPIAlert.kpi_value_id == latest.id,
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KPIAlert.alert_level == level,
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).first()
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if existing:
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# 已有预警，跳过
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break
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# 创建新预警
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alert = KPIAlert(
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kpi_id=kpi.id,
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kpi_value_id=latest.id,
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alert_level=level,
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alert_message=f"{kpi.kpi_name}[{period}] {msg}",
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status="pending",
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)
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db_session.add(alert)
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db_session.flush() # 获取alert.id
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new_count += 1
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logger.info(f" 新增预警 [{level}] {kpi.kpi_name}: {msg}")
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# Bug2修复: red/yellow预警自动创建行动计划（预警→行动闭环）
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if level in ("red", "yellow"):
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plan_title = f"改善: {kpi.kpi_name} {msg}"
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if kpi.kpi_name and "现金" in kpi.kpi_name or kpi.kpi_code == "F_OP_CFLOW":
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plan_title = f"资金缺口应对: {msg} —— 催收应收+安排融资"
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elif kpi.kpi_code == "F_AR_DAYS":
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plan_title = f"应收催收: {msg} —— 逾期客户专项跟进"
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elif kpi.kpi_code == "C_REBATE_RATE":
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plan_title = f"渠补谈判: {msg} —— 下游渠道返利谈判"
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elif kpi.kpi_code == "F_COST_RATIO":
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plan_title = f"费用压缩: {msg} —— 管理费削减计划"
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plan = ActionPlan(
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alert_id=alert.id,
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kpi_id=kpi.id,
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title=plan_title,
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assignee="财务部",
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priority="high" if level == "red" else "medium",
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due_date=datetime.now().date() + timedelta(days=3 if level == "red" else 7),
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created_by="alert_generator",
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)
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db_session.add(plan)
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db_session.flush()
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alert.action_plan_linked_id = plan.id
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logger.info(f" ↳ 自动创建行动计划 #{plan.id}: {plan_title}")
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break # 只取最高级别
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elif level == "red" and not triggered:
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# 红没触发，如果已有红色预警但当前不满足，自动降级或关闭
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existing_red = db_session.query(KPIAlert).filter(
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KPIAlert.kpi_id == kpi.id,
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KPIAlert.kpi_value_id == latest.id,
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KPIAlert.alert_level == "red",
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KPIAlert.status.in_(["pending", "processing"]),
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).first()
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if existing_red:
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existing_red.status = "resolved"
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existing_red.resolution = "自动解除: 当前值不再触发红色阈值"
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existing_red.resolved_at = datetime.now()
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logger.info(f" 自动解除预警 [red] {kpi.kpi_name}")
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db_session.commit()
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return new_count
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def run_rule_engine_checks(db_session) -> dict:
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"""预警规则引擎（rule_type 驱动）— 预测偏差 + 客户集中度（P2 2026-09-10）
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复用 alert_rules 的检查端点实现（FastAPI 路由函数=带 Depends 默认值的普通函数，
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显式传参即可复用，零逻辑复制），按存在规则的账套逐个执行。
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任何单点失败只记录日志，不影响静态阈值主流程。
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"""
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from app.api.alert_rules import (
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AlertRule, run_forecast_deviation_check, run_customer_concentration_check,
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)
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stats = {"forecast_deviation": 0, "customer_concentration": 0}
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try:
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rows = db_session.query(AlertRule.entity_id).filter(
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AlertRule.enabled == 1,
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AlertRule.rule_type.in_(("forecast_deviation", "customer_concentration")),
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).distinct().all()
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except Exception as e:
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logger.error(f"规则引擎检查跳过（规则查询失败）: {e}")
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return stats
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for (eid,) in rows:
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for key, fn in (("forecast_deviation", run_forecast_deviation_check),
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("customer_concentration", run_customer_concentration_check)):
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try:
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r = fn(db=db_session, entity_id=eid)
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n = int(r.get("generated", 0) or 0)
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stats[key] += n
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if n:
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logger.info(f" 规则预警 entity={eid} {key}: {n}条")
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except Exception as e:
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logger.error(f"规则检查失败 entity={eid} {key}: {e}")
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return stats
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def generate_and_push(db_session) -> dict:
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"""生成预警并推送，返回统计"""
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period = datetime.now().strftime("%Y-%m")
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# 0. Bug1修复: 先清理历史green预警
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cleaned = cleanup_green_alerts(db_session)
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# 1. 生成预警
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logger.info(f"开始预警检查 ({period})...")
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new_count = run_alert_check(db_session, period)
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logger.info(f"预警检查完成: 新增 {new_count} 条")
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# 1b. 规则引擎检查（预测偏差 / 客户集中度，P2 2026-09-10）
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rule_stats = run_rule_engine_checks(db_session)
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# 2. 推送
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pushed = 0
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if new_count > 0:
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try:
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from app.utils.notifier import push_pending_alerts
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pushed = push_pending_alerts(db_session)
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logger.info(f"推送完成: {pushed} 条")
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except Exception as e:
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logger.error(f"推送失败: {e}")
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return {"period": period, "new_alerts": new_count, "pushed": pushed,
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"cleaned_green": cleaned, "rule_engine": rule_stats}
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if __name__ == "__main__":
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
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)
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db = get_session_local()()
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try:
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result = generate_and_push(db)
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print(f"预警检查: {result['new_alerts']}条新预警 / {result['pushed']}条已推送"
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f" / 规则引擎{result['rule_engine']}")
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finally:
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db.close()
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