fix: 战略地图P0修复 — KPI code统一+放开同层连线+数据迁移
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Hermes CI Fix
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"""KPI因果链建模 — 任务2
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KPI间因果关系网络 + 模拟推演
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"""
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from fastapi import APIRouter, Depends, HTTPException, Query
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from sqlalchemy.orm import Session
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from sqlalchemy import text
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from typing import Optional
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import logging
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from app.database import get_db
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from app.auth_middleware import require_auth, require_role
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from app.models import KPIDefinition, KPICausality, KPIValue, OperationLog
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logger = logging.getLogger("kpi-causality")
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router = APIRouter(prefix="/api/cma/kpi-causality", tags=["KPI因果链"],
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dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
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)
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WRITE_ROLES = Depends(require_role("ceo", "finance", "it"))
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def _to_dict(obj):
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return {c.name: getattr(obj, c.name) for c in obj.__table__.columns}
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# ============================================================
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# 注意: 静态路径必须放在动态路径之前（/{id}之前）
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# ============================================================
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@router.get("/full-network")
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def get_full_network(db: Session = Depends(get_db)):
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"""获取全局因果网络数据（用于力导向图）"""
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edges = db.query(KPICausality).all()
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node_ids = set()
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edge_list = []
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for e in edges:
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node_ids.add(e.source_kpi_id)
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node_ids.add(e.target_kpi_id)
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edge_list.append({
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"source": e.source_kpi_id,
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"target": e.target_kpi_id,
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"strength": e.strength,
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"direction": e.direction,
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"lag_months": e.lag_months,
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})
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# 获取所有节点信息
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kpis = db.query(KPIDefinition).filter(KPIDefinition.id.in_(node_ids)).all() if node_ids else []
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node_map = {k.id: {
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"id": k.id, "kpi_code": k.kpi_code, "kpi_name": k.kpi_name,
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"dimension": k.dimension, "category": k.category,
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} for k in kpis}
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nodes = []
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for nid in node_ids:
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info = node_map.get(nid, {"id": nid, "kpi_code": f"KPI#{nid}", "kpi_name": f"KPI#{nid}"})
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nodes.append(info)
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return {"nodes": nodes, "edges": edge_list, "total_edges": len(edge_list)}
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@router.get("/kpi/{kpi_id}/network")
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def get_kpi_network(kpi_id: int, db: Session = Depends(get_db)):
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"""获取KPI的因果网络（上游驱动 + 下游影响）"""
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kpi = db.query(KPIDefinition).filter(KPIDefinition.id == kpi_id).first()
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if not kpi:
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raise HTTPException(404, "KPI不存在")
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# 上游（指向当前KPI的因果）
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upstream = db.query(KPICausality).filter(KPICausality.target_kpi_id == kpi_id).all()
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upstream_list = []
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for c in upstream:
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src = db.query(KPIDefinition).filter(KPIDefinition.id == c.source_kpi_id).first()
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if src:
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upstream_list.append({
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"causality_id": c.id,
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"kpi_id": src.id, "kpi_code": src.kpi_code, "kpi_name": src.kpi_name,
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"strength": c.strength, "lag_months": c.lag_months,
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"direction": c.direction, "formula": c.formula,
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})
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# 下游（当前KPI指向的因果）
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downstream = db.query(KPICausality).filter(KPICausality.source_kpi_id == kpi_id).all()
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downstream_list = []
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for c in downstream:
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tgt = db.query(KPIDefinition).filter(KPIDefinition.id == c.target_kpi_id).first()
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if tgt:
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downstream_list.append({
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"causality_id": c.id,
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"kpi_id": tgt.id, "kpi_code": tgt.kpi_code, "kpi_name": tgt.kpi_name,
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"strength": c.strength, "lag_months": c.lag_months,
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"direction": c.direction, "formula": c.formula,
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})
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return {
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"kpi": {"id": kpi.id, "kpi_code": kpi.kpi_code, "kpi_name": kpi.kpi_name, "dimension": kpi.dimension},
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"upstream": upstream_list,
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"downstream": downstream_list,
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}
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@router.post("/simulate")
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def simulate_causality(data: dict, db: Session = Depends(get_db)):
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"""模拟推演: 修改一个KPI的值，预测对其他KPI的影响
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Body: { kpi_id: int, new_value: float, period: str }
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"""
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kpi_id = data.get("kpi_id")
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new_value = data.get("new_value")
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period = data.get("period")
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if not kpi_id or new_value is None:
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raise HTTPException(400, "必须指定kpi_id和new_value")
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source_kpi = db.query(KPIDefinition).filter(KPIDefinition.id == kpi_id).first()
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if not source_kpi:
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raise HTTPException(404, "KPI不存在")
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# 获取当前值
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current_value = None
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query_values = db.query(KPIValue).filter(
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KPIValue.kpi_id == kpi_id,
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KPIValue.actual_value.isnot(None),
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)
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if period:
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query_values = query_values.filter(KPIValue.period == period)
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latest = query_values.order_by(KPIValue.period.desc()).first()
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if latest:
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current_value = latest.actual_value
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previous_value = current_value or new_value
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change_pct = ((new_value - previous_value) / previous_value * 100) if previous_value and previous_value != 0 else 0
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# BFS遍历下游因果链
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visited = set()
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impacts = []
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queue = [(kpi_id, change_pct, 0, 1.0)] # (kpi_id, change_pct, depth, cumulative_strength)
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while queue:
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current_kpi_id, current_change, depth, cum_strength = queue.pop(0)
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if current_kpi_id in visited:
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continue
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visited.add(current_kpi_id)
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# 查找从current_kpi_id出发的下游因果链
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downstream = db.query(KPICausality).filter(
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KPICausality.source_kpi_id == current_kpi_id
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).all()
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for edge in downstream:
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target_id = edge.target_kpi_id
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if target_id in visited:
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continue
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target_kpi = db.query(KPIDefinition).filter(KPIDefinition.id == target_id).first()
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if not target_kpi:
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continue
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# 计算影响: 变化率 × 强度 × 方向
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edge_strength = edge.strength or 0.5
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direction_factor = 1.0 if edge.direction == "positive" else -1.0
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propagated_change = current_change * edge_strength * direction_factor
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# 获取当前值
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tgt_val = db.query(KPIValue).filter(
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KPIValue.kpi_id == target_id,
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KPIValue.actual_value.isnot(None),
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).order_by(KPIValue.period.desc()).first()
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predicted_value = None
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if tgt_val and tgt_val.actual_value:
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predicted_value = round(tgt_val.actual_value * (1 + propagated_change / 100), 2)
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impacts.append({
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"kpi_id": target_id,
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"kpi_code": target_kpi.kpi_code,
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"kpi_name": target_kpi.kpi_name,
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"dimension": target_kpi.dimension,
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"current_value": tgt_val.actual_value if tgt_val else None,
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"predicted_value": predicted_value,
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"change_pct": round(propagated_change, 2),
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"strength": edge_strength,
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"direction": edge.direction,
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"lag_months": edge.lag_months,
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"depth": depth + 1,
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"path_strength": round(cum_strength * edge_strength, 3),
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})
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# 继续遍历下游
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new_cum = cum_strength * edge_strength
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if new_cum > 0.05 and depth < 5:
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queue.append((target_id, propagated_change, depth + 1, new_cum))
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return {
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"source": {
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"kpi_id": source_kpi.id,
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"kpi_code": source_kpi.kpi_code,
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"kpi_name": source_kpi.kpi_name,
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"current_value": current_value,
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"new_value": new_value,
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"change_pct": round(change_pct, 2),
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},
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"impacts": impacts,
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"total_impacted": len(impacts),
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}
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# ============================================================
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# CRUD (动态路径)
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# ============================================================
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@router.get("")
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def list_causalities(
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source_kpi_id: Optional[int] = None,
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target_kpi_id: Optional[int] = None,
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db: Session = Depends(get_db),
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):
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"""获取因果链列表"""
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query = db.query(KPICausality)
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if source_kpi_id:
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query = query.filter(KPICausality.source_kpi_id == source_kpi_id)
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if target_kpi_id:
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query = query.filter(KPICausality.target_kpi_id == target_kpi_id)
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items = query.order_by(KPICausality.id).all()
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result = []
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for c in items:
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d = _to_dict(c)
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src = db.query(KPIDefinition).filter(KPIDefinition.id == c.source_kpi_id).first()
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tgt = db.query(KPIDefinition).filter(KPIDefinition.id == c.target_kpi_id).first()
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d["source_kpi_code"] = src.kpi_code if src else None
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d["source_kpi_name"] = src.kpi_name if src else None
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d["target_kpi_code"] = tgt.kpi_code if tgt else None
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d["target_kpi_name"] = tgt.kpi_name if tgt else None
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result.append(d)
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return {"data": result, "total": len(result)}
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@router.get("/{causality_id}")
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def get_causality(causality_id: int, db: Session = Depends(get_db)):
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c = db.query(KPICausality).filter(KPICausality.id == causality_id).first()
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if not c:
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raise HTTPException(404, "因果链不存在")
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d = _to_dict(c)
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src = db.query(KPIDefinition).filter(KPIDefinition.id == c.source_kpi_id).first()
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tgt = db.query(KPIDefinition).filter(KPIDefinition.id == c.target_kpi_id).first()
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d["source"] = {"id": src.id, "kpi_code": src.kpi_code, "kpi_name": src.kpi_name} if src else None
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d["target"] = {"id": tgt.id, "kpi_code": tgt.kpi_code, "kpi_name": tgt.kpi_name} if tgt else None
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return d
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@router.post("")
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def create_causality(data: dict, db: Session = Depends(get_db), user=WRITE_ROLES):
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"""创建因果链"""
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source_id = data.get("source_kpi_id")
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target_id = data.get("target_kpi_id")
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if not source_id or not target_id:
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raise HTTPException(400, "必须指定源KPI和目标KPI")
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if source_id == target_id:
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raise HTTPException(400, "源和目标不能相同")
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src = db.query(KPIDefinition).filter(KPIDefinition.id == source_id).first()
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tgt = db.query(KPIDefinition).filter(KPIDefinition.id == target_id).first()
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if not src or not tgt:
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raise HTTPException(404, "KPI不存在")
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existing = db.query(KPICausality).filter(
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KPICausality.source_kpi_id == source_id,
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KPICausality.target_kpi_id == target_id,
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).first()
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if existing:
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raise HTTPException(400, f"因果链已存在: {src.kpi_code}→{tgt.kpi_code}")
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c = KPICausality(
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source_kpi_id=source_id,
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target_kpi_id=target_id,
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strength=data.get("strength", 0.5),
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lag_months=data.get("lag_months", 1),
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formula=data.get("formula"),
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direction=data.get("direction", "positive"),
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)
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db.add(c)
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db.commit()
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db.refresh(c)
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db.add(OperationLog(action="create", target_type="kpi_causality",
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detail=f"创建因果链: {src.kpi_code}→{tgt.kpi_code}"))
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db.commit()
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return _to_dict(c)
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@router.put("/{causality_id}")
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def update_causality(causality_id: int, data: dict, db: Session = Depends(get_db), user=WRITE_ROLES):
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c = db.query(KPICausality).filter(KPICausality.id == causality_id).first()
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if not c:
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raise HTTPException(404, "因果链不存在")
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for field in ("strength", "lag_months", "formula", "direction"):
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if field in data:
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setattr(c, field, data[field])
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db.commit()
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db.refresh(c)
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return _to_dict(c)
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@router.delete("/{causality_id}")
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def delete_causality(causality_id: int, db: Session = Depends(get_db), user=WRITE_ROLES):
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c = db.query(KPICausality).filter(KPICausality.id == causality_id).first()
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if c:
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db.delete(c)
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db.commit()
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return {"message": "已删除"}
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