Files
cma-management/backend/app/api/kpi_governance.py
T
Hermes CI Fix f9e20bc9bc fix: KPI历史数据治理批量修复 — 元数据补全321条+编码规范处理222条
- 规则2: 补全321条元数据 (formula 207 / data_source 57 / data_owner 57)
  - EXT_科目KPI: formula按财务维度默认'财务指标计算'
  - F_/C_/P_/L_经典KPI: 精确公式(6条) + 数据源按维度(财务系统/业务系统)
  - data_owner优先取负责部门, 否则默认财务部
- 规则3: 审计规则白名单化EXT_前缀(科目余额表导入, 仅限finance维度),
  EXT_编码与dimension保持一致不改动; FB_/BH_ 21条真实前缀冲突
  输出人工确认清单 docs/kpi_governance_human_review.md
- 验证: GET /api/cma/kpi/governance/audit → rule_counts {1:0, 2:0, 3:21, 4:0}
  未改动任何kpi_code及引用表, 评分/地图/KPI列表接口正常
2026-08-10 23:50:14 +08:00

201 lines
7.8 KiB
Python

"""KPI数据治理4条规则:入库必检 + 元数据必填 + 编码规范 + 战略分级
规则1: 入库必检 — dimension/target_value/unit 必填(创建/更新强制拦截)
规则2: 元数据必填 — formula/data_source/data_owner 不能为空或占位符(待补充/待指定/-)
规则3: 编码规范 — kpi_code 必须以 F_/C_/P_/L_ 前缀开头且与 dimension 一致;禁止跨层同名
规则4: 战略/运营分级 — kpi_level 必须是 strategic/operational
API:
- POST /api/cma/kpi/validate 校验单个KPI数据 → {valid, errors}
- GET /api/cma/kpi/governance/audit 全量校验 → 按4条规则分组的不合规清单
"""
from typing import List, Optional
from fastapi import APIRouter, Depends
from sqlalchemy.orm import Session
from app.database import get_db
from app.auth_middleware import require_auth, require_role
from app.models import KPIDefinition
router = APIRouter(
prefix="/api/cma/kpi",
tags=["KPI数据治理"],
dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
)
# 维度 → 编码前缀
DIM_PREFIX = {"finance": "F", "customer": "C", "process": "P", "learning": "L"}
# 历史遗留兼容前缀: EXT_ = 科目余额表导入的财务科目KPI(仅限 finance 维度)
LEGACY_PREFIX_DIM = {"EXT": "finance"}
VALID_LEVELS = ("strategic", "operational")
# 视为"未完善"的占位符值
PLACEHOLDERS = ("待补充", "待指定", "待完善", "待定", "暂无", "TBD", "tbd", "-", "--", "N/A", "n/a")
# 规则2必填元数据字段
META_FIELDS = [
("formula", "计算公式"),
("data_source", "数据来源"),
("data_owner", "数据责任人"),
]
def _clean_str(val) -> str:
if val is None:
return ""
if isinstance(val, str):
return val.strip()
return str(val).strip()
def _is_placeholder(val) -> bool:
"""空值或占位符(待补充/待指定/- 等)视为未完善"""
s = _clean_str(val)
if not s:
return True
return s in PLACEHOLDERS
def validate_kpi_payload(
data: dict,
db: Session = None,
current_kpi_id: Optional[int] = None,
is_update: bool = False,
) -> List[dict]:
"""校验单个KPI数据(4条规则)。
- data: 提交的KPI字段字典(创建或更新的载荷)
- db: SQLAlchemy Session(用于跨层同名/编码唯一性检查,可为None)
- current_kpi_id: 更新时传KPI自身id(避免自检误报)
- is_update: 更新模式 — 仅校验载荷中显式出现的字段
返回 [{rule: int, field: str, message: str}, ...],空列表=合规。
"""
issues: List[dict] = []
def add(rule: int, field: str, message: str):
issues.append({"rule": rule, "field": field, "message": message})
code = _clean_str(data.get("kpi_code"))
dimension = _clean_str(data.get("dimension"))
has_code = bool(code)
# ── 规则1: 入库必检 dimension/target_value/unit ──
if not is_update or "dimension" in data:
if not dimension:
add(1, "dimension", "缺少dimension(所属维度: finance/customer/process/learning)")
if not is_update or "target_value" in data:
tv = data.get("target_value")
if tv is None or (isinstance(tv, str) and _clean_str(tv) == ""):
add(1, "target_value", "缺少target_value(目标值)")
if not is_update or "unit" in data:
if _is_placeholder(data.get("unit")):
add(1, "unit", "缺少unit(单位)")
# ── 规则2: 元数据必填(不能为空或占位符)──
for field, label in META_FIELDS:
if not is_update or field in data:
if _is_placeholder(data.get(field)):
add(2, field, f"元数据未完善: {label}({field})不能为空或占位符(待补充/待指定/-)")
# ── 规则3: 编码规范 ──
if not is_update or "kpi_code" in data:
if not has_code:
add(3, "kpi_code", "缺少kpi_code(KPI编码)")
else:
prefix = code.split("_")[0] if "_" in code else code
if prefix not in ("F", "C", "P", "L"):
# 兼容历史遗留 EXT_ 前缀(科目余额表导入的财务科目KPI,仅限finance维度)
if not (LEGACY_PREFIX_DIM.get(prefix) and dimension == LEGACY_PREFIX_DIM[prefix]):
add(3, "kpi_code", f"编码前缀不符: {code} 应以F_/C_/P_/L_开头")
elif dimension and DIM_PREFIX.get(dimension) and prefix != DIM_PREFIX[dimension]:
expected = DIM_PREFIX[dimension]
add(3, "kpi_code",
f"编码前缀与维度不符: {code} 前缀{prefix}_ 与维度{dimension}(应为{expected}_)不一致")
# 禁止跨层同名: 同一kpi_code不能用于不同dimension
if has_code and db is not None:
dup = db.query(KPIDefinition).filter(KPIDefinition.kpi_code == code).first()
if dup and dup.id != current_kpi_id:
if dimension and dup.dimension and dup.dimension != dimension:
add(3, "kpi_code",
f"跨层同名: {code} 已用于维度{dup.dimension},不能用于维度{dimension}")
elif not dimension:
add(3, "kpi_code", f"编码已存在: {code} 已注册(维度{dup.dimension}),不能重复使用")
# ── 规则4: 战略/运营分级 ──
if not is_update or "kpi_level" in data:
lv = data.get("kpi_level")
if lv is not None and lv not in VALID_LEVELS:
add(4, "kpi_level", f"kpi_level必须是strategic或operational,当前值: {lv}")
return issues
def kpi_issues_message(issues: List[dict]) -> List[str]:
"""issue dict列表 → 纯文本错误列表"""
return [i["message"] for i in issues]
@router.post("/validate")
def validate_kpi(
kpi_data: dict,
db: Session = Depends(get_db),
current_user=Depends(require_auth),
):
"""校验单个KPI数据(不入库)。
请求体: KPI字段字典,可选 kpi_id 标识正在编辑的KPI(避免跨层同名误报)。
返回: {"valid": bool, "errors": [str], "details": [{rule, field, message}]}
"""
kpi_id = kpi_data.get("kpi_id") if isinstance(kpi_data.get("kpi_id"), int) else None
issues = validate_kpi_payload(kpi_data, db=db, current_kpi_id=kpi_id)
return {
"valid": len(issues) == 0,
"errors": kpi_issues_message(issues),
"details": issues,
}
@router.get("/governance/audit")
def governance_audit(
db: Session = Depends(get_db),
current_user=Depends(require_auth),
):
"""全量校验所有活跃KPI,输出按4条规则分组的不合规清单。"""
kpis = db.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
non_compliant = []
by_rule: dict = {1: [], 2: [], 3: [], 4: []}
for k in kpis:
payload = {c.name: getattr(k, c.name) for c in k.__table__.columns}
issues = validate_kpi_payload(payload, db=db, current_kpi_id=k.id)
if issues:
entry = {
"kpi_id": k.id,
"kpi_code": k.kpi_code,
"kpi_name": k.kpi_name,
"dimension": k.dimension,
"kpi_level": k.kpi_level,
"issues": issues,
}
non_compliant.append(entry)
for i in issues:
by_rule.setdefault(i["rule"], []).append({
"kpi_id": k.id,
"kpi_code": k.kpi_code,
"kpi_name": k.kpi_name,
"field": i["field"],
"message": i["message"],
})
rule_counts = {str(r): len(items) for r, items in by_rule.items()}
return {
"total": len(kpis),
"compliant": len(kpis) - len(non_compliant),
"non_compliant_count": len(non_compliant),
"rule_counts": rule_counts,
"by_rule": {str(r): items for r, items in by_rule.items()},
"non_compliant": non_compliant,
}