feat: 数据分类分级 — 重要数据标记+资产清单+CSV导出(8/20评估办法政策驱动)

- subjects/kpi_definitions 新增 important_flag/data_level/data_category 列
- 新增 /api/cma/data-classification/* API: inventory/stats/标记/批量/export/industry-reference
- 数据级别: core核心/important重要/general一般(GB/T 43697 简化)
- 前端 DataClassification.vue: 统计概览+清单+打标+导出+行业参考目录
- pytest 17例覆盖(含多租户隔离验证)
This commit is contained in:
Hermes CI Fix
2026-08-26 07:51:39 +08:00
parent 6af4366a84
commit a64f184525
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"""数据分类分级 — 重要数据标记(2026-08-26 政策驱动)
背景:《网络数据安全风险评估办法》(2026-08-20 三部门施行)
- 重要数据处理者每年一次强制评估
- 评估前提 = 先分类分级("不知道重要数据在哪,评估无从谈起"
- 本模块 = "分类分级工具"第一版(标记+清单),不做评估算法
数据级别(参考 GB/T 43697 简化):
- core 核心数据(一旦遭篡改/破坏/泄露,直接危害国家安全/经济运行)
- important 重要数据(一旦遭篡改/破坏/泄露,危害公共利益/企业关键业务)
- general 一般数据(其余)
覆盖对象:
- subjects 会计科目(全局,无 entity_id,与现有科目管理一致)
- kpi_definitions KPI字典(按 entity_id 多租户隔离)
"""
from fastapi import APIRouter, Depends, HTTPException, Query
from sqlalchemy.orm import Session
from sqlalchemy import func, or_
from typing import Optional, List
from datetime import datetime
import csv
import io
from app.database import get_db
from app.deps import get_entity_id
from app.auth_middleware import require_role, require_auth
from app.models import Subject, KPIDefinition, Entity
router = APIRouter(prefix="/api/cma/data-classification", tags=["数据分类分级"],
dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
)
# 写操作只允许 ceo/finance/it(与 KPI 字典一致)
WRITE_ROLES = Depends(require_role("ceo", "finance", "it"))
VALID_LEVELS = {"core", "important", "general"}
LEVEL_LABELS = {
"core": "核心数据",
"important": "重要数据",
"general": "一般数据",
}
# 行业参考目录(内置提示,可按行业自定义扩展)
INDUSTRY_REFERENCE = [
{"industry": "通用/企业服务", "category": "客户数据", "suggest_level": "important",
"desc": "客户名单、合同、订单、应收账款等客户经营数据"},
{"industry": "通用/企业服务", "category": "财务数据", "suggest_level": "important",
"desc": "财务报表、银行账户、税务申报、薪酬数据"},
{"industry": "通用/企业服务", "category": "员工数据", "suggest_level": "important",
"desc": "员工身份、薪酬、社保、考勤、健康信息"},
{"industry": "金融", "category": "账户交易", "suggest_level": "core",
"desc": "客户账户、交易流水、信贷记录(金融行业核心数据)"},
{"industry": "医疗", "category": "健康医疗", "suggest_level": "core",
"desc": "病历、健康档案、基因数据(医疗行业核心数据)"},
{"industry": "工业", "category": "关键基础设施", "suggest_level": "important",
"desc": "生产控制、工艺参数、供应链关键环节数据"},
{"industry": "互联网", "category": "用户个人信息", "suggest_level": "important",
"desc": "个人信息、日志、位置数据(万人以上规模需重点评估)"},
{"industry": "能源", "category": "能源数据", "suggest_level": "important",
"desc": "能源生产、传输、消费监测数据"},
]
def _subject_to_item(s: Subject) -> dict:
return {
"type": "subject",
"id": s.id,
"code": s.subject_code,
"name": s.subject_name,
"dimension": None,
"category": s.new_standard_category or s.category or "",
"important_flag": 1 if s.important_flag else 0,
"data_level": s.data_level or "general",
"data_category": s.data_category or "",
"data_owner": None,
"storage": "会计科目台账",
}
def _kpi_to_item(k: KPIDefinition) -> dict:
return {
"type": "kpi",
"id": k.id,
"code": k.kpi_code,
"name": k.kpi_name,
"dimension": k.dimension,
"category": k.category or "",
"important_flag": 1 if k.important_flag else 0,
"data_level": k.data_level or "general",
"data_category": k.data_category or "",
"data_owner": k.data_owner,
"storage": f"KPI台账(entity_id={k.entity_id})",
}
def _query_items(
data_type: Optional[str],
data_level: Optional[str],
important: Optional[int],
keyword: Optional[str],
entity_id: int,
db: Session,
) -> list:
"""内部清单查询(供 inventory/export 复用,避免依赖注入问题)"""
items: list[dict] = []
if not data_type or data_type == "subject":
q = db.query(Subject).filter(Subject.is_active == 1)
if data_level:
q = q.filter(Subject.data_level == data_level)
if important == 1:
q = q.filter(Subject.important_flag == 1)
if keyword:
like = f"%{keyword}%"
q = q.filter(
Subject.subject_name.like(like) | Subject.subject_code.like(like)
)
for s in q.order_by(Subject.subject_code).all():
items.append(_subject_to_item(s))
if not data_type or data_type == "kpi":
q = db.query(KPIDefinition).filter(
KPIDefinition.status == "active",
KPIDefinition.entity_id == entity_id,
)
if data_level:
q = q.filter(KPIDefinition.data_level == data_level)
if important == 1:
q = q.filter(KPIDefinition.important_flag == 1)
if keyword:
like = f"%{keyword}%"
q = q.filter(
KPIDefinition.kpi_name.like(like) | KPIDefinition.kpi_code.like(like)
)
for k in q.order_by(KPIDefinition.kpi_code).all():
items.append(_kpi_to_item(k))
return items
def _stats_of(items: list) -> dict:
return {
"total": len(items),
"marked": sum(1 for i in items if i["important_flag"] == 1),
"by_level": {
"core": sum(1 for i in items if i["data_level"] == "core"),
"important": sum(1 for i in items if i["data_level"] == "important"),
"general": sum(1 for i in items if i["data_level"] == "general"),
},
"by_type": {
"subject": sum(1 for i in items if i["type"] == "subject"),
"kpi": sum(1 for i in items if i["type"] == "kpi"),
},
}
@router.get("/inventory")
def get_inventory(
data_type: Optional[str] = Query(None, description="subject/kpi,缺省返回全部"),
data_level: Optional[str] = Query(None, description="core/important/general 过滤"),
important: Optional[int] = Query(None, description="1=仅已标记重要数据"),
keyword: Optional[str] = Query(None, description="编码/名称搜索"),
entity_id: int = Depends(get_entity_id),
db: Session = Depends(get_db),
current_user = Depends(require_auth),
):
"""数据资产清单(科目 + KPI 合并输出,含重要级别)"""
if data_level and data_level not in VALID_LEVELS:
raise HTTPException(400, f"无效的数据级别: {data_level},可选 {sorted(VALID_LEVELS)}")
items = _query_items(data_type, data_level, important, keyword, entity_id, db)
return {"total": len(items), "items": items, "stats": _stats_of(items)}
@router.get("/stats")
def get_stats(
entity_id: int = Depends(get_entity_id),
db: Session = Depends(get_db),
current_user = Depends(require_auth),
):
"""数据分类分级统计概览(评估前准备看板)"""
subject_total = db.query(Subject).filter(Subject.is_active == 1).count()
subject_marked = db.query(Subject).filter(
Subject.is_active == 1, Subject.important_flag == 1
).count()
kpi_total = db.query(KPIDefinition).filter(
KPIDefinition.status == "active", KPIDefinition.entity_id == entity_id
).count()
kpi_marked = db.query(KPIDefinition).filter(
KPIDefinition.status == "active",
KPIDefinition.entity_id == entity_id,
KPIDefinition.important_flag == 1,
).count()
ent = db.query(Entity).filter(Entity.id == entity_id).first()
return {
"entity_id": entity_id,
"entity_name": ent.name if ent else "",
"subjects": {"total": subject_total, "marked": subject_marked},
"kpis": {"total": kpi_total, "marked": kpi_marked},
"total": subject_total + kpi_total,
"marked_total": subject_marked + kpi_marked,
"coverage_pct": round((subject_marked + kpi_marked) / (subject_total + kpi_total) * 100, 1)
if (subject_total + kpi_total) else 0,
"policy_note": "《网络数据安全风险评估办法》(2026-08-20施行):重要数据处理者每年一次强制评估,评估前提=先完成数据分类分级",
}
@router.put("/subjects/{subject_id}")
def mark_subject(
subject_id: int,
important_flag: Optional[int] = Query(None, description="1=重要数据, 0=取消"),
data_level: Optional[str] = Query(None, description="core/important/general"),
data_category: Optional[str] = Query(None, description="行业参考分类(自定义)"),
db: Session = Depends(get_db),
current_user = Depends(require_auth),
):
"""标记单个科目:重要数据标记 + 数据分级 + 行业分类"""
subject = db.query(Subject).filter(Subject.id == subject_id).first()
if not subject:
raise HTTPException(404, "科目不存在")
if data_level is not None and data_level not in VALID_LEVELS:
raise HTTPException(400, f"无效的数据级别: {data_level},可选 {sorted(VALID_LEVELS)}")
if important_flag is not None:
subject.important_flag = 1 if important_flag else 0
if data_level is not None:
subject.data_level = data_level
if data_level in ("core", "important"):
subject.important_flag = 1 # 核心/重要级别自动视为重要数据
if data_category is not None:
subject.data_category = data_category or None
db.commit()
return {
"message": "更新成功",
"subject_id": subject_id,
"important_flag": subject.important_flag,
"data_level": subject.data_level,
"data_category": subject.data_category,
}
@router.put("/kpis/{kpi_id}")
def mark_kpi(
kpi_id: int,
important_flag: Optional[int] = Query(None, description="1=重要数据, 0=取消"),
data_level: Optional[str] = Query(None, description="core/important/general"),
data_category: Optional[str] = Query(None, description="行业参考分类(自定义)"),
entity_id: int = Depends(get_entity_id),
db: Session = Depends(get_db),
current_user = Depends(require_auth),
):
"""标记单个KPI:重要数据标记 + 数据分级 + 行业分类(按账套隔离)"""
kpi = db.query(KPIDefinition).filter(
KPIDefinition.id == kpi_id,
KPIDefinition.entity_id == entity_id,
).first()
if not kpi:
raise HTTPException(404, "KPI不存在或不属于当前账套")
if data_level is not None and data_level not in VALID_LEVELS:
raise HTTPException(400, f"无效的数据级别: {data_level},可选 {sorted(VALID_LEVELS)}")
if important_flag is not None:
kpi.important_flag = 1 if important_flag else 0
if data_level is not None:
kpi.data_level = data_level
if data_level in ("core", "important"):
kpi.important_flag = 1 # 核心/重要级别自动视为重要数据
if data_category is not None:
kpi.data_category = data_category or None
db.commit()
return {
"message": "更新成功",
"kpi_id": kpi_id,
"important_flag": kpi.important_flag,
"data_level": kpi.data_level,
"data_category": kpi.data_category,
}
@router.put("/batch")
def batch_mark(
data_type: str = Query(..., description="subject/kpi"),
ids: List[int] = Query(..., description="ID列表"),
important_flag: Optional[int] = Query(None, description="1=重要数据, 0=取消"),
data_level: Optional[str] = Query(None, description="core/important/general"),
data_category: Optional[str] = Query(None, description="行业参考分类(自定义)"),
entity_id: int = Depends(get_entity_id),
db: Session = Depends(get_db),
current_user = Depends(require_auth),
):
"""批量标记(科目全局 / KPI按账套隔离)"""
if data_type not in ("subject", "kpi"):
raise HTTPException(400, f"无效的数据类型: {data_type},可选 subject/kpi")
if data_level is not None and data_level not in VALID_LEVELS:
raise HTTPException(400, f"无效的数据级别: {data_level},可选 {sorted(VALID_LEVELS)}")
if not ids:
raise HTTPException(400, "ids 不能为空")
updated = 0
if data_type == "subject":
q = db.query(Subject).filter(Subject.id.in_(ids), Subject.is_active == 1)
targets = q.all()
for s in targets:
if important_flag is not None:
s.important_flag = 1 if important_flag else 0
if data_level is not None:
s.data_level = data_level
if data_level in ("core", "important"):
s.important_flag = 1
if data_category is not None:
s.data_category = data_category or None
updated += 1
else:
q = db.query(KPIDefinition).filter(
KPIDefinition.id.in_(ids),
KPIDefinition.entity_id == entity_id,
KPIDefinition.status == "active",
)
targets = q.all()
for k in targets:
if important_flag is not None:
k.important_flag = 1 if important_flag else 0
if data_level is not None:
k.data_level = data_level
if data_level in ("core", "important"):
k.important_flag = 1
if data_category is not None:
k.data_category = data_category or None
updated += 1
db.commit()
return {"message": f"批量更新成功", "data_type": data_type, "updated_count": updated}
@router.get("/export")
def export_csv(
data_type: Optional[str] = Query(None, description="subject/kpi,缺省全部"),
data_level: Optional[str] = Query(None, description="core/important/general 过滤"),
important: Optional[int] = Query(None, description="1=仅已标记重要数据"),
entity_id: int = Depends(get_entity_id),
db: Session = Depends(get_db),
current_user = Depends(require_auth),
):
"""导出数据分类分级清单(评估前准备材料)CSV"""
if data_level and data_level not in VALID_LEVELS:
raise HTTPException(400, f"无效的数据级别: {data_level}")
items = _query_items(data_type, data_level, important, None, entity_id, db)
buf = io.StringIO()
writer = csv.writer(buf)
writer.writerow(["类型", "编码", "名称", "维度", "分类", "重要标记", "数据级别", "行业参考分类", "数据责任人", "存储位置"])
for i in items:
writer.writerow([
"科目" if i["type"] == "subject" else "KPI",
i["code"],
i["name"],
i["dimension"] or "",
i["category"] or "",
"" if i["important_flag"] else "",
LEVEL_LABELS.get(i["data_level"], i["data_level"]),
i["data_category"] or "",
i["data_owner"] or "",
i["storage"] or "",
])
content = "\ufeff" + buf.getvalue() # BOM 兼容 Excel
filename = f"data-classification-inventory_{datetime.now().strftime('%Y%m%d')}.csv"
from starlette.responses import Response
return Response(
content=content,
media_type="text/csv; charset=utf-8",
headers={"Content-Disposition": f'attachment; filename="{filename}"'},
)
@router.get("/industry-reference")
def industry_reference():
"""行业参考目录(内置提示,按行业给出重点数据分类建议)"""
return {"items": INDUSTRY_REFERENCE}
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@@ -5,7 +5,7 @@ from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from dotenv import load_dotenv
from app.database import init_db
from app.api import auth, kpis, kpi_governance, templates, maps, dashboard, data, alerts, ai_analysis, alert_rules, users, thresholds, notifications, permissions, action_plans, alignment, org, objectives, versions, budget, cost, predict, reports, security, knowledge, bot_bridge, bot_bridge_v2, lead, tenant, customer_dashboard, deviation_push, budget_generate, knowledge_articles, kpi_causality, data_quality, bi_reports, entities, bsc_layers, okr, okr_templates, subjects, driver_budget, bot_kpis, ontology, bot_iron_law, analysis_results, expenses, cash, tax_compliance, verify, growth_quality, products
from app.api import auth, kpis, kpi_governance, templates, maps, dashboard, data, alerts, ai_analysis, alert_rules, users, thresholds, notifications, permissions, action_plans, alignment, org, objectives, versions, budget, cost, predict, reports, security, knowledge, bot_bridge, bot_bridge_v2, lead, tenant, customer_dashboard, deviation_push, budget_generate, knowledge_articles, kpi_causality, data_quality, bi_reports, entities, bsc_layers, okr, okr_templates, subjects, driver_budget, bot_kpis, ontology, bot_iron_law, analysis_results, expenses, cash, tax_compliance, verify, growth_quality, products, data_classification
from app.utils.cache import clear_all as clear_cache, delete as delete_cache
from scripts.erp_sync import run_sync as run_erp_sync
from app.auth_middleware import require_auth
@@ -80,6 +80,7 @@ app.include_router(bot_iron_law.router)
app.include_router(analysis_results.router)
app.include_router(expenses.router)
app.include_router(cash.router)
app.include_router(data_classification.router)
app.include_router(tax_compliance.router)
app.include_router(verify.router)
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@@ -86,6 +86,9 @@ class KPIDefinition(Base):
threshold_yellow = Column(String(100), nullable=True, comment="黄灯阈值")
threshold_red = Column(String(100), nullable=True, comment="红灯阈值")
category = Column(String(50), nullable=True, comment="BSC二级类别: revenue_growth/profitability/cost_control/asset_efficiency/cash_risk/customer_scale/customer_concentration/customer_satisfaction/supply_chain/delivery_quality/talent_pipeline/employee_engagement/innovation")
important_flag = Column(Integer, default=0, comment="是否重要数据(1=是, 数据分类分级 2026-08-26)")
data_level = Column(String(20), nullable=True, comment="数据分级: core核心/important重要/general一般")
data_category = Column(String(50), nullable=True, comment="行业参考分类(自定义,如金融/医疗/工业)")
responsible_dept = Column(String(200), nullable=True, comment="负责部门")
responsible_user = Column(String(100), nullable=True, comment="负责人")
kpi_level = Column(String(20), default="operational", comment="strategic/operational")
@@ -574,6 +577,9 @@ class Subject(Base):
level = Column(Integer, default=1, comment="科目级别 1-4")
category = Column(String(50), nullable=True, comment="科目类别")
new_standard_category = Column(String(20), nullable=True, comment="新30号准则分类: operating/investing/financing/tax/discontinued")
important_flag = Column(Integer, default=0, comment="是否重要数据(1=是, 数据分类分级 2026-08-26)")
data_level = Column(String(20), nullable=True, comment="数据分级: core核心/important重要/general一般")
data_category = Column(String(50), nullable=True, comment="行业参考分类(自定义,如金融/医疗/工业)")
is_active = Column(Integer, default=1, comment="是否启用")
remark = Column(String(500), nullable=True, comment="备注")
created_at = Column(DateTime, server_default=func.now())
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@@ -0,0 +1,247 @@
"""数据分类分级 API 测试 — 重要数据标记 + 资产清单 + 导出"""
import hashlib
import pytest
from fastapi.testclient import TestClient
from sqlalchemy.orm import Session
from app.models import Subject, KPIDefinition, Entity
from tests.conftest import create_test_user, get_token_for_user, auth_header
def create_test_subject(db: Session, **kwargs) -> Subject:
"""创建测试科目"""
defaults = {
"subject_code": "1001",
"subject_name": "库存现金",
"level": 1,
"is_active": 1,
}
defaults.update(kwargs)
s = Subject(**defaults)
db.add(s)
db.commit()
db.refresh(s)
return s
def create_test_kpi(db: Session, **kwargs) -> KPIDefinition:
"""创建测试KPI(带entity_id"""
defaults = {
"entity_id": 1,
"kpi_code": "F_TEST_REVENUE",
"kpi_name": "营业收入(万元)",
"dimension": "finance",
"status": "active",
}
defaults.update(kwargs)
k = KPIDefinition(**defaults)
db.add(k)
db.commit()
db.refresh(k)
return k
class TestInventory:
def test_inventory_empty(self, client: TestClient, db: Session):
create_test_user(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/inventory", headers=auth_header(token))
assert r.status_code == 200
data = r.json()
assert data["total"] == 0
assert data["stats"]["marked"] == 0
def test_inventory_contains_subject_and_kpi(self, client: TestClient, db: Session):
create_test_user(db)
create_test_subject(db)
create_test_kpi(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/inventory", headers=auth_header(token))
assert r.status_code == 200
data = r.json()
types = {i["type"] for i in data["items"]}
assert types == {"subject", "kpi"}
assert data["total"] == 2
# 未标记时级别默认 general
assert data["stats"]["by_level"]["general"] == 2
def test_filter_by_data_type(self, client: TestClient, db: Session):
create_test_user(db)
create_test_subject(db)
create_test_kpi(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/inventory",
params={"data_type": "kpi"}, headers=auth_header(token))
data = r.json()
assert data["total"] == 1
assert data["items"][0]["type"] == "kpi"
def test_filter_by_level(self, client: TestClient, db: Session):
create_test_user(db)
create_test_subject(db, data_level="important", important_flag=1)
create_test_kpi(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/inventory",
params={"data_level": "important"}, headers=auth_header(token))
data = r.json()
assert data["total"] == 1
assert data["items"][0]["name"] == "库存现金"
def test_filter_important_only(self, client: TestClient, db: Session):
create_test_user(db)
create_test_subject(db, data_level="important", important_flag=1)
create_test_kpi(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/inventory",
params={"important": 1}, headers=auth_header(token))
data = r.json()
assert data["total"] == 1
def test_invalid_level_400(self, client: TestClient, db: Session):
create_test_user(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/inventory",
params={"data_level": "secret"}, headers=auth_header(token))
assert r.status_code == 400
class TestMarkSubject:
def test_mark_subject(self, client: TestClient, db: Session):
create_test_user(db)
s = create_test_subject(db)
token = get_token_for_user(client)
r = client.put(f"/api/cma/data-classification/subjects/{s.id}",
params={"data_level": "important", "data_category": "财务数据"},
headers=auth_header(token))
assert r.status_code == 200
body = r.json()
# 重要级别自动视为重要数据
assert body["important_flag"] == 1
assert body["data_level"] == "important"
assert body["data_category"] == "财务数据"
def test_mark_subject_general_clears(self, client: TestClient, db: Session):
create_test_user(db)
s = create_test_subject(db, data_level="important", important_flag=1)
token = get_token_for_user(client)
r = client.put(f"/api/cma/data-classification/subjects/{s.id}",
params={"data_level": "general", "important_flag": 0},
headers=auth_header(token))
assert r.status_code == 200
assert r.json()["data_level"] == "general"
assert r.json()["important_flag"] == 0
def test_mark_subject_not_found(self, client: TestClient, db: Session):
create_test_user(db)
token = get_token_for_user(client)
r = client.put("/api/cma/data-classification/subjects/9999",
params={"data_level": "important"}, headers=auth_header(token))
assert r.status_code == 404
class TestMarkKpi:
def test_mark_kpi(self, client: TestClient, db: Session):
create_test_user(db)
k = create_test_kpi(db, entity_id=1)
token = get_token_for_user(client)
r = client.put(f"/api/cma/data-classification/kpis/{k.id}",
params={"data_level": "core", "data_category": "财务数据"},
headers=auth_header(token))
assert r.status_code == 200
assert r.json()["important_flag"] == 1
assert r.json()["data_level"] == "core"
def test_kpi_entity_isolation(self, client: TestClient, db: Session):
"""多租户隔离:entity 2 的KPIentity 1 的token不可见、不可标记"""
create_test_user(db)
k2 = create_test_kpi(db, entity_id=2, kpi_code="F_OTHER_ENTITY")
token = get_token_for_user(client) # token 绑定 entity 1
# 不可标记
r = client.put(f"/api/cma/data-classification/kpis/{k2.id}",
params={"data_level": "important"}, headers=auth_header(token))
assert r.status_code == 404
# 清单中不可见
r2 = client.get("/api/cma/data-classification/inventory",
params={"data_type": "kpi"}, headers=auth_header(token))
data = r2.json()
assert all(i["code"] != "F_OTHER_ENTITY" for i in data["items"])
class TestBatch:
def test_batch_mark_subjects(self, client: TestClient, db: Session):
create_test_user(db)
s1 = create_test_subject(db, subject_code="1001", subject_name="库存现金")
s2 = create_test_subject(db, subject_code="1002", subject_name="银行存款")
token = get_token_for_user(client)
r = client.put("/api/cma/data-classification/batch",
params={"data_type": "subject", "ids": [s1.id, s2.id],
"data_level": "important", "data_category": "财务数据"},
headers=auth_header(token))
assert r.status_code == 200
assert r.json()["updated_count"] == 2
# 回查确认生效
db.expire_all()
assert db.query(Subject).get(s1.id).important_flag == 1
assert db.query(Subject).get(s2.id).data_level == "important"
def test_batch_invalid_type(self, client: TestClient, db: Session):
create_test_user(db)
token = get_token_for_user(client)
r = client.put("/api/cma/data-classification/batch",
params={"data_type": "bad", "ids": [1]}, headers=auth_header(token))
assert r.status_code == 400
class TestExport:
def test_export_csv(self, client: TestClient, db: Session):
create_test_user(db)
create_test_subject(db, data_level="important", important_flag=1)
create_test_kpi(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/export", headers=auth_header(token))
assert r.status_code == 200
assert "text/csv" in r.headers["content-type"]
text = r.text
# 表头 + 类型 + 中文标签
assert "类型" in text and "数据级别" in text
assert "库存现金" in text
assert "科目" in text and "KPI" in text
assert "重要数据" in text
def test_export_filtered(self, client: TestClient, db: Session):
create_test_user(db)
create_test_subject(db, data_level="important", important_flag=1)
create_test_kpi(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/export",
params={"important": 1}, headers=auth_header(token))
text = r.text
assert "库存现金" in text
assert "营业收入(万元)" not in text
class TestStats:
def test_stats(self, client: TestClient, db: Session):
create_test_user(db)
create_test_subject(db, data_level="important", important_flag=1)
create_test_subject(db, subject_code="1002", subject_name="银行存款")
create_test_kpi(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/stats", headers=auth_header(token))
assert r.status_code == 200
data = r.json()
assert data["subjects"]["total"] == 2
assert data["subjects"]["marked"] == 1
assert data["kpis"]["total"] == 1
assert data["marked_total"] == 1
assert "policy_note" in data
def test_industry_reference(self, client: TestClient, db: Session):
create_test_user(db)
token = get_token_for_user(client)
r = client.get("/api/cma/data-classification/industry-reference", headers=auth_header(token))
assert r.status_code == 200
items = r.json()["items"]
assert len(items) >= 5
industries = {i["industry"] for i in items}
assert "金融" in industries and "医疗" in industries
+5 -4
View File
@@ -9,10 +9,10 @@ interface MenuItem {
// ── 角色路由映射 ──
export const ROLE_ROUTES: Record<string, string[]> = {
ceo: ['/my-dashboard', '/dashboard', '/kpis', '/maps', '/maps-review', '/maps/canvas', '/maps/review', '/alerts', '/notifications', '/org', '/users', '/permissions', '/budget', '/deviations', '/cost', '/cost-intelligence', '/predict', '/action-plans', '/knowledge', '/guide', '/customer', '/learning-dashboard', '/reports', '/alignment', '/dupont-analysis', '/analysis-confidence', '/expenses', '/cash-plan', '/receivables', '/growth-quality', '/product-matrix', '/tax-compliance'],
finance: ['/my-dashboard', '/dashboard', '/kpis', '/maps', '/maps-review', '/maps/canvas', '/maps/review', '/alerts', '/data', '/budget', '/deviations', '/cost', '/cost-intelligence', '/predict', '/action-plans', '/knowledge', '/guide', '/customer', '/learning-dashboard', '/reports', '/alignment', '/dupont-analysis', '/analysis-confidence', '/expenses', '/cash-plan', '/receivables', '/growth-quality', '/product-matrix', '/tax-compliance'],
business: ['/my-dashboard', '/dashboard', '/kpis', '/alerts', '/budget', '/deviations', '/action-plans', '/knowledge', '/guide', '/customer', '/expenses', '/cash-plan', '/growth-quality', '/product-matrix', '/tax-compliance'],
it: ['/my-dashboard', '/dashboard', '/kpis', '/alerts', '/data', '/org', '/users', '/permissions', '/budget', '/deviations', '/cost', '/cost-intelligence', '/predict', '/action-plans', '/knowledge', '/guide', '/customer', '/learning-dashboard', '/analysis-confidence', '/expenses', '/cash-plan', '/product-matrix', '/tax-compliance'],
ceo: ['/my-dashboard', '/dashboard', '/kpis', '/maps', '/maps-review', '/maps/canvas', '/maps/review', '/alerts', '/notifications', '/org', '/users', '/permissions', '/budget', '/deviations', '/cost', '/cost-intelligence', '/predict', '/action-plans', '/knowledge', '/guide', '/customer', '/learning-dashboard', '/reports', '/alignment', '/dupont-analysis', '/analysis-confidence', '/expenses', '/cash-plan', '/receivables', '/growth-quality', '/product-matrix', '/tax-compliance', '/data-classification'],
finance: ['/my-dashboard', '/dashboard', '/kpis', '/maps', '/maps-review', '/maps/canvas', '/maps/review', '/alerts', '/data', '/budget', '/deviations', '/cost', '/cost-intelligence', '/predict', '/action-plans', '/knowledge', '/guide', '/customer', '/learning-dashboard', '/reports', '/alignment', '/dupont-analysis', '/analysis-confidence', '/expenses', '/cash-plan', '/receivables', '/growth-quality', '/product-matrix', '/tax-compliance', '/data-classification'],
business: ['/my-dashboard', '/dashboard', '/kpis', '/alerts', '/budget', '/deviations', '/action-plans', '/knowledge', '/guide', '/customer', '/expenses', '/cash-plan', '/growth-quality', '/product-matrix', '/tax-compliance', '/data-classification'],
it: ['/my-dashboard', '/dashboard', '/kpis', '/alerts', '/data', '/org', '/users', '/permissions', '/budget', '/deviations', '/cost', '/cost-intelligence', '/predict', '/action-plans', '/knowledge', '/guide', '/customer', '/learning-dashboard', '/analysis-confidence', '/expenses', '/cash-plan', '/product-matrix', '/tax-compliance', '/data-classification'],
}
export const ROLE_ACTIONS: Record<string, string[]> = {
@@ -61,6 +61,7 @@ export const MENU_ITEMS: MenuItem[] = [
// ── GROUP 5: 基础数据与知识──
{ path: '/kpis', label: 'KPI字典', icon: 'Document', roles: ['ceo', 'finance', 'business', 'it'], group: '基础数据与知识' },
{ path: '/data', label: '数据管理', icon: 'Connection', roles: ['ceo', 'finance', 'it'], group: '基础数据与知识' },
{ path: '/data-classification', label: '数据分类分级', icon: 'WarningFilled', roles: ['ceo', 'finance', 'business', 'it'], group: '基础数据与知识' },
{ path: '/knowledge', label: 'CMA知识库', icon: 'Document', roles: ['ceo', 'finance', 'business', 'it'], group: '基础数据与知识' },
{ path: '/okr-templates', label: 'OKR模板库', icon: 'Collection', roles: ['ceo', 'finance', 'it'], group: '基础数据与知识' },
+1
View File
@@ -39,6 +39,7 @@ const routes = [
{ path: 'okr-templates', name: 'OKRTemplates', component: () => import('@/views/OKRTemplates.vue'), meta: { title: 'OKR模板库', roles: ['ceo', 'finance', 'it'], editable: true } },
{ path: 'okr/:id', name: 'OkrDetail', component: () => import('@/views/OkrDetail.vue'), meta: { title: 'OKR详情', roles: ['ceo', 'finance', 'it'] } },
{ path: 'subjects', name: 'SubjectManage', component: () => import('@/views/SubjectManage.vue'), meta: { title: '科目打标', roles: ['ceo', 'finance', 'business', 'it'] } },
{ path: 'data-classification', name: 'DataClassification', component: () => import('@/views/DataClassification.vue'), meta: { title: '数据分类分级', roles: ['ceo', 'finance', 'business', 'it'], editable: true } },
{ path: 'mpm-calculator', name: 'MpmCalculator', component: () => import('@/views/MpmCalculator.vue'), meta: { title: 'MPM计算器', roles: ['ceo', 'finance', 'business'] } },
{ path: 'bot-kpis', name: 'BotKpis', component: () => import('@/views/BotKpiDashboard.vue'), meta: { title: 'Bot KPI看板', roles: ['ceo', 'finance', 'it'] } },
{ path: 'analysis-confidence', name: 'AnalysisConfidence', component: () => import('@/views/AnalysisConfidence.vue'), meta: { title: '分析置信度', roles: ['ceo', 'finance', 'it'] } },
+377
View File
@@ -0,0 +1,377 @@
<template>
<div class="dc-page">
<!-- 政策提示 -->
<div class="policy-banner">
<span class="policy-icon">📜</span>
<span>
网络数据安全风险评估办法(2026-08-20 施行)重要数据处理者每年一次强制评估评估前提=先完成数据分类分级
本页为分类分级工具第一版标记 + 数据资产清单 + 导出评估前准备材料
</span>
</div>
<!-- 统计概览 -->
<div class="stats-row">
<div class="stat-card">
<div class="stat-num">{{ stats.subjects?.total ?? 0 }}</div>
<div class="stat-label">会计科目</div>
<div class="stat-sub">已标记 {{ stats.subjects?.marked ?? 0 }}</div>
</div>
<div class="stat-card">
<div class="stat-num">{{ stats.kpis?.total ?? 0 }}</div>
<div class="stat-label">KPI 指标</div>
<div class="stat-sub">已标记 {{ stats.kpis?.marked ?? 0 }}</div>
</div>
<div class="stat-card">
<div class="stat-num">{{ stats.marked_total ?? 0 }}</div>
<div class="stat-label">重要数据项</div>
<div class="stat-sub">覆盖率 {{ stats.coverage_pct ?? 0 }}%</div>
</div>
<div class="stat-card">
<div class="stat-num">{{ stats.entity_name || ('账套 #' + (stats.entity_id ?? '-')) }}</div>
<div class="stat-label">当前账套</div>
<div class="stat-sub">多租户隔离</div>
</div>
</div>
<!-- 操作条 -->
<div class="toolbar">
<el-radio-group v-model="dataType" size="small" @change="loadInventory">
<el-radio-button label="">全部</el-radio-button>
<el-radio-button label="subject">科目</el-radio-button>
<el-radio-button label="kpi">KPI</el-radio-button>
</el-radio-group>
<el-select v-model="filterLevel" placeholder="数据级别" clearable size="small" style="width:130px;" @change="loadInventory">
<el-option label="核心数据" value="core" />
<el-option label="重要数据" value="important" />
<el-option label="一般数据" value="general" />
</el-select>
<el-checkbox v-model="onlyImportant" size="small" @change="loadInventory">仅看重要数据</el-checkbox>
<el-input v-model="keyword" placeholder="搜索编码/名称" size="small" style="width:180px;" clearable @change="loadInventory" />
<span style="margin-left:auto;">
<el-button size="small" type="success" :disabled="selectedIds.length === 0 || !canWrite" @click="openBatchPanel">
批量打标 ({{ selectedIds.length }})
</el-button>
<el-button size="small" type="primary" :loading="exporting" @click="doExport">导出清单 CSV</el-button>
<el-button size="small" @click="loadInventory">刷新</el-button>
</span>
</div>
<!-- 批量打标面板 -->
<div v-if="batchVisible" class="batch-panel">
<span>已选 <b>{{ selectedIds.length }}</b> 批量设置</span>
<el-select v-model="batchLevel" placeholder="数据级别" size="small" style="width:130px;">
<el-option label="核心数据" value="core" />
<el-option label="重要数据" value="important" />
<el-option label="一般数据" value="general" />
</el-select>
<el-input v-model="batchCategory" placeholder="行业参考分类(可选,如 财务数据/客户数据)" size="small" style="width:220px;" />
<el-button type="primary" size="small" :loading="batchLoading" @click="doBatch">确认打标</el-button>
<el-button size="small" @click="batchVisible = false">取消</el-button>
</div>
<!-- 数据资产清单 -->
<el-table
:data="items"
border stripe size="small"
style="width:100%;margin-top:8px;"
@selection-change="onSelectionChange"
>
<el-table-column type="selection" width="36" />
<el-table-column label="类型" width="64">
<template #default="{ row }">
<el-tag :type="row.type === 'subject' ? '' : 'primary'" size="small">
{{ row.type === 'subject' ? '科目' : 'KPI' }}
</el-tag>
</template>
</el-table-column>
<el-table-column prop="code" label="编码" width="110" />
<el-table-column prop="name" label="名称" min-width="170" />
<el-table-column prop="dimension" label="维度" width="80">
<template #default="{ row }">
<span v-if="row.dimension">{{ dimLabel(row.dimension) }}</span>
<span v-else style="color:#ccc;"></span>
</template>
</el-table-column>
<el-table-column label="重要标记" width="84">
<template #default="{ row }">
<el-tag :type="row.important_flag ? 'danger' : 'info'" size="small">
{{ row.important_flag ? '重要' : '一般' }}
</el-tag>
</template>
</el-table-column>
<el-table-column label="数据级别" width="130">
<template #default="{ row }">
<el-select
v-model="row.data_level"
size="small"
style="width:112px;"
:disabled="!canWrite"
@change="val => onLevelChange(row, val)"
>
<el-option label="核心数据" value="core" />
<el-option label="重要数据" value="important" />
<el-option label="一般数据" value="general" />
</el-select>
</template>
</el-table-column>
<el-table-column label="行业参考分类" width="170">
<template #default="{ row }">
<el-select
v-model="row.data_category"
size="small"
style="width:150px;"
:disabled="!canWrite"
filterable
allow-create
default-first-option
clearable
placeholder="选择或输入"
@change="val => onCategoryChange(row, val)"
>
<el-option v-for="c in categoryOptions" :key="c" :label="c" :value="c" />
</el-select>
</template>
</el-table-column>
<el-table-column prop="data_owner" label="责任人" width="90">
<template #default="{ row }">
<span v-if="row.data_owner">{{ row.data_owner }}</span>
<span v-else style="color:#ccc;"></span>
</template>
</el-table-column>
<el-table-column prop="storage" label="存储位置" width="130">
<template #default="{ row }">
<span style="font-size:12px;">{{ row.storage }}</span>
</template>
</el-table-column>
</el-table>
<div class="table-footer"> {{ totalItems }} · 已标记 {{ markedCount }} </div>
<!-- 行业参考目录 -->
<el-collapse style="margin-top:12px;">
<el-collapse-item>
<template #title>
<span style="font-weight:600;">🏭 行业参考目录按行业提示重点数据可自定义</span>
</template>
<el-table :data="industryRef" border stripe size="small" style="width:100%;">
<el-table-column prop="industry" label="行业" width="130" />
<el-table-column prop="category" label="数据分类" width="140" />
<el-table-column label="建议级别" width="100">
<template #default="{ row }">
<el-tag :type="row.suggest_level === 'core' ? 'danger' : 'warning'" size="small">
{{ row.suggest_level === 'core' ? '核心' : '重要' }}
</el-tag>
</template>
</el-table-column>
<el-table-column prop="desc" label="说明" />
</el-table>
</el-collapse-item>
</el-collapse>
</div>
</template>
<script setup lang="ts">
import { ref, computed, onMounted } from 'vue'
import { ElMessage } from 'element-plus'
import axios from 'axios'
const api = axios.create({ baseURL: '/api/cma', timeout: 30000 })
api.interceptors.request.use((config: any) => {
const token = localStorage.getItem('cma_token')
if (token) config.headers.Authorization = `Bearer ${token}`
return config
})
const userRole = computed(() => (localStorage.getItem('cma_role') || 'finance'))
const canWrite = computed(() => ['ceo', 'finance', 'it'].includes(userRole.value))
const loading = ref(false)
const items = ref<any[]>([])
const totalItems = ref(0)
const markedCount = ref(0)
const stats = ref<any>({})
const industryRef = ref<any[]>([])
const dataType = ref('')
const filterLevel = ref('')
const onlyImportant = ref(false)
const keyword = ref('')
const selectedIds = ref<number[]>([])
const selectedType = ref('subject')
const exporting = ref(false)
const batchVisible = ref(false)
const batchLevel = ref('important')
const batchCategory = ref('')
const batchLoading = ref(false)
const categoryOptions = ['财务数据', '客户数据', '员工数据', '生产数据', '供应链数据', '税务数据', '薪酬数据', '个人信息']
const dimMap: Record<string, string> = {
finance: '财务', customer: '客户', process: '流程', learning: '学习成长',
}
function dimLabel(d: string) {
return dimMap[d] || d
}
async function loadStats() {
try {
const r = await api.get('/data-classification/stats')
stats.value = (r as any).data || {}
} catch (e) {
stats.value = {}
}
}
async function loadInventory() {
loading.value = true
try {
const params: any = {}
if (dataType.value) params.data_type = dataType.value
if (filterLevel.value) params.data_level = filterLevel.value
if (onlyImportant.value) params.important = 1
if (keyword.value) params.keyword = keyword.value
const r = await api.get('/data-classification/inventory', { params })
const d = (r as any).data || {}
items.value = d.items || []
totalItems.value = d.total || 0
markedCount.value = (d.stats || {}).marked || 0
} catch (e) {
ElMessage.error('加载数据资产清单失败')
items.value = []
} finally {
loading.value = false
}
}
async function loadIndustryRef() {
try {
const r = await api.get('/data-classification/industry-reference')
industryRef.value = (r as any).data?.items || []
} catch (e) {
industryRef.value = []
}
}
function onSelectionChange(rows: any[]) {
selectedIds.value = rows.map((r: any) => r.id)
selectedType.value = rows.length ? rows[0].type : 'subject'
}
async function onLevelChange(row: any, val: string) {
try {
const url = row.type === 'subject' ? `/data-classification/subjects/${row.id}` : `/data-classification/kpis/${row.id}`
await api.put(url, null, { params: { data_level: val } })
row.important_flag = (val === 'core' || val === 'important') ? 1 : row.important_flag
ElMessage.success(`${row.name} 分级更新成功`)
await loadStats()
} catch (e) {
ElMessage.error('更新失败')
await loadInventory()
}
}
async function onCategoryChange(row: any, val: string) {
try {
const url = row.type === 'subject' ? `/data-classification/subjects/${row.id}` : `/data-classification/kpis/${row.id}`
await api.put(url, null, { params: { data_category: val || '' } })
ElMessage.success(`${row.name} 分类更新成功`)
} catch (e) {
ElMessage.error('更新失败')
await loadInventory()
}
}
function openBatchPanel() {
batchLevel.value = 'important'
batchCategory.value = ''
batchVisible.value = true
}
async function doBatch() {
batchLoading.value = true
try {
await api.put('/data-classification/batch', null, {
params: {
data_type: selectedType.value,
ids: selectedIds.value,
data_level: batchLevel.value,
...(batchCategory.value ? { data_category: batchCategory.value } : {}),
}
})
ElMessage.success(`批量打标 ${selectedIds.value.length} 项成功`)
batchVisible.value = false
await loadInventory()
await loadStats()
} catch (e) {
ElMessage.error('批量打标失败')
} finally {
batchLoading.value = false
}
}
async function doExport() {
exporting.value = true
try {
const params: any = {}
if (dataType.value) params.data_type = dataType.value
if (filterLevel.value) params.data_level = filterLevel.value
if (onlyImportant.value) params.important = 1
const r: any = await api.get('/data-classification/export', { params, responseType: 'blob' })
const blob = r.data
const url = window.URL.createObjectURL(blob)
const a = document.createElement('a')
a.href = url
a.download = `数据分类分级清单_${new Date().toISOString().slice(0, 10)}.csv`
a.click()
window.URL.revokeObjectURL(url)
ElMessage.success('清单已导出')
} catch (e) {
ElMessage.error('导出失败')
} finally {
exporting.value = false
}
}
onMounted(() => {
loadStats()
loadInventory()
loadIndustryRef()
})
</script>
<style scoped>
.dc-page { max-width: 1280px; margin: 0 auto; padding: 16px; }
.policy-banner {
background: linear-gradient(90deg, #fef3e2, #fff8ef);
border: 1px solid #f5d9a8;
border-radius: 8px;
padding: 10px 14px;
font-size: 13px;
color: #7a5b1e;
margin-bottom: 14px;
display: flex;
gap: 8px;
align-items: flex-start;
}
.policy-icon { font-size: 16px; }
.stats-row { display: grid; grid-template-columns: repeat(4, 1fr); gap: 12px; margin-bottom: 14px; }
.stat-card {
background: #fff; border: 1px solid #e5e7ef; border-radius: 10px;
padding: 14px 16px; box-shadow: 0 1px 3px rgba(0,0,0,.04);
}
.stat-num { font-size: 24px; font-weight: 700; color: #1a1a2e; }
.stat-label { font-size: 13px; color: #666; margin-top: 2px; }
.stat-sub { font-size: 12px; color: #999; margin-top: 2px; }
.toolbar { display: flex; align-items: center; gap: 10px; flex-wrap: wrap; }
.batch-panel {
background: #f0f7ff; border: 1px solid #c8ddf5; border-radius: 8px;
padding: 10px 12px; margin-top: 10px; display: flex; align-items: center; gap: 10px; flex-wrap: wrap;
font-size: 13px;
}
.table-footer { font-size: 12px; color: #999; margin-top: 6px; }
</style>