529 lines
19 KiB
Python
529 lines
19 KiB
Python
"""
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检测报告查看功能测试用例
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覆盖场景：
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1. 查询检测结果列表（按任务、实体、风险等级过滤）
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2. 获取检测结果详情
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3. 获取检测结果汇总报告
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4. 风险分布统计
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5. 报告导出功能（模拟）
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"""
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import pytest
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from datetime import datetime, date, timedelta
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from unittest.mock import AsyncMock, MagicMock, patch
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, and_, func
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from app.models.risk_detection import (
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DetectionResult,
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DetectionTask,
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RiskLevel,
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)
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from app.api.v1.endpoints.risk_detection import router as risk_detection_router
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from fastapi.testclient import TestClient
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from app.main import app
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class TestDetectionReport:
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"""检测报告测试类"""
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@pytest.fixture
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def mock_db_session(self):
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"""创建Mock数据库会话"""
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session = AsyncMock(spec=AsyncSession)
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session.execute = AsyncMock()
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return session
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@pytest.fixture
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def mock_detection_results(self):
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"""Mock检测结果数据"""
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return [
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DetectionResult(
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id=1,
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task_id="task_test_001",
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rule_id="rule_revenue_001",
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entity_id="ZB_TEST_001",
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entity_type="streamer",
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risk_level=RiskLevel.HIGH,
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risk_score=85.0,
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risk_category="收入完整性",
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description="平台充值与申报收入存在重大不匹配",
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suggestion="请核实收入申报的准确性，补缴相应税款",
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risk_data={
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"recharge_amount": 100000.0,
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"declared_amount": 80000.0,
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"discrepancy": 20000.0,
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"discrepancy_rate": 0.2
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},
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evidence=[
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{
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"type": "bank_transaction",
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"description": "银行流水显示收入100,000元",
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"data": {"amount": 100000.0, "date": "2024-01-15"}
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},
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{
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"type": "tax_declaration",
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"description": "申报收入仅80,000元",
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"data": {"amount": 80000.0, "date": "2024-02-15"}
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}
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],
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status="active",
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is_false_positive=False,
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detected_at=datetime(2024, 2, 20, 10, 30, 0),
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),
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DetectionResult(
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id=2,
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task_id="task_test_001",
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rule_id="rule_private_001",
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entity_id="ZB_TEST_001",
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entity_type="streamer",
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risk_level=RiskLevel.MEDIUM,
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risk_score=65.0,
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risk_category="私户收款",
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description="发现使用私人账户进行资金转账",
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suggestion="建议规范资金管理，使用对公账户",
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risk_data={
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"private_account_amount": 50000.0,
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"total_transactions": 100000.0,
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"private_account_ratio": 0.5
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},
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evidence=[
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{
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"type": "bank_transaction",
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"description": "私人账户转账记录",
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"data": {"amount": 50000.0, "account": "6222021234567890123"}
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}
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],
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status="active",
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is_false_positive=False,
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detected_at=datetime(2024, 2, 20, 11, 0, 0),
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),
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DetectionResult(
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id=3,
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task_id="task_test_002",
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rule_id="rule_expense_001",
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entity_id="ZB_TEST_002",
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entity_type="streamer",
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risk_level=RiskLevel.LOW,
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risk_score=30.0,
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risk_category="费用异常",
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description="费用增长略高于平均水平",
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suggestion="关注费用增长趋势",
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risk_data={
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"current_expense": 50000.0,
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"average_expense": 45000.0,
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"growth_rate": 0.11
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},
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evidence=[],
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status="active",
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is_false_positive=False,
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detected_at=datetime(2024, 2, 21, 14, 20, 0),
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),
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]
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@pytest.mark.asyncio
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async def test_list_results_with_task_filter(self, mock_db_session, mock_detection_results):
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"""测试按任务ID查询检测结果"""
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from app.api.v1.endpoints.risk_detection import list_results
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# 设置mock返回值
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = [
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r for r in mock_detection_results if r.task_id == "task_test_001"
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]
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# 执行测试
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results = await list_results(
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task_id="task_test_001",
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db=mock_db_session
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)
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# 验证结果
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assert len(results) == 2
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assert all(r["task_id"] == "task_test_001" for r in results)
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@pytest.mark.asyncio
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async def test_list_results_with_entity_filter(self, mock_db_session, mock_detection_results):
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"""测试按实体ID查询检测结果"""
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from app.api.v1.endpoints.risk_detection import list_results
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# 设置mock返回值
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = [
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r for r in mock_detection_results if r.entity_id == "ZB_TEST_001"
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]
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# 执行测试
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results = await list_results(
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entity_id="ZB_TEST_001",
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db=mock_db_session
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)
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# 验证结果
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assert len(results) == 2
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assert all(r["entity_id"] == "ZB_TEST_001" for r in results)
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@pytest.mark.asyncio
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async def test_list_results_with_risk_level_filter(self, mock_db_session, mock_detection_results):
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"""测试按风险等级查询检测结果"""
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from app.api.v1.endpoints.risk_detection import list_results
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# 设置mock返回值
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = [
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r for r in mock_detection_results if r.risk_level == RiskLevel.HIGH
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]
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# 执行测试
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results = await list_results(
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risk_level="HIGH",
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db=mock_db_session
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)
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# 验证结果
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assert len(results) == 1
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assert results[0]["result"]["risk_level"] == "HIGH"
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assert results[0]["result"]["risk_score"] == 85.0
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@pytest.mark.asyncio
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async def test_list_results_with_multiple_filters(self, mock_db_session, mock_detection_results):
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"""测试多条件组合查询检测结果"""
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from app.api.v1.endpoints.risk_detection import list_results
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# 设置mock返回值
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = [
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r for r in mock_detection_results
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if r.task_id == "task_test_001" and r.entity_id == "ZB_TEST_001"
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]
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# 执行测试
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results = await list_results(
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task_id="task_test_001",
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entity_id="ZB_TEST_001",
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limit=100,
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db=mock_db_session
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)
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# 验证结果
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assert len(results) == 2
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assert all(r["task_id"] == "task_test_001" and r["entity_id"] == "ZB_TEST_001" for r in results)
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@pytest.mark.asyncio
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async def test_get_result_detail(self, mock_db_session, mock_detection_results):
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"""测试获取检测结果详情"""
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from app.api.v1.endpoints.risk_detection import get_result
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# 设置mock返回值
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mock_db_session.execute.return_value.scalar_one_or_none.return_value = mock_detection_results[0]
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# 执行测试
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result = await get_result(
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result_id=1,
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db=mock_db_session
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)
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# 验证结果
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assert result["id"] == 1
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assert result["task_id"] == "task_test_001"
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assert result["rule_id"] == "rule_revenue_001"
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assert result["result"]["entity_id"] == "ZB_TEST_001"
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assert result["result"]["risk_level"] == "HIGH"
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assert result["result"]["risk_score"] == 85.0
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assert result["result"]["description"] == "平台充值与申报收入存在重大不匹配"
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assert len(result["result"]["evidence"]) == 2
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@pytest.mark.asyncio
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async def test_get_result_not_found(self, mock_db_session):
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"""测试获取不存在的检测结果"""
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from app.api.v1.endpoints.risk_detection import get_result
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# 设置mock返回值为None
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mock_db_session.execute.return_value.scalar_one_or_none.return_value = None
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# 验证抛出异常
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from fastapi import HTTPException
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with pytest.raises(HTTPException) as exc_info:
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await get_result(result_id=9999, db=mock_db_session)
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assert exc_info.value.status_code == 404
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@pytest.mark.asyncio
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async def test_get_detection_summary(self, mock_db_session, mock_detection_results):
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"""测试获取检测结果汇总"""
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from app.api.v1.endpoints.risk_detection import get_detection_summary
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# 设置mock返回值
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = [
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r for r in mock_detection_results if r.entity_id == "ZB_TEST_001"
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]
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# 执行测试
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summary = await get_detection_summary(
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entity_id="ZB_TEST_001",
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entity_type="streamer",
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period="2024-01",
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db=mock_db_session
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)
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# 验证结果
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assert summary["entity_id"] == "ZB_TEST_001"
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assert summary["entity_type"] == "streamer"
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assert summary["period"] == "2024-01"
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assert summary["total_detections"] == 2
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assert "HIGH" in summary["risk_distribution"]
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assert summary["risk_distribution"]["HIGH"] == 1
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assert "MEDIUM" in summary["risk_distribution"]
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assert summary["risk_distribution"]["MEDIUM"] == 1
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assert summary["avg_risk_score"] == 75.0 # (85.0 + 65.0) / 2
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assert summary["high_risk_count"] == 1
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assert len(summary["recommendations"]) > 0
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@pytest.mark.asyncio
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async def test_get_detection_summary_no_results(self, mock_db_session):
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"""测试获取空检测结果的汇总"""
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from app.api.v1.endpoints.risk_detection import get_detection_summary
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# 设置mock返回值为空列表
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = []
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# 执行测试
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summary = await get_detection_summary(
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entity_id="ZB_TEST_999",
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entity_type="streamer",
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period="2024-01",
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db=mock_db_session
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)
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# 验证结果
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assert summary["entity_id"] == "ZB_TEST_999"
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assert summary["total_detections"] == 0
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assert summary["risk_distribution"] == {}
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assert summary["avg_risk_score"] == 0.0
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assert summary["high_risk_count"] == 0
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assert len(summary["recommendations"]) > 0
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assert "未发现明显风险" in summary["recommendations"][0]
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@pytest.mark.asyncio
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async def test_get_detection_summary_critical_risk(self, mock_db_session):
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"""测试获取包含极高风险的汇总"""
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from app.api.v1.endpoints.risk_detection import get_detection_summary
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# 创建包含极高风险的结果
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critical_results = [
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DetectionResult(
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id=1,
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task_id="task_test_001",
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rule_id="rule_revenue_001",
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entity_id="ZB_TEST_001",
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entity_type="streamer",
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risk_level=RiskLevel.CRITICAL,
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risk_score=95.0,
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risk_category="收入完整性",
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description="重大收入隐瞒",
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suggestion="立即处理",
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risk_data={},
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evidence=[],
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status="active",
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is_false_positive=False,
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detected_at=datetime.now(),
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)
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]
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# 设置mock返回值
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = critical_results
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# 执行测试
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summary = await get_detection_summary(
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entity_id="ZB_TEST_001",
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entity_type="streamer",
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period="2024-01",
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db=mock_db_session
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)
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# 验证结果
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assert summary["risk_distribution"]["CRITICAL"] == 1
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assert "极高风险项目" in summary["recommendations"][0]
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assert summary["high_risk_count"] == 1
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@pytest.mark.asyncio
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async def test_risk_distribution_statistics(self, mock_db_session, mock_detection_results):
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"""测试风险分布统计"""
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from app.api.v1.endpoints.risk_detection import get_detection_summary
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# 设置mock返回值
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = mock_detection_results
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# 执行测试
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summary = await get_detection_summary(
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entity_id="ZB_TEST_ALL",
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entity_type="streamer",
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period="2024-01",
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db=mock_db_session
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)
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# 验证风险分布统计
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assert summary["total_detections"] == 3
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# 统计各风险等级数量
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risk_dist = summary["risk_distribution"]
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assert risk_dist.get("HIGH", 0) == 1
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assert risk_dist.get("MEDIUM", 0) == 1
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assert risk_dist.get("LOW", 0) == 1
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# 验证平均风险评分
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expected_avg = (85.0 + 65.0 + 30.0) / 3
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assert summary["avg_risk_score"] == expected_avg
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# 验证高风险计数（CRITICAL + HIGH）
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assert summary["high_risk_count"] == 1
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@pytest.mark.asyncio
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async def test_list_results_with_limit(self, mock_db_session, mock_detection_results):
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"""测试查询结果数量限制"""
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from app.api.v1.endpoints.risk_detection import list_results
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# 设置mock返回值（返回所有结果）
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mock_db_session.execute.return_value.scalars.return_value.all.return_value = mock_detection_results
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# 执行测试 - 限制数量为2
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results = await list_results(
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limit=2,
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db=mock_db_session
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)
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# 验证limit参数被正确传递（在实际实现中应该限制返回数量）
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# 注意：这里我们假设实现已经处理了limit参数
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mock_db_session.execute.assert_called()
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@pytest.mark.asyncio
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async def test_result_evidence_structure(self, mock_db_session, mock_detection_results):
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"""测试结果中证据链结构"""
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from app.api.v1.endpoints.risk_detection import get_result
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# 设置mock返回值
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mock_db_session.execute.return_value.scalar_one_or_none.return_value = mock_detection_results[0]
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# 执行测试
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result = await get_result(
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result_id=1,
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db=mock_db_session
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)
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# 验证证据链结构
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evidence = result["result"]["evidence"]
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assert len(evidence) == 2
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# 验证每个证据项的结构
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for ev in evidence:
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assert "type" in ev
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assert "description" in ev
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assert "data" in ev
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assert ev["type"] in ["bank_transaction", "tax_declaration"]
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@pytest.mark.asyncio
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async def test_result_risk_data_structure(self, mock_db_session, mock_detection_results):
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"""测试结果中风险数据结构"""
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from app.api.v1.endpoints.risk_detection import get_result
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# 设置mock返回值
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mock_db_session.execute.return_value.scalar_one_or_none.return_value = mock_detection_results[0]
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# 执行测试
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result = await get_result(
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result_id=1,
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db=mock_db_session
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)
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# 验证风险数据结构
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risk_data = result["result"]["risk_data"]
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assert "recharge_amount" in risk_data
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assert "declared_amount" in risk_data
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assert "discrepancy" in risk_data
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assert "discrepancy_rate" in risk_data
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# 验证数据类型
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assert isinstance(risk_data["recharge_amount"], (int, float))
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assert isinstance(risk_data["discrepancy_rate"], (int, float))
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@pytest.mark.asyncio
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async def test_false_positive_filtering(self, mock_db_session, mock_detection_results):
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"""测试误报过滤（如果实现）"""
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from app.api.v1.endpoints.risk_detection import list_results
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# 创建包含误报的结果
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results_with_fp = mock_detection_results + [
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DetectionResult(
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id=4,
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task_id="task_test_003",
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rule_id="rule_test_001",
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entity_id="ZB_TEST_003",
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entity_type="streamer",
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risk_level=RiskLevel.LOW,
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risk_score=20.0,
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risk_category="测试",
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description="误报结果",
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suggestion="忽略",
|
||
risk_data={},
|
||
evidence=[],
|
||
status="active",
|
||
is_false_positive=True,
|
||
detected_at=datetime.now(),
|
||
)
|
||
]
|
||
|
||
# 设置mock返回值
|
||
mock_db_session.execute.return_value.scalars.return_value.all.return_value = results_with_fp
|
||
|
||
# 执行测试
|
||
results = await list_results(
|
||
db=mock_db_session
|
||
)
|
||
|
||
# 验证结果（如果实现过滤误报功能）
|
||
# 注意：当前实现可能没有过滤误报，这里只是示例
|
||
assert len(results) >= 3
|
||
|
||
|
||
class TestReportAPIRoutes:
|
||
"""报告API路由测试类"""
|
||
|
||
@pytest.fixture
|
||
def client(self):
|
||
"""创建测试客户端"""
|
||
return TestClient(app)
|
||
|
||
def test_get_algorithms(self, client):
|
||
"""测试获取算法列表API"""
|
||
response = client.get("/api/v1/risk-detection/algorithms")
|
||
|
||
assert response.status_code == 200
|
||
data = response.json()
|
||
assert len(data) >= 5 # 至少有5个算法
|
||
|
||
# 验证算法结构
|
||
for algo in data:
|
||
assert "code" in algo
|
||
assert "name" in algo
|
||
assert "description" in algo
|
||
assert "parameters" in algo
|
||
|
||
# 验证特定算法
|
||
revenue_algo = next((a for a in data if a["code"] == "REVENUE_INTEGRITY_CHECK"), None)
|
||
assert revenue_algo is not None
|
||
assert revenue_algo["name"] == "收入完整性检测"
|
||
|
||
def test_get_rules(self, client):
|
||
"""测试获取规则列表API"""
|
||
response = client.get("/api/v1/risk-detection/rules")
|
||
|
||
assert response.status_code == 200
|
||
data = response.json()
|
||
assert isinstance(data, list)
|
||
|
||
# 验证规则结构
|
||
for rule in data:
|
||
assert "rule_id" in rule
|
||
assert "rule_name" in rule
|
||
assert "algorithm_code" in rule
|
||
assert "is_enabled" in rule
|
||
|
||
|
||
if __name__ == "__main__":
|
||
pytest.main([__file__, "-v"])
|