381 lines
12 KiB
Markdown
381 lines
12 KiB
Markdown
# 收入完整性检测算法测试用例
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## 📋 概述
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本测试套件为收入完整性检测算法（RevenueIntegrityAlgorithm）提供全面的测试覆盖，包括正常场景、异常情况、边界值等共计19个测试场景。
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## 🏗️ 测试架构
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```
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app/tests/
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├── conftest.py # pytest配置文件，共享fixtures
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└── test_revenue_integrity.py # 主测试文件
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run_tests.py # 测试运行脚本
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```
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## 📊 测试场景覆盖
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### 1. 正常场景测试（3个用例）
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- ✅ **收入一致（有分成协议）**：充值45000元，申报45000元，预期无风险
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- ✅ **收入一致（无分成协议）**：无协议但收入匹配，预期无风险
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- ✅ **轻微差异（低风险）**：差异在可接受范围内
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### 2. 少报收入场景测试（3个用例）
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- ⚠️ **中度少报**：差异率28.57%，风险等级MEDIUM
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- 🚨 **高度少报**：差异率42.86%，风险等级HIGH
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- 🔴 **严重少报**：差异率71.43%，风险等级CRITICAL
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### 3. 多报收入场景测试（1个用例）
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- ⚠️ **轻微多报**：申报超过充值，但风险较低
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### 4. 边界值测试（7个用例）
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- 📌 **无充值数据**：有申报无充值，高风险
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- 📌 **无申报数据**：有充值无申报，Critical风险
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- 📌 **完全一致**：零差异，无风险
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- 📌 **大额边界值**：差异100000元（刚好达到Critical阈值）
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- 📌 **差异率边界值**：差异率50%（刚好达到Critical阈值）
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- 📌 **月度对账**：模拟真实30笔充值场景
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- 📌 **企业主播**：统一社会信用代码场景
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### 5. 错误处理测试（4个用例）
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- ❌ **缺少主播ID**：返回UNKNOWN风险等级
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- ❌ **缺少期间参数**：参数验证错误
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- ❌ **无效期间格式**：格式校验错误
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- ❌ **主播不存在**：数据不存在错误
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### 6. 真实业务场景测试（3个用例）
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- 🏢 **新主播无历史**：少量数据处理
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- 🏢 **企业主播**：企业主体测试
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- 🏢 **月度对账**：大量数据场景
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## 🚀 快速开始
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### 1. 安装依赖
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```bash
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# 安装pytest和异步测试支持
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pip install pytest pytest-asyncio pytest-html pytest-cov
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# 安装项目依赖
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pip install -r requirements.txt
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```
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### 2. 运行所有测试
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```bash
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# 使用运行脚本（推荐）
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python run_tests.py
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# 或直接使用pytest
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pytest app/tests/test_revenue_integrity.py -v
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```
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### 3. 运行特定测试
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```bash
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# 运行正常场景测试
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python run_tests.py -k "normal"
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# 运行少报收入测试
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python run_tests.py -k "under_reporting"
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# 运行边界值测试
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python run_tests.py -k "boundary"
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# 运行错误处理测试
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python run_tests.py -k "error"
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```
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### 4. 生成详细报告
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```bash
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# 生成HTML报告
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python run_tests.py --html=test_report.html
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# 生成覆盖率报告
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python run_tests.py --cov
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# 生成HTML覆盖率报告
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python run_tests.py --cov --html=coverage_report.html
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```
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## 📝 测试数据说明
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### Mock数据结构
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#### 1. 主播信息（StreamerInfo）
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```python
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{
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"streamer_id": "ZB_TEST_001",
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"streamer_name": "测试主播",
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"entity_type": "individual", # individual/enterprise
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"tax_registration_no": "TAX123456789",
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"unified_social_credit_code": None,
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"id_card_no": "110101199001011234",
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"phone_number": "13800138000",
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"bank_account_no": "6222021234567890123",
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"bank_name": "中国工商银行",
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}
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```
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#### 2. 充值数据（PlatformRecharge）
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```python
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{
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"recharge_id": "RC001",
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"user_name": "测试用户",
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"amount": 10000.0,
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"time": datetime(2024, 1, 15, 10, 30, 0),
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"payment_method": "bank_transfer",
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"status": "success",
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}
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```
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#### 3. 税务申报（TaxDeclaration）
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```python
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{
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"declaration_id": "TAX001",
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"taxpayer_name": "测试主播",
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"tax_period": "2024-01",
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"sales_revenue": 45000.0,
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"declaration_date": date(2024, 2, 15),
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"tax_rate": 0.03,
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}
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```
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#### 4. 分成协议（RevenueSharingContract）
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```python
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{
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"streamer_ratio": 70.0, # 主播分成70%
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"platform_ratio": 30.0, # 平台分成30%
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"contract_start_date": date(2024, 1, 1),
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"contract_end_date": date(2024, 12, 31),
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}
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```
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## 🎯 风险等级判断规则
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### 风险等级定义
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| 风险等级 | 差异率阈值 | 差异金额阈值 | 描述 |
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|---------|-----------|-------------|------|
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| **CRITICAL** | > 50% | > 100,000元 | 严重风险，可能存在重大税务问题 |
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| **HIGH** | > 30% | > 50,000元 | 高度风险，需要重点关注 |
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| **MEDIUM** | > 10% | > 10,000元 | 中度风险，需要进一步核查 |
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| **LOW** | > 5% | > 5,000元 | 低度风险，持续监控 |
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| **NONE** | ≤ 5% | ≤ 5,000元 | 正常，收入基本一致 |
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### 计算公式
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```python
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# 预期收入计算（如果有分成协议）
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expected_revenue = recharge_total * (streamer_ratio / 100)
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# 差异计算
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difference = abs(declared_revenue - expected_revenue)
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# 差异率计算
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difference_rate = (difference / expected_revenue) * 100
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```
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## 🧪 测试用例详解
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### 示例1：测试严重少报收入
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```python
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@pytest.mark.asyncio
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async def test_critical_under_reporting(self, algorithm, mock_db_session, streamer_info, mock_contract_data):
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"""测试场景6：严重少报收入（Critical风险）"""
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# 充值500000元，分成70%，预期350000元，申报100000元
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# 差异250000元，差异率71.43%
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recharge_data = [
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{"recharge_id": f"RC{i}", "user_name": "测试", "amount": 100000.0,
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"time": datetime(2024, 1, 15), "payment_method": "bank_transfer"}
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for i in range(1, 6)
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]
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declaration_data = [
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{"declaration_id": "TAX001", "taxpayer_name": "测试主播",
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"tax_period": "2024-01", "sales_revenue": 100000.0,
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"declaration_date": date(2024, 2, 15)}
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]
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mock_db_session.execute.side_effect = [
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self._create_streamer_result(streamer_info),
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self._create_recharge_result(recharge_data),
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self._create_declaration_result(declaration_data),
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self._create_contract_result(mock_contract_data),
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]
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# 执行检测
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context = self._create_context("ZB_TEST_001", "2024-01", mock_db_session)
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result = await algorithm.detect(context)
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# 断言
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assert result.risk_level == RiskLevel.CRITICAL
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assert result.risk_score >= 85.0
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assert "严重风险" in result.description
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assert result.risk_data["difference"] >= 100000.0
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```
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### 示例2：测试边界值
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```python
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@pytest.mark.asyncio
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async def test_large_amount_boundary(self, algorithm, mock_db_session, streamer_info):
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"""测试场景11：大额边界值（刚好10万元差异）"""
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# 充值200000元，申报100000元，差异100000元，差异率50%
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# 这个值刚好达到CRITICAL的金额阈值
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recharge_data = [
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{"recharge_id": "RC001", "user_name": "测试", "amount": 200000.0,
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"time": datetime(2024, 1, 15), "payment_method": "bank_transfer"}
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]
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declaration_data = [
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{"declaration_id": "TAX001", "taxpayer_name": "测试主播",
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"tax_period": "2024-01", "sales_revenue": 100000.0,
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"declaration_date": date(2024, 2, 15)}
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]
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mock_db_session.execute.side_effect = [
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self._create_streamer_result(streamer_info),
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self._create_recharge_result(recharge_data),
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self._create_declaration_result(declaration_data),
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MagicMock(scalar_one_or_none=lambda: None),
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]
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# 执行检测
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context = self._create_context("ZB_TEST_001", "2024-01", mock_db_session)
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result = await algorithm.detect(context)
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# 断言：刚好达到Critical阈值
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assert result.risk_level == RiskLevel.CRITICAL
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assert result.risk_data["difference"] == 100000.0
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```
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## 🔧 扩展测试
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### 添加新的测试场景
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1. **在test_revenue_integrity.py中添加新方法**：
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```python
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@pytest.mark.asyncio
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async def test_new_scenario(self, algorithm, mock_db_session, streamer_info):
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"""测试新场景：描述"""
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# 准备测试数据
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recharge_data = [...]
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declaration_data = [...]
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# Mock数据库查询
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mock_db_session.execute.side_effect = [...]
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# 执行检测
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context = self._create_context("ZB_TEST_001", "2024-01", mock_db_session)
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result = await algorithm.detect(context)
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# 断言结果
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assert result.risk_level == RiskLevel.XXX
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assert ...
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```
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2. **在conftest.py中添加新的Mock数据**：
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```python
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@pytest.fixture
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def mock_new_data():
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"""新类型Mock数据"""
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return {
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# 数据结构定义
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}
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```
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## 📈 测试报告
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### 运行测试后的输出示例
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```
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===========================================
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收入完整性检测算法测试运行器
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===========================================
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执行命令: python -m pytest app/tests/test_revenue_integrity.py -v
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collected 19 items
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityNormal::test_revenue_match_with_contract PASSED [ 5%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityNormal::test_revenue_match_without_contract PASSED [ 10%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityNormal::test_slight_difference_low_risk PASSED [ 15%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityUnderReporting::test_medium_under_reporting PASSED [ 21%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityUnderReporting::test_high_under_reporting PASSED [ 26%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityUnderReporting::test_critical_under_reporting PASSED [ 31%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityOverReporting::test_over_reporting_low_risk PASSED [ 36%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityEdgeCases::test_no_recharge_data PASSED [ 42%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityEdgeCases::test_no_declaration_data PASSED [ 47%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityEdgeCases::test_zero_difference PASSED [ 52%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityEdgeCases::test_large_amount_boundary PASSED [ 57%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityEdgeCases::test_rate_boundary_50_percent PASSED [ 63%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityErrorHandling::test_missing_streamer_id PASSED [ 68%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityErrorHandling::test_missing_period PASSED [ 73%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityErrorHandling::test_invalid_period_format PASSED [ 78%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityErrorHandling::test_streamer_not_found PASSED [ 84%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityBusinessScenarios::test_monthly_reconciliation PASSED [ 89%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityBusinessScenarios::test_new_streamer_no_history PASSED [ 94%]
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app/tests/test_revenue_integrity.py::TestRevenueIntegrityBusinessScenarios::test_enterprise_streamer PASSED [100%]
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===========================================
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✓ 所有测试通过！
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===========================================
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```
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## ⚠️ 注意事项
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1. **异步测试**：所有测试都是异步的，需要使用`@pytest.mark.asyncio`标记
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2. **数据库Mock**：使用`AsyncMock`模拟数据库会话，避免真实数据库连接
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3. **数据隔离**：每次测试使用独立的Mock数据，避免数据污染
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4. **风险等级断言**：确保断言的风险等级与测试场景匹配
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5. **边界值测试**：特别注意差异率和金额的边界值
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## 🐛 常见问题
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### Q: 测试运行失败，提示"ModuleNotFoundError"
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**A**: 确保在项目根目录运行，并检查PYTHONPATH设置
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```bash
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export PYTHONPATH=/path/to/deeprisk-claude-1/backend:$PYTHONPATH
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```
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### Q: 异步测试报错
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**A**: 确保安装了`pytest-asyncio`并使用正确的标记
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```bash
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pip install pytest-asyncio
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```
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### Q: 想要调试特定测试
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**A**: 使用pytest的调试选项
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```bash
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pytest app/tests/test_revenue_integrity.py::TestRevenueIntegrityNormal::test_revenue_match_with_contract -v -s
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```
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## 📚 参考资料
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- [pytest文档](https://docs.pytest.org/)
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- [pytest-asyncio文档](https://pytest-asyncio.readthedocs.io/)
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- [Python unittest.mock](https://docs.python.org/3/library/unittest.mock.html)
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- [SQLAlchemy异步支持](https://docs.sqlalchemy.org/en/14/orm/extensions/asyncio.html)
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## 🤝 贡献
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欢迎提交新的测试用例！请确保：
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1. 测试场景明确
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2. Mock数据完整
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3. 断言准确
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4. 遵循现有代码风格
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---
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**创建时间**: 2024-11-30
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**版本**: 1.0.0
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**作者**: Claude Code
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