287 lines
7.5 KiB
Python
287 lines
7.5 KiB
Python
"""
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Pytest配置文件
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提供共享的测试fixtures和配置
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"""
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import pytest
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from unittest.mock import Mock
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.models.risk_detection import DetectionRule, RiskLevel
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from app.services.risk_detection.engine.rule_engine import RuleEngine
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from app.services.risk_detection.engine.dependency_resolver import DependencyResolver
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from app.services.risk_detection.engine.execution_plan import ExecutionPlanner
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from app.services.risk_detection.engine.result_processor import ResultProcessor
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@pytest.fixture
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def mock_db_session():
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"""模拟数据库会话"""
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session = Mock(spec=AsyncSession)
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return session
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@pytest.fixture
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def sample_detection_rules():
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"""模拟检测规则列表"""
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rules = []
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# 规则1：收入完整性检测
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rule1 = Mock(spec=DetectionRule)
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rule1.rule_id = "rule_revenue_integrity"
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rule1.algorithm_code = "REVENUE_INTEGRITY_CHECK"
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rule1.rule_name = "收入完整性检测"
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rule1.parameters = {
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"comparison_type": "monthly",
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"dependencies": []
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}
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rule1.is_enabled = True
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rules.append(rule1)
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# 规则2：私户收款检测
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rule2 = Mock(spec=DetectionRule)
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rule2.rule_id = "rule_private_account"
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rule2.algorithm_code = "PRIVATE_ACCOUNT_DETECTION"
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rule2.rule_name = "私户收款检测"
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rule2.parameters = {
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"threshold_amount": 10000,
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"dependencies": ["rule_revenue_integrity"]
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}
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rule2.is_enabled = True
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rules.append(rule2)
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# 规则3：发票虚开检测
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rule3 = Mock(spec=DetectionRule)
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rule3.rule_id = "rule_invoice_fraud"
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rule3.algorithm_code = "INVOICE_FRAUD_DETECTION"
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rule3.rule_name = "发票虚开检测"
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rule3.parameters = {
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"suspicious_rate_threshold": 0.3,
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"dependencies": ["rule_revenue_integrity"]
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}
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rule3.is_enabled = True
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rules.append(rule3)
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# 规则4：费用异常检测
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rule4 = Mock(spec=DetectionRule)
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rule4.rule_id = "rule_expense_anomaly"
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rule4.algorithm_code = "EXPENSE_ANOMALY_DETECTION"
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rule4.rule_name = "费用异常检测"
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rule4.parameters = {
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"anomaly_threshold": 2.0,
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"dependencies": []
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}
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rule4.is_enabled = True
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rules.append(rule4)
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# 规则5：税率错误检测
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rule5 = Mock(spec=DetectionRule)
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rule5.rule_id = "rule_tax_rate"
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rule5.algorithm_code = "TAX_RATE_CHECK"
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rule5.rule_name = "税率错误检测"
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rule5.parameters = {
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"dependencies": []
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}
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rule5.is_enabled = True
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rules.append(rule5)
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# 规则6：综合风险评估
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rule6 = Mock(spec=DetectionRule)
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rule6.rule_id = "rule_tax_risk_assessment"
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rule6.algorithm_code = "TAX_RISK_ASSESSMENT"
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rule6.rule_name = "综合风险评估"
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rule6.parameters = {
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"dependencies": [
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"rule_revenue_integrity",
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"rule_private_account",
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"rule_invoice_fraud",
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"rule_expense_anomaly",
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"rule_tax_rate"
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]
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}
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rule6.is_enabled = True
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rules.append(rule6)
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return rules
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@pytest.fixture
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def rule_engine(mock_db_session):
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"""规则引擎实例"""
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engine = RuleEngine(db_session=mock_db_session)
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return engine
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@pytest.fixture
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def dependency_resolver():
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"""依赖解析器实例"""
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return DependencyResolver()
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@pytest.fixture
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def execution_planner():
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"""执行计划器实例"""
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return ExecutionPlanner()
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@pytest.fixture
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def result_processor():
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"""结果处理器实例"""
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return ResultProcessor()
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@pytest.fixture
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def mock_detection_results():
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"""模拟检测结果列表"""
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from app.services.risk_detection.engine.result_processor import DetectionResult
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results = []
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# 结果1：低风险
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result1 = DetectionResult(
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task_id="task_1",
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rule_id="rule_1",
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entity_id="entity_1",
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entity_type="streamer",
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risk_level=RiskLevel.LOW,
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risk_score=25.0,
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description="检测到轻微风险",
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suggestion="继续保持合规状态"
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)
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results.append(result1)
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# 结果2：中风险
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result2 = DetectionResult(
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task_id="task_1",
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rule_id="rule_2",
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entity_id="entity_1",
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entity_type="streamer",
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risk_level=RiskLevel.MEDIUM,
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risk_score=55.0,
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description="检测到中等风险",
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suggestion="需要关注并及时处理"
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)
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results.append(result2)
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# 结果3：高风险
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result3 = DetectionResult(
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task_id="task_1",
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rule_id="rule_3",
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entity_id="entity_1",
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entity_type="streamer",
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risk_level=RiskLevel.HIGH,
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risk_score=80.0,
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description="检测到高风险",
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suggestion="建议立即采取整改措施"
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)
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results.append(result3)
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return results
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@pytest.fixture
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def sample_entity_info():
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"""模拟实体信息"""
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return {
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"entity_id": "streamer_001",
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"entity_type": "streamer",
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"entity_name": "测试主播",
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"period": "2024-01",
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"taxpayer_id": "12345678901234567890",
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"unified_social_credit_code": "91310000MA1KXXXXXX",
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"id_card_no": "110101199001011234"
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}
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@pytest.fixture
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def sample_recharge_data():
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"""模拟充值数据"""
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return {
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"total": 100000.00,
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"count": 50,
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"top_records": [
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{
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"recharge_id": "R001",
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"user_name": "用户A",
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"amount": 5000.0,
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"time": "2024-01-15 10:30:00",
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"payment_method": "支付宝"
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},
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{
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"recharge_id": "R002",
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"user_name": "用户B",
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"amount": 3000.0,
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"time": "2024-01-16 14:20:00",
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"payment_method": "微信"
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}
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]
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}
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@pytest.fixture
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def sample_declaration_data():
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"""模拟申报数据"""
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return {
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"total": 80000.00,
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"count": 3,
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"records": [
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{
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"declaration_id": "D001",
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"taxpayer_name": "测试主播",
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"tax_period": "2024-01",
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"sales_revenue": 50000.0,
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"declaration_date": "2024-02-15"
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},
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{
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"declaration_id": "D002",
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"taxpayer_name": "测试主播",
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"tax_period": "2024-01",
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"sales_revenue": 30000.0,
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"declaration_date": "2024-02-15"
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}
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]
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}
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@pytest.fixture
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def sample_contract_data():
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"""模拟合同数据"""
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return {
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"streamer_ratio": 70.0,
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"platform_ratio": 30.0,
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"contract_start_date": "2024-01-01",
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"contract_end_date": "2024-12-31",
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"contract_status": "active"
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}
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@pytest.fixture
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def sample_risk_thresholds():
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"""模拟风险阈值配置"""
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return {
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"critical_rate_threshold": 50.0,
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"critical_amount_threshold": 100000.0,
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"high_rate_threshold": 30.0,
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"high_amount_threshold": 50000.0,
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"medium_rate_threshold": 10.0,
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"medium_amount_threshold": 10000.0,
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"low_rate_threshold": 5.0,
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"low_amount_threshold": 5000.0,
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}
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# 配置pytest-asyncio
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def pytest_configure(config):
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"""配置pytest"""
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config.addinivalue_line(
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"markers", "asyncio: mark test as async"
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)
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# 自定义标记
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def pytest_collection_modifyitems(config, items):
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"""修改收集的测试项目"""
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for item in items:
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# 为所有异步测试添加asyncio标记
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if asyncio.iscoroutinefunction(getattr(item.function, "__code__", None)):
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item.add_marker(pytest.mark.asyncio)
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