v0-json-schema
This commit is contained in:
gongwenxin
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"""Pydantic models for application configuration."""
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from pydantic import BaseModel
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from typing import Optional, Dict, Literal
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# These models were previously in config/manager.py, moved here for better organization.
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class APICallerConfig(BaseModel):
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default_timeout: int = 30
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default_headers: Optional[Dict[str, str]] = None
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# Add other API caller specific configs: e.g., retry_attempts, backoff_factor
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class JSONSchemaValidatorConfig(BaseModel):
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default_draft_version: Optional[str] = None # e.g., "draft7", "draft2020-12"
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# Add other schema validator specific configs
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class RuleStorageConfig(BaseModel):
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type: Literal["filesystem", "database", "in_memory"] = "filesystem"
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path: Optional[str] = "./rules" # For filesystem adapter: path to rules directory
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connection_string: Optional[str] = None # For database adapter
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# Add other storage specific configs, e.g., for filesystem: file_pattern = "*.json"
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class RuleRepositoryConfig(BaseModel):
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storage: RuleStorageConfig = RuleStorageConfig()
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default_version_strategy: Literal["latest_enabled", "latest_stable", "exact"] = "latest_enabled"
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preload_rules: bool = False
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# Add other rule repository specific configs
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class LoggingConfig(BaseModel):
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level: Literal["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"] = "INFO"
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format: str = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
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# file_path: Optional[str] = None # Optional: if logging to a file
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class TestExecutorConfig(BaseModel):
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# Add configurations specific to the Test Executor
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# For example, default behavior for failing a test step, etc.
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stop_on_first_failure: bool = False
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class ReportGeneratorConfig(BaseModel):
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# Add configurations specific to the Report Generator
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output_format: Literal["json", "html", "xml"] = "json"
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output_path: str = "./reports"
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class AppConfig(BaseModel):
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app_name: str = "DDMS Compliance Suite"
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logging: LoggingConfig = LoggingConfig()
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api_caller: APICallerConfig = APICallerConfig()
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json_schema_validator: JSONSchemaValidatorConfig = JSONSchemaValidatorConfig()
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rule_repository: RuleRepositoryConfig = RuleRepositoryConfig()
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test_executor: TestExecutorConfig = TestExecutorConfig()
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report_generator: ReportGeneratorConfig = ReportGeneratorConfig()
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# input_parser: ... # Config for input parser if needed
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# assertion_engine: ... # Config for assertion engine if needed
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"""Base Pydantic models for the application."""
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from pydantic import BaseModel, Field
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from typing import Optional, List, Dict, Any, Union, Literal
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from enum import Enum
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class SeverityLevel(str, Enum):
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ERROR = "error"
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WARNING = "warning"
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INFO = "info"
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class RuleCategory(str, Enum):
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JSON_SCHEMA = "JSONSchema"
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API_LINTING = "APILinting"
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BUSINESS_LOGIC = "BusinessLogic"
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DATA_QUALITY = "DataQuality"
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SECURITY = "Security"
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PERFORMANCE = "Performance"
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MAPPING = "Mapping"
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PYTHON_CODE = "PythonCode" # Python代码规则类别
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API_DESIGN = "APIDesign" # API设计规则类别
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ERROR_HANDLING = "ErrorHandling" # 错误处理规则类别
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COMPATIBILITY = "Compatibility" # 兼容性规则类别
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GENERIC = "Generic"
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class TargetType(str, Enum):
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API_REQUEST = "APIRequest"
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API_RESPONSE = "APIResponse"
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DATA_OBJECT = "DataObject"
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OPENAPI_SPECIFICATION = "OpenAPISpecification"
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GENERIC_TARGET = "GenericTarget"
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class RuleLifecycle(str, Enum):
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"""规则生命周期枚举，定义规则在测试流程中的适用阶段"""
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REQUEST_PREPARATION = "请求准备阶段"
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RESPONSE_VALIDATION = "响应验证阶段"
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POST_VALIDATION = "后处理阶段"
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API_SPECIFICATION_VALIDATION = "API规范验证阶段" # 新增的生命周期
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ANY_STAGE = "任意阶段"
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class RuleScope(str, Enum):
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"""规则作用域枚举，定义规则针对的具体对象"""
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REQUEST_URL = "请求URL"
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REQUEST_HEADERS = "请求头"
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REQUEST_PARAMS = "请求参数"
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REQUEST_BODY = "请求体"
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RESPONSE_STATUS = "响应状态码"
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RESPONSE_HEADERS = "响应头"
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RESPONSE_BODY = "响应体"
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RESPONSE_TIME = "响应时间"
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SECURITY = "安全性"
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PERFORMANCE = "性能"
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ANY_SCOPE = "任意作用域"
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class BaseRule(BaseModel):
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"""通用规则属性 (Pydantic基类 BaseRule)"""
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id: str # 规则唯一ID
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name: str # 规则名称
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description: Optional[str] = None # 规则详细描述
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category: RuleCategory # 规则类别
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version: str = "1.0.0" # 版本号
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severity: SeverityLevel = SeverityLevel.INFO # 严重性
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source: Optional[str] = None # 规则来源 (例如 "PlatformStandard-XYZ", "OWASP-ASVS")
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is_enabled: bool = True # 是否启用
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tags: Optional[List[str]] = None # 规则标签 (如 "critical", "wellbore")
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target_type: Optional[TargetType] = None # 规则适用目标类型 (描述性元数据)
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target_identifier: Optional[str] = None # 规则适用目标的具体标识 (描述性元数据)
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author: Optional[str] = None # 规则作者
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# 新增字段
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lifecycle: Optional[RuleLifecycle] = Field(
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default=RuleLifecycle.ANY_STAGE,
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description="规则的推荐适用阶段或类型。主要用于识别 API_SPECIFICATION_VALIDATION (静态分析) 规则。"
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"对于其他动态规则，此字段为元数据提示，实际执行阶段由 TestStep 定义。"
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)
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scope: Optional[RuleScope] = Field(
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default=RuleScope.ANY_SCOPE,
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description="描述规则逻辑主要关注的API交互部分 (例如，请求头、响应体)。"
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"此字段为描述性元数据，用于规则分类和理解，不作为执行时的强制约束。"
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)
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code: Optional[str] = None # 规则验证代码
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class JSONSchemaDefinition(BaseRule):
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"""JSON Schema 定义 (用于API请求/响应体结构验证)"""
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category: Literal[RuleCategory.JSON_SCHEMA] = RuleCategory.JSON_SCHEMA
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schema_content: Dict[str, Any] # 实际的JSON Schema
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class APILintingRuleset(BaseRule):
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"""API 设计规范/Linting规则 (例如，基于Spectral的OpenAPI规范校验规则集)"""
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category: Literal[RuleCategory.API_LINTING] = RuleCategory.API_LINTING
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ruleset_format: str = "spectral" # 例如 "spectral", "custom_json_rules"
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ruleset_content: Union[str, Dict[str, Any]] # 规则集内容或其引用（例如，文件路径或URL，或直接嵌入的规则字典）
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class BusinessAssertionTemplate(BaseRule):
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"""业务逻辑断言模板或具体规则"""
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category: Literal[RuleCategory.BUSINESS_LOGIC] = RuleCategory.BUSINESS_LOGIC
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template_language: str = "python_expression" # 如 "python_expression", "jsonpath_assert"
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template_expression: str
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expected_parameters: Optional[List[str]] = None # 执行断言模板时需要输入的参数列表
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class DataQualityRule(BaseRule):
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"""数据质量校验规则"""
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category: Literal[RuleCategory.DATA_QUALITY] = RuleCategory.DATA_QUALITY
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# Specific fields for data quality rules, e.g.:
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field_name: Optional[str] = None
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validation_type: str # e.g., "regex", "range", "custom_function"
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validation_expression: str # regex pattern, range boundaries, function name/path
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class PythonCodeRule(BaseRule):
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"""使用 Python 代码定义的规则
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此类规则允许以 Python 代码片段形式定义复杂的验证逻辑，提供了最大的灵活性。
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代码将在受控环境中执行，以确保安全性。
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"""
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category: Literal[RuleCategory.PYTHON_CODE] = RuleCategory.PYTHON_CODE
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# Python 代码内容或文件路径
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code_file: Optional[str] = None
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# 脚本入口函数名，默认为 validate
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entry_function: str = "validate"
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# 预期的入口函数参数
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expected_parameters: Optional[List[str]] = None
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# 是否允许导入外部模块 (出于安全考虑，默认为 False)
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allow_imports: bool = False
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# 允许导入的模块列表 (如果 allow_imports 为 True)
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allowed_modules: Optional[List[str]] = None
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# 超时设置（秒），防止无限循环等恶意代码
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timeout: int = 5
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# 代码依赖的其他规则ID
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depends_on: Optional[List[str]] = None
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# 新增规则类型
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class PerformanceRule(BaseRule):
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"""性能相关规则，如响应时间、吞吐量等"""
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category: Literal[RuleCategory.PERFORMANCE] = RuleCategory.PERFORMANCE
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lifecycle: Literal[RuleLifecycle.RESPONSE_VALIDATION] = RuleLifecycle.RESPONSE_VALIDATION
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scope: Literal[RuleScope.RESPONSE_TIME] = RuleScope.RESPONSE_TIME
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threshold: Union[float, int] # 性能阈值
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metric: str # 性能指标名称
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unit: str = "ms" # 默认单位：毫秒
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class SecurityRule(BaseRule):
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"""安全相关规则，如身份验证、授权、加密等"""
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category: Literal[RuleCategory.SECURITY] = RuleCategory.SECURITY
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check_type: str # 安全检查类型（如认证、授权、加密等）
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expected_value: Optional[str] = None # 预期值
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class RESTfulDesignRule(BaseRule):
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"""RESTful API设计规则，如HTTP方法使用、URL设计等"""
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category: Literal[RuleCategory.API_DESIGN] = RuleCategory.API_DESIGN
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design_aspect: str # 设计方面（如URL、HTTP方法、参数等）
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pattern: Optional[str] = None # 匹配模式（如正则表达式）
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class ErrorHandlingRule(BaseRule):
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"""错误处理规则，如错误码、错误消息等"""
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category: Literal[RuleCategory.ERROR_HANDLING] = RuleCategory.ERROR_HANDLING
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error_code: str # 错误码
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expected_status: int # 预期HTTP状态码
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expected_message: Optional[str] = None # 预期错误消息
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# 更新联合类型以包含新规则类型
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AnyRule = Union[
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JSONSchemaDefinition,
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APILintingRuleset,
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BusinessAssertionTemplate,
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DataQualityRule,
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PythonCodeRule,
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PerformanceRule,
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SecurityRule,
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RESTfulDesignRule,
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ErrorHandlingRule,
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BaseRule # 通用或未明确分类的规则
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]
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class RuleQuery(BaseModel):
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"""规则查询条件对象 (Pydantic模型)"""
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rule_id: Optional[str] = None
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category: Optional[RuleCategory] = None
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target_type: Optional[TargetType] = None
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target_identifier: Optional[str] = None
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version: Optional[str] = "latest" # 或特殊标识 ("latest", "stable", or specific version)
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tags: Optional[List[str]] = None
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is_enabled: Optional[bool] = True # 默认查询已启用的规则
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# 新增字段
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lifecycle: Optional[RuleLifecycle] = None
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scope: Optional[RuleScope] = None
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@@ -0,0 +1,144 @@
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"""
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Pydantic models for Test Cases, Test Steps, and Test Suites.
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"""
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from typing import Optional, List, Dict, Any, Union, Literal
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from pydantic import BaseModel, Field, HttpUrl
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from enum import Enum
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from .rule_models import SeverityLevel # Assuming rule_models.py is in the same directory
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from ..api_caller.caller import APIRequest # Adjust path as necessary
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class TestDataGenerationStrategy(str, Enum):
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"""Defines how test data for an API request should be generated."""
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STATIC = "static" # Data is explicitly provided
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FROM_SCHEMA = "from_schema" # Data is generated based on OpenAPI/JSON schema
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FROM_PREVIOUS_STEP = "from_previous_step" # Data is extracted from a previous test step's output
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AI_GENERATED = "ai_generated" # Data is generated by an AI model
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class TestDataGenerationConfig(BaseModel):
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"""Configuration for generating test data for an API request."""
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strategy: TestDataGenerationStrategy = TestDataGenerationStrategy.STATIC
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# For STATIC strategy:
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static_data: Optional[Dict[str, Any]] = Field(default=None, description="Explicit data for the request (e.g., body, params).")
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# For FROM_SCHEMA strategy:
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schema_source: Optional[str] = Field(default=None, description="Identifier for the schema to be used (e.g., operationId, or path to schema file).")
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# For FROM_PREVIOUS_STEP strategy:
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source_step_id: Optional[str] = Field(default=None, description="The ID of the previous TestStep whose output will be used.")
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extraction_rules: Optional[Dict[str, str]] = Field(default_None, description="Rules to extract data (e.g., JSONPath expressions like {'user_id': '$.body.id'}).")
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# For AI_GENERATED strategy:
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ai_prompt: Optional[str] = Field(default=None, description="Prompt to be used by an AI model to generate data.")
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ai_model_config: Optional[Dict[str, Any]] = Field(default_None, description="Configuration for the AI model (e.g., temperature, max_tokens).")
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class APIRequestContext(BaseModel):
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"""
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Defines how to construct the APIRequest for a TestStep, potentially using
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data from previous steps or other dynamic sources.
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"""
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method: str = Field(description="HTTP method (GET, POST, PUT, DELETE, etc.).")
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url_template: str = Field(description="URL template, can contain placeholders like {base_url} or {resource_id}.")
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path_params_source: Optional[Dict[str, TestDataGenerationConfig]] = Field(default_None, description="How to generate/get path parameters.")
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query_params_source: Optional[Dict[str, TestDataGenerationConfig]] = Field(default_None, description="How to generate/get query parameters.")
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headers_source: Optional[Dict[str, TestDataGenerationConfig]] = Field(default_None, description="How to generate/get request headers. Default headers can be added by the orchestrator.")
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body_source: Optional[TestDataGenerationConfig] = Field(default_None, description="How to generate/get the request body.")
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# Stores the actual APIRequest object after context resolution
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# This field will be populated by the TestOrchestrator before execution.
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resolved_request: Optional[APIRequest] = Field(default=None, exclude=True)
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class TestStep(BaseModel):
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"""
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Represents a single step within a TestCase, typically involving one API call
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and a set of rules to be validated against its request/response.
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"""
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step_id: str = Field(description="Unique identifier for this test step within the TestCase.")
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description: Optional[str] = Field(default=None, description="Description of what this test step does.")
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api_request_context: APIRequestContext = Field(description="Context to build the API request for this step.")
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# Rules to be applied at different phases of this step
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# Applied after the request is prepared but before it's sent.
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# Useful for validating the constructed request itself.
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request_preparation_rule_ids: List[str] = Field(default_factory=list, description="Rules to apply to the APIRequest before sending.")
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# Applied after the API response is received. This is the most common place for validation rules.
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response_validation_rule_ids: List[str] = Field(default_factory=list, description="Rules to apply to the APIResponse.")
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# Applied after response validation, يمكن استخدامه لتنظيف البيانات أو إجراءات ما بعد الاختبار
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post_validation_rule_ids: List[str] = Field(default_factory=list, description="Rules to apply after response validation (e.g., cleanup).")
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# Configuration for expected outcomes, more specific than just rule pass/fail
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expected_status_code: Optional[int] = Field(default=None, description="Expected HTTP status code.")
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# Allows defining assertions on the response body using something like JSONPath
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# e.g., {"$.data.status": "completed", "$.errors": null}
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response_body_assertions: Optional[Dict[str, Any]] = Field(default_None, description="Assertions to make on the response body (e.g., using JSONPath).")
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# Execution control
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skip: bool = Field(default=False, description="If True, this test step will be skipped.")
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# Allows storing output from this step to be used by subsequent steps
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# e.g., {"created_user_id": "$.response.body.id"}
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outputs_to_extract: Optional[Dict[str, str]] = Field(default_None, description="JSONPath expressions to extract data from response to be used in later steps.")
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class TestCaseExecutionMode(str, Enum):
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SEQUENTIAL = "sequential" # Steps are executed one after another
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PARALLEL = "parallel" # Steps (if independent) can be executed in parallel
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class TestCase(BaseModel):
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"""
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Defines a test case, which consists of one or more test steps,
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metadata, and configurations for execution.
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"""
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id: str = Field(description="Unique identifier for the test case.")
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name: str = Field(description="Name of the test case.")
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description: Optional[str] = Field(default=None, description="Detailed description of the test case.")
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tags: List[str] = Field(default_factory=list, description="Tags for categorizing and filtering test cases.")
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severity: SeverityLevel = Field(default=SeverityLevel.INFO, description="Severity of the test case if it fails.")
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author: Optional[str] = Field(default=None, description="Author of the test case.")
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creation_date: Optional[str] = Field(default=None, description="Date when the test case was created (ISO format).") # Consider using datetime
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version: str = Field(default="1.0.0", description="Version of the test case.")
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# Test Steps
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steps: List[TestStep] = Field(description="A list of test steps to be executed for this test case.")
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execution_mode: TestCaseExecutionMode = Field(default=TestCaseExecutionMode.SEQUENTIAL, description="How the steps in this test case should be executed.")
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# Data that can be shared across steps within this test case.
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# Steps can read from and write to this context.
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shared_context: Dict[str, Any] = Field(default_factory=dict, description="Data context televisão across steps.")
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# Overall expected outcome for the test case (can be high-level)
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expected_overall_result: Optional[str] = Field(default=None, description="A high-level description of the expected outcome for the entire test case.")
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# For iterative/load testing
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execution_count: int = Field(default=1, ge=1, description="Number of times this test case should be executed.")
|
||||
# If > 1, defines delay between iterations in seconds.
|
||||
delay_between_iterations_sec: float = Field(default=0, ge=0)
|
||||
|
||||
|
||||
class TestSuite(BaseModel):
|
||||
"""
|
||||
A collection of TestCases, possibly with a shared configuration or setup/teardown logic.
|
||||
"""
|
||||
id: str = Field(description="Unique identifier for the test suite.")
|
||||
name: str = Field(description="Name of the test suite.")
|
||||
description: Optional[str] = Field(default=None, description="Description of the test suite.")
|
||||
tags: List[str] = Field(default_factory=list, description="Tags for categorizing and filtering test suites.")
|
||||
|
||||
# List of TestCase IDs or full TestCase objects. Using IDs allows for referencing.
|
||||
# For simplicity in this initial design, let's assume full TestCase objects.
|
||||
# Later, we could support referencing TestCase definitions stored elsewhere.
|
||||
test_cases: List[TestCase] = Field(default_factory=list, description="List of test cases included in this suite.")
|
||||
|
||||
# Global parameters or configurations that can apply to all TestCases in the suite
|
||||
# These could override individual TestCase settings or provide defaults.
|
||||
global_parameters: Optional[Dict[str, Any]] = Field(default_None, description="Parameters applicable to all test cases in the suite.")
|
||||
|
||||
# Setup: API calls or actions to perform before running any TestCase in the suite.
|
||||
# Similar structure to TestStep but without specific rule validations, more for setup.
|
||||
setup_steps: Optional[List[TestStep]] = Field(default_None, description="Steps to execute before running test cases in the suite.")
|
||||
|
||||
# Teardown: API calls or actions to perform after all TestCases in the suite have run.
|
||||
teardown_steps: Optional[List[TestStep]] = Field(default_None, description="Steps to execute after running test cases in the suite.")
|
||||
|
||||
# Execution control for the suite
|
||||
# e.g., run all, run tagged, run failed from previous
|
||||
execution_strategy: Optional[str] = Field(default=None, description="Strategy for executing test cases within the suite.")
|
||||
Reference in New Issue
Block a user