fix:yapi
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gongwenxin
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本 API 合规性测试框架主要由以下几个核心组件构成，它们协同工作以完成测试的定义、发现、执行和报告：
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本 API 合规性测试框架主要由以下几个核心组件构成，它们协同工作以完成测试的定义、发现、执行和报告：
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1. **命令行接口 (`run_api_tests.py`)**:
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1. **命令行接口 (`run_api_tests.py`)**:
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* 作为测试执行的入口。
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* 负责解析用户通过命令行传入的参数，例如 API 服务的基础 URL、API 规范文件路径（YAPI 或 Swagger）、测试用例目录、输出报告配置以及 LLM 相关配置。
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* 初始化并驱动 `APITestOrchestrator`。
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2. **测试编排器 (`APITestOrchestrator` 在 `ddms_compliance_suite/test_orchestrator.py`)**:
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* 作为测试执行的入口。
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* **核心控制器**：是整个测试流程的指挥中心。
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* 负责解析用户通过命令行传入的参数，例如 API 服务的基础 URL、API 规范文件路径（YAPI 或 Swagger）、测试用例目录、输出报告配置以及 LLM 相关配置。
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* **组件初始化**：负责初始化和管理其他关键组件，如 `InputParser`（API 规范解析器）、`APICaller`（API 请求调用器）、`TestCaseRegistry`（测试用例注册表）以及可选的 `LLMService`（大模型服务）。
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* 初始化并驱动 `APITestOrchestrator`。
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* **测试流程管理**：
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2. **测试编排器 (`APITestOrchestrator` 在 `ddms_compliance_suite/test_orchestrator.py`)**:
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* 调用 `InputParser` 解析指定的 API 规范文件，获取所有端点的定义。
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* 根据用户指定的过滤器（如 YAPI 分类或 Swagger 标签）筛选需要测试的 API 端点。
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* 对每一个选定的 API 端点：
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* 通过 `TestCaseRegistry` 获取所有适用于该端点的自定义测试用例类。
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* 实例化每个测试用例类。
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* 调用 `_prepare_initial_request_data` 方法准备初始请求数据（路径参数、查询参数、请求头、请求体）。此方法会根据全局配置和测试用例自身的配置决定是否使用 LLM 进行数据生成，并利用 `LLMService` 和动态 Pydantic 模型创建（`_create_pydantic_model_from_schema`）来实现。如果LLM未启用或不适用，则使用传统的基于 Schema 的数据生成逻辑（`_generate_params_from_list`, `_generate_data_from_schema`）。此阶段还实现了端点级别的LLM参数缓存。
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* 依次调用测试用例实例中定义的 `generate_*` 方法，允许测试用例修改生成的请求数据。
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* 调用测试用例实例中定义的 `validate_request_*` 方法，对即将发送的请求进行预校验。
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* 使用 `APICaller` 发送最终构建的 API 请求。
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* 接收到 API 响应后，调用测试用例实例中定义的 `validate_response` 和 `check_performance` 方法，对响应进行详细验证。
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* **结果汇总**：收集每个测试用例的执行结果 (`ExecutedTestCaseResult`)，汇总成每个端点的测试结果 (`TestResult`)，并最终生成整个测试运行的摘要 (`TestSummary`)。
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3. **测试用例注册表 (`TestCaseRegistry` 在 `ddms_compliance_suite/test_case_registry.py`)**:
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* **核心控制器**：是整个测试流程的指挥中心。
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* **动态发现**：负责在用户指定的目录 (`custom_test_cases_dir`) 下扫描并动态加载所有以 `.py` 结尾的测试用例文件。
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* **组件初始化**：负责初始化和管理其他关键组件，如 `InputParser`（API 规范解析器）、`APICaller`（API 请求调用器）、`TestCaseRegistry`（测试用例注册表）以及可选的 `LLMService`（大模型服务）。
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* **类识别与注册**：从加载的模块中，识别出所有继承自 `BaseAPITestCase` 的类，并根据其 `id` 属性进行注册。
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* **测试流程管理**：
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* **执行顺序排序**：在发现所有测试用例类后，会根据每个类的 `execution_order` 属性（主排序键，升序）和类名 `__name__`（次排序键，字母升序）对它们进行排序。
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* 调用 `InputParser` 解析指定的 API 规范文件，获取所有端点的定义。
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* **适用性筛选**：提供 `get_applicable_test_cases` 方法，根据 API 端点的 HTTP 方法和路径（通过正则表达式匹配）筛选出适用的、已排序的测试用例类列表给编排器。
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* 根据用户指定的过滤器（如 YAPI 分类或 Swagger 标签）筛选需要测试的 API 端点。
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* 对每一个选定的 API 端点：
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* 通过 `TestCaseRegistry` 获取所有适用于该端点的自定义测试用例类。
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* 实例化每个测试用例类。
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* 调用 `_prepare_initial_request_data` 方法准备初始请求数据（路径参数、查询参数、请求头、请求体）。此方法会根据全局配置和测试用例自身的配置决定是否使用 LLM 进行数据生成，并利用 `LLMService` 和动态 Pydantic 模型创建（`_create_pydantic_model_from_schema`）来实现。如果LLM未启用或不适用，则使用传统的基于 Schema 的数据生成逻辑（`_generate_params_from_list`, `_generate_data_from_schema`）。此阶段还实现了端点级别的LLM参数缓存。
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* 依次调用测试用例实例中定义的 `generate_*` 方法，允许测试用例修改生成的请求数据。
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* 调用测试用例实例中定义的 `validate_request_*` 方法，对即将发送的请求进行预校验。
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* 使用 `APICaller` 发送最终构建的 API 请求。
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* 接收到 API 响应后，调用测试用例实例中定义的 `validate_response` 和 `check_performance` 方法，对响应进行详细验证。
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* **结果汇总**：收集每个测试用例的执行结果 (`ExecutedTestCaseResult`)，汇总成每个端点的测试结果 (`TestResult`)，并最终生成整个测试运行的摘要 (`TestSummary`)。
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3. **测试用例注册表 (`TestCaseRegistry` 在 `ddms_compliance_suite/test_case_registry.py`)**:
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4. **测试框架核心 (`test_framework_core.py`)**:
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* **动态发现**：负责在用户指定的目录 (`custom_test_cases_dir`) 下扫描并动态加载所有以 `.py` 结尾的测试用例文件。
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* **`BaseAPITestCase`**：所有自定义测试用例的基类。它定义了测试用例应具备的元数据（如 `id`, `name`, `description`, `severity`, `tags`, `execution_order`, `applicable_methods`, `applicable_paths_regex` 以及 LLM 使用标志位）和一系列生命周期钩子方法（如 `generate_*`, `validate_*`）。
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* **类识别与注册**：从加载的模块中，识别出所有继承自 `BaseAPITestCase` 的类，并根据其 `id` 属性进行注册。
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* **`APIRequestContext` / `APIResponseContext`**：数据类，分别用于封装 API 请求和响应的上下文信息，在测试用例的钩子方法间传递。
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* **执行顺序排序**：在发现所有测试用例类后，会根据每个类的 `execution_order` 属性（主排序键，升序）和类名 `__name__`（次排序键，字母升序）对它们进行排序。
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* **`ValidationResult`**：数据类，用于表示单个验证点的结果（通过/失败、消息、详细信息）。
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* **适用性筛选**：提供 `get_applicable_test_cases` 方法，根据 API 端点的 HTTP 方法和路径（通过正则表达式匹配）筛选出适用的、已排序的测试用例类列表给编排器。
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* **`TestSeverity`**：枚举类型，定义测试用例的严重级别。
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4. **测试框架核心 (`test_framework_core.py`)**:
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5. **API 规范解析器 (`InputParser` 在 `ddms_compliance_suite/input_parser/parser.py`)**:
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* **`BaseAPITestCase`**：所有自定义测试用例的基类。它定义了测试用例应具备的元数据（如 `id`, `name`, `description`, `severity`, `tags`, `execution_order`, `applicable_methods`, `applicable_paths_regex` 以及 LLM 使用标志位）和一系列生命周期钩子方法（如 `generate_*`, `validate_*`）。
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* 负责读取和解析 YAPI（JSON 格式）或 Swagger/OpenAPI（JSON 或 YAML 格式）的 API 规范文件。
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* **`APIRequestContext` / `APIResponseContext`**：数据类，分别用于封装 API 请求和响应的上下文信息，在测试用例的钩子方法间传递。
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* 将原始规范数据转换成框架内部易于处理的结构化对象（如 `ParsedYAPISpec`, `YAPIEndpoint`, `ParsedSwaggerSpec`, `SwaggerEndpoint`）。
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* **`ValidationResult`**：数据类，用于表示单个验证点的结果（通过/失败、消息、详细信息）。
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* **`TestSeverity`**：枚举类型，定义测试用例的严重级别。
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5. **API 规范解析器 (`InputParser` 在 `ddms_compliance_suite/input_parser/parser.py`)**:
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6. **API 调用器 (`APICaller` 在 `ddms_compliance_suite/api_caller/caller.py`)**:
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* 负责读取和解析 YAPI（JSON 格式）或 Swagger/OpenAPI（JSON 或 YAML 格式）的 API 规范文件。
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* 封装了实际的 HTTP 请求发送逻辑。
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* 将原始规范数据转换成框架内部易于处理的结构化对象（如 `ParsedYAPISpec`, `YAPIEndpoint`, `ParsedSwaggerSpec`, `SwaggerEndpoint`）。
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* 接收一个 `APIRequest` 对象（包含方法、URL、参数、头部、请求体），使用如 `requests` 库执行请求，并返回一个 `APIResponse` 对象（包含状态码、响应头、响应体内容等）。
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6. **API 调用器 (`APICaller` 在 `ddms_compliance_suite/api_caller/caller.py`)**:
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7. **LLM 服务 (`LLMService` 在 `ddms_compliance_suite/llm_utils/llm_service.py`)** (可选):
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* 封装了实际的 HTTP 请求发送逻辑。
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* 如果配置了 LLM 服务（如通义千问的兼容 OpenAI 模式的 API），此组件负责与 LLM API 交互。
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* 接收一个 `APIRequest` 对象（包含方法、URL、参数、头部、请求体），使用如 `requests` 库执行请求，并返回一个 `APIResponse` 对象（包含状态码、响应头、响应体内容等）。
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* 主要用于根据 Pydantic 模型（从 JSON Schema 动态创建）智能生成复杂的请求参数或请求体。
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7. **LLM 服务 (`LLMService` 在 `ddms_compliance_suite/llm_utils/llm_service.py`)** (可选):
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* 如果配置了 LLM 服务（如通义千问的兼容 OpenAI 模式的 API），此组件负责与 LLM API 交互。
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* 主要用于根据 Pydantic 模型（从 JSON Schema 动态创建）智能生成复杂的请求参数或请求体。
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这个架构旨在提供一个灵活、可扩展的 API 测试框架，允许用户通过编写自定义的 Python 测试用例来定义复杂的验证逻辑。
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这个架构旨在提供一个灵活、可扩展的 API 测试框架，允许用户通过编写自定义的 Python 测试用例来定义复杂的验证逻辑。
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@ -56,67 +57,67 @@
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### 1. 创建自定义测试用例
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### 1. 创建自定义测试用例
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1. **创建 Python 文件**：在您的自定义测试用例目录（例如 `custom_testcases/`）下创建一个新的 `.py` 文件。
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1. **创建 Python 文件**：在您的自定义测试用例目录（例如 `custom_testcases/`）下创建一个新的 `.py` 文件。
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2. **继承 `BaseAPITestCase`**：定义一个或多个类，使其继承自 `ddms_compliance_suite.test_framework_core.BaseAPITestCase`。
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2. **继承 `BaseAPITestCase`**：定义一个或多个类，使其继承自 `ddms_compliance_suite.test_framework_core.BaseAPITestCase`。
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3. **定义元数据 (类属性)**：
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3. **定义元数据 (类属性)**：
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* `id: str`: 测试用例的全局唯一标识符 (例如 `"TC-MYFEATURE-001"`)。
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* `name: str`: 人类可读的名称。
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* `description: str`: 详细描述。
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* `severity: TestSeverity`: 严重程度 (例如 `TestSeverity.CRITICAL`, `TestSeverity.HIGH`, 等)。
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* `tags: List[str]`: 分类标签 (例如 `["smoke", "regression"]`)。
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* **`execution_order: int` (新增)**: 控制测试用例的执行顺序。**数值较小的会比较大的先执行**。如果多个测试用例此值相同，则它们会再根据类名的字母顺序排序。默认值为 `100`。
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```python
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class MyFirstCheck(BaseAPITestCase):
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execution_order = 10
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# ... other metadata
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class MySecondCheck(BaseAPITestCase):
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* `id: str`: 测试用例的全局唯一标识符 (例如 `"TC-MYFEATURE-001"`)。
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execution_order = 20
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* `name: str`: 人类可读的名称。
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# ... other metadata
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* `description: str`: 详细描述。
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```
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* `severity: TestSeverity`: 严重程度 (例如 `TestSeverity.CRITICAL`, `TestSeverity.HIGH`, 等)。
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* `applicable_methods: Optional[List[str]]`: 限制适用的 HTTP 方法 (例如 `["POST", "PUT"]`)。`None` 表示所有方法。
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* `tags: List[str]`: 分类标签 (例如 `["smoke", "regression"]`)。
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* `applicable_paths_regex: Optional[str]`: 限制适用的 API 路径 (Python 正则表达式)。`None` 表示所有路径。
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* **`execution_order: int` (新增)**: 控制测试用例的执行顺序。**数值较小的会比较大的先执行**。如果多个测试用例此值相同，则它们会再根据类名的字母顺序排序。默认值为 `100`。
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* **LLM 使用标志 (可选)**: 这些标志允许测试用例覆盖全局 LLM 配置。
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```python
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* `use_llm_for_body: bool = False`
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class MyFirstCheck(BaseAPITestCase):
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* `use_llm_for_path_params: bool = False`
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execution_order = 10
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* `use_llm_for_query_params: bool = False`
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# ... other metadata
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* `use_llm_for_headers: bool = False`
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(如果测试用例中不设置这些，则遵循 `run_api_tests.py` 传入的全局 LLM 开关。)
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4. **实现验证逻辑**：重写 `BaseAPITestCase` 中一个或多个 `generate_*` 或 `validate_*` 方法。
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class MySecondCheck(BaseAPITestCase):
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execution_order = 20
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# ... other metadata
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```
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* `applicable_methods: Optional[List[str]]`: 限制适用的 HTTP 方法 (例如 `["POST", "PUT"]`)。`None` 表示所有方法。
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* `applicable_paths_regex: Optional[str]`: 限制适用的 API 路径 (Python 正则表达式)。`None` 表示所有路径。
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* **LLM 使用标志 (可选)**: 这些标志允许测试用例覆盖全局 LLM 配置。
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* `use_llm_for_body: bool = False`
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* `use_llm_for_path_params: bool = False`
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* `use_llm_for_query_params: bool = False`
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* `use_llm_for_headers: bool = False`
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(如果测试用例中不设置这些，则遵循 `run_api_tests.py` 传入的全局 LLM 开关。)
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4. **实现验证逻辑**：重写 `BaseAPITestCase` 中一个或多个 `generate_*` 或 `validate_*` 方法。
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### 2. `BaseAPITestCase` 核心方法
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### 2. `BaseAPITestCase` 核心方法
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* **`__init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any])`**:
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* **`__init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any])`**:
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* 构造函数。`endpoint_spec` 包含当前测试端点的 API 定义，`global_api_spec` 包含完整的 API 规范。
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* 基类会初始化 `self.logger`，可用于记录日志。
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* **请求生成与修改方法**: 在 API 请求发送前调用，用于修改或生成请求数据。
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* 构造函数。`endpoint_spec` 包含当前测试端点的 API 定义，`global_api_spec` 包含完整的 API 规范。
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* `generate_query_params(self, current_query_params: Dict[str, Any]) -> Dict[str, Any]`
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* 基类会初始化 `self.logger`，可用于记录日志。
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* `generate_headers(self, current_headers: Dict[str, str]) -> Dict[str, str]`
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* **请求生成与修改方法**: 在 API 请求发送前调用，用于修改或生成请求数据。
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* `generate_request_body(self, current_body: Optional[Any]) -> Optional[Any]`
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* （如果需要，您也可以尝试定义 `generate_path_params` 方法来自定义路径参数的生成，其模式与上述类似。）
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* **请求预校验方法**: 在请求数据完全构建后、发送前调用，用于静态检查。返回 `List[ValidationResult]`。
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* `generate_query_params(self, current_query_params: Dict[str, Any]) -> Dict[str, Any]`
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* `validate_request_url(self, url: str, request_context: APIRequestContext) -> List[ValidationResult]`
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* `generate_headers(self, current_headers: Dict[str, str]) -> Dict[str, str]`
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* `validate_request_headers(self, headers: Dict[str, str], request_context: APIRequestContext) -> List[ValidationResult]`
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* `generate_request_body(self, current_body: Optional[Any]) -> Optional[Any]`
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* `validate_request_body(self, body: Optional[Any], request_context: APIRequestContext) -> List[ValidationResult]`
|
* **请求预校验方法**: 在请求数据完全构建后、发送前调用，用于静态检查。返回 `List[ValidationResult]`。
|
||||||
|
|
||||||
* **响应验证方法**: 在收到 API 响应后调用，这是最主要的验证阶段。返回 `List[ValidationResult]`。
|
* `validate_request_url(self, url: str, request_context: APIRequestContext) -> List[ValidationResult]`
|
||||||
* `validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> List[ValidationResult]`
|
* `validate_request_headers(self, headers: Dict[str, str], request_context: APIRequestContext) -> List[ValidationResult]`
|
||||||
* 检查状态码、响应头、响应体内容是否符合预期。
|
* `validate_request_body(self, body: Optional[Any], request_context: APIRequestContext) -> List[ValidationResult]`
|
||||||
* 进行业务逻辑相关的断言。
|
* **响应验证方法**: 在收到 API 响应后调用，这是最主要的验证阶段。返回 `List[ValidationResult]`。
|
||||||
|
|
||||||
* **性能检查方法 (可选)**:
|
* `validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> List[ValidationResult]`
|
||||||
* `check_performance(self, response_context: APIResponseContext, request_context: APIRequestContext) -> List[ValidationResult]`
|
* 检查状态码、响应头、响应体内容是否符合预期。
|
||||||
* 通常用于检查响应时间 `response_context.elapsed_time`。
|
* 进行业务逻辑相关的断言。
|
||||||
|
* **性能检查方法 (可选)**:
|
||||||
|
|
||||||
|
* `check_performance(self, response_context: APIResponseContext, request_context: APIRequestContext) -> List[ValidationResult]`
|
||||||
|
* 通常用于检查响应时间 `response_context.elapsed_time`。
|
||||||
|
|
||||||
### 3. 核心辅助类
|
### 3. 核心辅助类
|
||||||
|
|
||||||
* **`ValidationResult(passed: bool, message: str, details: Optional[Dict[str, Any]] = None)`**:
|
* **`ValidationResult(passed: bool, message: str, details: Optional[Dict[str, Any]] = None)`**:
|
||||||
* 封装单个验证点的结果。所有 `validate_*` 和 `check_*` 方法都应返回此对象的列表。
|
* 封装单个验证点的结果。所有 `validate_*` 和 `check_*` 方法都应返回此对象的列表。
|
||||||
* **`APIRequestContext`**: 包含当前请求的详细信息（方法、URL、参数、头、体、端点规范）。
|
* **`APIRequestContext`**: 包含当前请求的详细信息（方法、URL、参数、头、体、端点规范）。
|
||||||
* **`APIResponseContext`**: 包含 API 响应的详细信息（状态码、头、JSON 内容、文本内容、耗时、原始响应对象、关联的请求上下文）。
|
* **`APIResponseContext`**: 包含 API 响应的详细信息（状态码、头、JSON 内容、文本内容、耗时、原始响应对象、关联的请求上下文）。
|
||||||
|
|
||||||
### 4. 示例 (展示 `execution_order`)
|
### 4. 示例 (展示 `execution_order`)
|
||||||
|
|
||||||
@ -161,10 +162,10 @@ class EssentialHeaderCheck(BaseAPITestCase):
|
|||||||
|
|
||||||
### 5. 最佳实践
|
### 5. 最佳实践
|
||||||
|
|
||||||
* **单一职责**：让每个 `APITestCase` 专注于特定的验证目标。
|
* **单一职责**：让每个 `APITestCase` 专注于特定的验证目标。
|
||||||
* **清晰命名**：为类、ID、名称使用描述性文字。
|
* **清晰命名**：为类、ID、名称使用描述性文字。
|
||||||
* **善用 `endpoint_spec`**：参考 API 定义进行精确测试。
|
* **善用 `endpoint_spec`**：参考 API 定义进行精确测试。
|
||||||
* **详细的 `ValidationResult`**：失败时提供充足的上下文信息。
|
* **详细的 `ValidationResult`**：失败时提供充足的上下文信息。
|
||||||
* **日志记录**：使用 `self.logger` 记录测试过程中的重要信息和问题。
|
* **日志记录**：使用 `self.logger` 记录测试过程中的重要信息和问题。
|
||||||
|
|
||||||
希望这份更新的架构概览和编写指南对您有所帮助！通过 `execution_order`，您可以更好地控制复杂场景下测试用例的执行流程。
|
希望这份更新的架构概览和编写指南对您有所帮助！通过 `execution_order`，您可以更好地控制复杂场景下测试用例的执行流程。
|
||||||
430
assets/doc/井筒API示例_simple.json
Normal file
430
assets/doc/井筒API示例_simple.json
Normal file
@ -0,0 +1,430 @@
|
|||||||
|
[
|
||||||
|
{
|
||||||
|
"index": 0,
|
||||||
|
"name": "公共分类",
|
||||||
|
"desc": "公共分类",
|
||||||
|
"add_time": 1730355210,
|
||||||
|
"up_time": 1730355210,
|
||||||
|
"list": [
|
||||||
|
{
|
||||||
|
"query_path": {
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/message/push/{schema}/{version}",
|
||||||
|
"params": []
|
||||||
|
},
|
||||||
|
"edit_uid": 0,
|
||||||
|
"status": "undone",
|
||||||
|
"type": "var",
|
||||||
|
"req_body_is_json_schema": true,
|
||||||
|
"res_body_is_json_schema": true,
|
||||||
|
"api_opened": false,
|
||||||
|
"index": 0,
|
||||||
|
"tag": [],
|
||||||
|
"_id": 135716,
|
||||||
|
"method": "POST",
|
||||||
|
"title": "数据推送接口",
|
||||||
|
"desc": "",
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/message/push/{schema}/{version}",
|
||||||
|
"req_params": [
|
||||||
|
{
|
||||||
|
"_id": "67ff3dc5335acf6754926ab7",
|
||||||
|
"name": "dms_instance_code",
|
||||||
|
"desc": "注册实例code\n井筒中心 well_kd_wellbore_ideas01"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"_id": "67ff3dc5335acf0829926ab6",
|
||||||
|
"name": "schema",
|
||||||
|
"desc": ""
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"_id": "67ff3dc5335acf485f926ab5",
|
||||||
|
"name": "version",
|
||||||
|
"desc": ""
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_form": [],
|
||||||
|
"req_headers": [
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "67ff3dc5335acf11b4926aba",
|
||||||
|
"name": "Content-Type",
|
||||||
|
"value": "application/json"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "67ff3dc5335acfae3f926ab9",
|
||||||
|
"name": "tenant-id",
|
||||||
|
"desc": "tenant-id (Only:undefined)"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "67ff3dc5335acfad4f926ab8",
|
||||||
|
"name": "Authorization",
|
||||||
|
"desc": "Authorization (Only:undefined)"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_query": [],
|
||||||
|
"req_body_type": "json",
|
||||||
|
"res_body_type": "json",
|
||||||
|
"res_body": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"number\"},\"message\":{\"type\":\"string\"},\"data\":{\"type\":\"object\",\"properties\":{\"total\":{\"type\":\"number\"},\"list\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"dsid\":{\"type\":\"string\"},\"dataRegion\":{\"type\":\"string\"},\"gasReleaseMon\":{\"type\":\"null\"},\"gasReleaseYear\":{\"type\":\"null\"},\"releaseGasCum\":{\"type\":\"null\"}}}}}}}}",
|
||||||
|
"req_body_other": "{\"properties\":{\"isSearchCount\":{\"default\":true,\"description\":\"是否统计总条数\",\"type\":\"boolean\"},\"query\":{\"description\":\"查询条件\",\"properties\":{\"dataRegions\":{\"description\":\"数据域，如：JD、DG、TL\",\"items\":{\"description\":\"数据域，如：JD、DG、TL\",\"type\":\"string\"},\"type\":\"array\"},\"fields\":{\"description\":\"查询的字段\",\"items\":{\"description\":\"查询的字段\",\"type\":\"string\"},\"type\":\"array\"},\"filter\":{\"description\":\"筛选器\",\"properties\":{\"key\":{\"description\":\"条件项\",\"type\":\"string\"},\"logic\":{\"description\":\"逻辑操作符，可选值为：AND、OR\",\"type\":\"string\"},\"realValue\":{\"description\":\"条件值\",\"items\":{\"description\":\"条件值\",\"type\":\"object\",\"properties\":{}},\"type\":\"array\"},\"singleValue\":{\"type\":\"object\",\"writeOnly\":true,\"properties\":{}},\"subFilter\":{\"description\":\"子条件\",\"items\":{\"$ref\":\"#/components/schemas/FilterVO\",\"type\":\"string\"},\"type\":\"array\"},\"symbol\":{\"description\":\"运算符，可选值为：>、>=、<、<=、>、<、=、<>、!=、IN、NOTIN、LIKE、IS；当运算符为 IS 时，条件值只能为NULL或NOT NULL\",\"type\":\"string\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/FilterVO\"},\"groupFields\":{\"description\":\"分组字段group by\",\"items\":{\"description\":\"分组字段group by\",\"type\":\"string\"},\"type\":\"array\"},\"groupFilter\":{\"description\":\"筛选器\",\"properties\":{\"key\":{\"description\":\"条件项\",\"type\":\"string\"},\"logic\":{\"description\":\"逻辑操作符，可选值为：AND、OR\",\"type\":\"string\"},\"realValue\":{\"description\":\"条件值\",\"items\":{\"description\":\"条件值\",\"type\":\"object\",\"properties\":{}},\"type\":\"array\"},\"singleValue\":{\"type\":\"object\",\"writeOnly\":true,\"properties\":{}},\"subFilter\":{\"description\":\"子条件\",\"items\":{\"$ref\":\"#/components/schemas/FilterVO\",\"type\":\"string\"},\"type\":\"array\"},\"symbol\":{\"description\":\"运算符，可选值为：>、>=、<、<=、>、<、=、<>、!=、IN、NOTIN、LIKE、IS；当运算符为 IS 时，条件值只能为NULL或NOT NULL\",\"type\":\"string\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/FilterVO\"},\"sort\":{\"additionalProperties\":{\"description\":\"排序字段，key=字段名，value=排序方式（ASC、DESC）\",\"type\":\"string\"},\"description\":\"排序字段，key=字段名，value=排序方式（ASC、DESC）\",\"type\":\"object\",\"properties\":{}}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/QueryVO\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/RdbQueryPageInput\"}",
|
||||||
|
"project_id": 1193,
|
||||||
|
"catid": 17672,
|
||||||
|
"markdown": "",
|
||||||
|
"uid": 808,
|
||||||
|
"add_time": 1744780583,
|
||||||
|
"up_time": 1744780741,
|
||||||
|
"__v": 0
|
||||||
|
}
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"index": 0,
|
||||||
|
"name": "地质单元",
|
||||||
|
"desc": null,
|
||||||
|
"add_time": 1745736888,
|
||||||
|
"up_time": 1745736888,
|
||||||
|
"list": [
|
||||||
|
{
|
||||||
|
"query_path": {
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit/{version}",
|
||||||
|
"params": []
|
||||||
|
},
|
||||||
|
"edit_uid": 0,
|
||||||
|
"status": "undone",
|
||||||
|
"type": "var",
|
||||||
|
"req_body_is_json_schema": true,
|
||||||
|
"res_body_is_json_schema": true,
|
||||||
|
"api_opened": false,
|
||||||
|
"index": 0,
|
||||||
|
"tag": [],
|
||||||
|
"_id": 135751,
|
||||||
|
"method": "POST",
|
||||||
|
"title": "地质单元列表查询",
|
||||||
|
"desc": "",
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit/{version}",
|
||||||
|
"req_params": [
|
||||||
|
{
|
||||||
|
"_id": "680dd55a335acff12e926d18",
|
||||||
|
"name": "dms_instance_code",
|
||||||
|
"desc": "注册实例code\n井筒中心 well_kd_wellbore_ideas01"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"_id": "680dd55a335acfc43d926d17",
|
||||||
|
"name": "version",
|
||||||
|
"example": "1.0.0",
|
||||||
|
"desc": "交换模型版本"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_form": [],
|
||||||
|
"req_headers": [
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd55a335acfb51b926d1d",
|
||||||
|
"name": "Content-Type",
|
||||||
|
"value": "application/json"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd55a335acf6226926d1c",
|
||||||
|
"name": "tenant-id",
|
||||||
|
"desc": "tenant-id (Only:undefined)"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd55a335acf39a0926d1b",
|
||||||
|
"name": "Authorization",
|
||||||
|
"desc": "Authorization (Only:undefined)"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_query": [
|
||||||
|
{
|
||||||
|
"required": "0",
|
||||||
|
"_id": "680dd55a335acfabfa926d1a",
|
||||||
|
"name": "pageNo",
|
||||||
|
"desc": "页码(从1开始)"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "0",
|
||||||
|
"_id": "680dd55a335acf831b926d19",
|
||||||
|
"name": "pageSize",
|
||||||
|
"desc": "分页大小(最大值200)"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_type": "json",
|
||||||
|
"res_body_type": "json",
|
||||||
|
"res_body": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"number\"},\"message\":{\"type\":\"string\"},\"data\":{\"type\":\"object\",\"properties\":{\"total\":{\"type\":\"number\"},\"list\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"dsid\":{\"type\":\"string\"},\"dataRegion\":{\"type\":\"string\"},\"gasReleaseMon\":{\"type\":\"null\"},\"gasReleaseYear\":{\"type\":\"null\"},\"releaseGasCum\":{\"type\":\"null\"}}}}}}}}",
|
||||||
|
"req_body_other": "{\"properties\":{\"isSearchCount\":{\"default\":true,\"description\":\"是否统计总条数\",\"type\":\"boolean\"},\"query\":{\"description\":\"查询条件\",\"properties\":{\"dataRegions\":{\"description\":\"数据域，如：JD、DG、TL\",\"items\":{\"description\":\"数据域，如：JD、DG、TL\",\"type\":\"string\"},\"type\":\"array\"},\"fields\":{\"description\":\"查询的字段\",\"items\":{\"description\":\"查询的字段\",\"type\":\"string\"},\"type\":\"array\"},\"filter\":{\"description\":\"筛选器\",\"properties\":{\"key\":{\"description\":\"条件项\",\"type\":\"string\"},\"logic\":{\"description\":\"逻辑操作符，可选值为：AND、OR\",\"type\":\"string\"},\"realValue\":{\"description\":\"条件值\",\"items\":{\"description\":\"条件值\",\"type\":\"object\",\"properties\":{}},\"type\":\"array\"},\"singleValue\":{\"type\":\"object\",\"writeOnly\":true,\"properties\":{}},\"subFilter\":{\"description\":\"子条件\",\"items\":{\"$ref\":\"#/components/schemas/FilterVO\",\"type\":\"string\"},\"type\":\"array\"},\"symbol\":{\"description\":\"运算符，可选值为：>、>=、<、<=、>、<、=、<>、!=、IN、NOTIN、LIKE、IS；当运算符为 IS 时，条件值只能为NULL或NOT NULL\",\"type\":\"string\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/FilterVO\"},\"groupFields\":{\"description\":\"分组字段group by\",\"items\":{\"description\":\"分组字段group by\",\"type\":\"string\"},\"type\":\"array\"},\"groupFilter\":{\"description\":\"筛选器\",\"properties\":{\"key\":{\"description\":\"条件项\",\"type\":\"string\"},\"logic\":{\"description\":\"逻辑操作符，可选值为：AND、OR\",\"type\":\"string\"},\"realValue\":{\"description\":\"条件值\",\"items\":{\"description\":\"条件值\",\"type\":\"object\",\"properties\":{}},\"type\":\"array\"},\"singleValue\":{\"type\":\"object\",\"writeOnly\":true,\"properties\":{}},\"subFilter\":{\"description\":\"子条件\",\"items\":{\"$ref\":\"#/components/schemas/FilterVO\",\"type\":\"string\"},\"type\":\"array\"},\"symbol\":{\"description\":\"运算符，可选值为：>、>=、<、<=、>、<、=、<>、!=、IN、NOTIN、LIKE、IS；当运算符为 IS 时，条件值只能为NULL或NOT NULL\",\"type\":\"string\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/FilterVO\"},\"sort\":{\"additionalProperties\":{\"description\":\"排序字段，key=字段名，value=排序方式（ASC、DESC）\",\"type\":\"string\"},\"description\":\"排序字段，key=字段名，value=排序方式（ASC、DESC）\",\"type\":\"object\",\"properties\":{}}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/QueryVO\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/RdbQueryPageInput\"}",
|
||||||
|
"project_id": 1193,
|
||||||
|
"catid": 18705,
|
||||||
|
"markdown": "",
|
||||||
|
"uid": 1103,
|
||||||
|
"add_time": 1745736910,
|
||||||
|
"up_time": 1745737050,
|
||||||
|
"__v": 0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"query_path": {
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit",
|
||||||
|
"params": []
|
||||||
|
},
|
||||||
|
"edit_uid": 0,
|
||||||
|
"status": "undone",
|
||||||
|
"type": "var",
|
||||||
|
"req_body_is_json_schema": true,
|
||||||
|
"res_body_is_json_schema": true,
|
||||||
|
"api_opened": false,
|
||||||
|
"index": 0,
|
||||||
|
"tag": [],
|
||||||
|
"_id": 135749,
|
||||||
|
"method": "PUT",
|
||||||
|
"title": "地质单元数据修改",
|
||||||
|
"desc": "",
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit",
|
||||||
|
"req_params": [
|
||||||
|
{
|
||||||
|
"_id": "680dd510335acf19c3926cec",
|
||||||
|
"name": "dms_instance_code",
|
||||||
|
"desc": "注册实例code\n井筒中心 well_kd_wellbore_ideas01"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_form": [],
|
||||||
|
"req_headers": [
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd510335acf7bb3926cf0",
|
||||||
|
"name": "Content-Type",
|
||||||
|
"value": "application/json"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd510335acf6953926cef",
|
||||||
|
"name": "tenant-id",
|
||||||
|
"desc": "tenant-id (Only:undefined)"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd510335acfd86b926cee",
|
||||||
|
"name": "Authorization",
|
||||||
|
"desc": "Authorization (Only:undefined)"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_query": [
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd510335acf1ed1926ced",
|
||||||
|
"name": "id",
|
||||||
|
"example": "dsid",
|
||||||
|
"desc": "主键id的key"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_type": "json",
|
||||||
|
"res_body_type": "json",
|
||||||
|
"res_body": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"number\"},\"message\":{\"type\":\"string\"},\"data\":{\"type\":\"boolean\"}}}",
|
||||||
|
"req_body_other": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"version\":{\"type\":\"string\"},\"data\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"bsflag\":{\"type\":\"number\"},\"wellCommonName\":{\"type\":\"string\"},\"wellId\":{\"type\":\"string\"},\"dataRegion\":{\"type\":\"string\"}},\"required\":[\"bsflag\",\"wellCommonName\",\"wellId\",\"dataRegion\"]}}}}",
|
||||||
|
"project_id": 1193,
|
||||||
|
"catid": 18705,
|
||||||
|
"markdown": "",
|
||||||
|
"uid": 1103,
|
||||||
|
"add_time": 1745736907,
|
||||||
|
"up_time": 1745736976,
|
||||||
|
"__v": 0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"query_path": {
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit",
|
||||||
|
"params": []
|
||||||
|
},
|
||||||
|
"edit_uid": 0,
|
||||||
|
"status": "undone",
|
||||||
|
"type": "var",
|
||||||
|
"req_body_is_json_schema": true,
|
||||||
|
"res_body_is_json_schema": true,
|
||||||
|
"api_opened": false,
|
||||||
|
"index": 0,
|
||||||
|
"tag": [],
|
||||||
|
"_id": 135750,
|
||||||
|
"method": "DELETE",
|
||||||
|
"title": "地质单元数据删除",
|
||||||
|
"desc": "",
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit",
|
||||||
|
"req_params": [
|
||||||
|
{
|
||||||
|
"_id": "680dd51b335acfe93a926cf1",
|
||||||
|
"name": "dms_instance_code",
|
||||||
|
"desc": "注册实例code\n井筒中心 well_kd_wellbore_ideas01"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_form": [],
|
||||||
|
"req_headers": [
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd51b335acfb316926cf5",
|
||||||
|
"name": "Content-Type",
|
||||||
|
"value": "application/json"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd51b335acf45f4926cf4",
|
||||||
|
"name": "tenant-id",
|
||||||
|
"desc": "tenant-id (Only:undefined)"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd51b335acf0cfa926cf3",
|
||||||
|
"name": "Authorization",
|
||||||
|
"desc": "Authorization (Only:undefined)"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_query": [
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd51b335acf7441926cf2",
|
||||||
|
"name": "id",
|
||||||
|
"example": "dsid",
|
||||||
|
"desc": "主键id的key"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_type": "json",
|
||||||
|
"res_body_type": "json",
|
||||||
|
"res_body": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"number\"},\"message\":{\"type\":\"string\"},\"data\":{\"type\":\"boolean\"}}}",
|
||||||
|
"req_body_other": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"version\":{\"type\":\"string\",\"title\":\"版本号\"},\"data\":{\"type\":\"array\",\"items\":{\"type\":\"string\"},\"title\":\"主键id数据集\"}}}",
|
||||||
|
"project_id": 1193,
|
||||||
|
"catid": 18705,
|
||||||
|
"markdown": "",
|
||||||
|
"uid": 1103,
|
||||||
|
"add_time": 1745736908,
|
||||||
|
"up_time": 1745736987,
|
||||||
|
"__v": 0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"query_path": {
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit",
|
||||||
|
"params": []
|
||||||
|
},
|
||||||
|
"edit_uid": 0,
|
||||||
|
"status": "done",
|
||||||
|
"type": "var",
|
||||||
|
"req_body_is_json_schema": true,
|
||||||
|
"res_body_is_json_schema": true,
|
||||||
|
"api_opened": false,
|
||||||
|
"index": 0,
|
||||||
|
"tag": [],
|
||||||
|
"_id": 135748,
|
||||||
|
"method": "POST",
|
||||||
|
"title": "地质单元数据添加",
|
||||||
|
"desc": "",
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit",
|
||||||
|
"req_params": [
|
||||||
|
{
|
||||||
|
"_id": "680dd4ff335acf81b3926ce8",
|
||||||
|
"name": "dms_instance_code",
|
||||||
|
"desc": "注册实例code\n井筒中心 well_kd_wellbore_ideas01"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_form": [],
|
||||||
|
"req_headers": [
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd4ff335acfc5c7926ceb",
|
||||||
|
"name": "Content-Type",
|
||||||
|
"value": "application/json"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd4ff335acff16f926cea",
|
||||||
|
"name": "tenant-id",
|
||||||
|
"desc": "tenant-id (Only:undefined)"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd4ff335acf1a5c926ce9",
|
||||||
|
"name": "Authorization",
|
||||||
|
"desc": "Authorization (Only:undefined)"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_query": [],
|
||||||
|
"req_body_type": "json",
|
||||||
|
"res_body_type": "json",
|
||||||
|
"res_body": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"number\"},\"message\":{\"type\":\"string\"},\"data\":{\"type\":\"boolean\"}}}",
|
||||||
|
"req_body_other": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"version\":{\"type\":\"string\",\"title\":\"交换模型版本号\"},\"data\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"bsflag\":{\"type\":\"number\",\"title\":\"必填字段删除标记\"},\"wellCommonName\":{\"type\":\"string\"},\"wellId\":{\"type\":\"string\"},\"dataRegion\":{\"type\":\"string\"}},\"required\":[\"bsflag\",\"wellCommonName\",\"wellId\",\"dataRegion\"]},\"title\":\"交换模型数据集\"}}}",
|
||||||
|
"project_id": 1193,
|
||||||
|
"catid": 18705,
|
||||||
|
"markdown": "",
|
||||||
|
"uid": 1103,
|
||||||
|
"add_time": 1745736907,
|
||||||
|
"up_time": 1745736959,
|
||||||
|
"__v": 0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"query_path": {
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit/{version}/{id}",
|
||||||
|
"params": []
|
||||||
|
},
|
||||||
|
"edit_uid": 0,
|
||||||
|
"status": "done",
|
||||||
|
"type": "var",
|
||||||
|
"req_body_is_json_schema": true,
|
||||||
|
"res_body_is_json_schema": true,
|
||||||
|
"api_opened": false,
|
||||||
|
"index": 0,
|
||||||
|
"tag": [],
|
||||||
|
"_id": 135752,
|
||||||
|
"method": "GET",
|
||||||
|
"title": "地质单元查询详情",
|
||||||
|
"desc": "",
|
||||||
|
"path": "/api/dms/{dms_instance_code}/v1/cd_geo_unit/{version}/{id}",
|
||||||
|
"req_params": [
|
||||||
|
{
|
||||||
|
"_id": "680dd53d335acf42db926d05",
|
||||||
|
"name": "dms_instance_code",
|
||||||
|
"desc": "注册实例code\n井筒中心 well_kd_wellbore_ideas01"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"_id": "680dd53d335acf2105926d04",
|
||||||
|
"name": "version",
|
||||||
|
"example": "1.0.0",
|
||||||
|
"desc": "交换模型版本"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"_id": "680dd53d335acf7970926d03",
|
||||||
|
"name": "id",
|
||||||
|
"desc": ""
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_body_form": [],
|
||||||
|
"req_headers": [
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd53d335acf68e4926d08",
|
||||||
|
"name": "Content-Type",
|
||||||
|
"value": "application/json"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd53d335acf9fb4926d07",
|
||||||
|
"name": "tenant-id",
|
||||||
|
"desc": "tenant-id (Only:undefined)"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"required": "1",
|
||||||
|
"_id": "680dd53d335acf7a8d926d06",
|
||||||
|
"name": "Authorization",
|
||||||
|
"desc": "Authorization (Only:undefined)"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"req_query": [],
|
||||||
|
"req_body_type": "json",
|
||||||
|
"res_body_type": "json",
|
||||||
|
"res_body": "{\"$schema\":\"http://json-schema.org/draft-04/schema#\",\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"number\"},\"message\":{\"type\":\"string\"},\"data\":{\"type\":\"object\",\"properties\":{\"total\":{\"type\":\"number\"},\"list\":{\"type\":\"array\",\"items\":{\"type\":\"object\",\"properties\":{\"dsid\":{\"type\":\"string\"},\"dataRegion\":{\"type\":\"string\"},\"gasReleaseMon\":{\"type\":\"null\"},\"gasReleaseYear\":{\"type\":\"null\"},\"releaseGasCum\":{\"type\":\"null\"}}}}}}}}",
|
||||||
|
"req_body_other": "{\"properties\":{\"isSearchCount\":{\"default\":true,\"description\":\"是否统计总条数\",\"type\":\"boolean\"},\"query\":{\"description\":\"查询条件\",\"properties\":{\"dataRegions\":{\"description\":\"数据域，如：JD、DG、TL\",\"items\":{\"description\":\"数据域，如：JD、DG、TL\",\"type\":\"string\"},\"type\":\"array\"},\"fields\":{\"description\":\"查询的字段\",\"items\":{\"description\":\"查询的字段\",\"type\":\"string\"},\"type\":\"array\"},\"filter\":{\"description\":\"筛选器\",\"properties\":{\"key\":{\"description\":\"条件项\",\"type\":\"string\"},\"logic\":{\"description\":\"逻辑操作符，可选值为：AND、OR\",\"type\":\"string\"},\"realValue\":{\"description\":\"条件值\",\"items\":{\"description\":\"条件值\",\"type\":\"object\",\"properties\":{}},\"type\":\"array\"},\"singleValue\":{\"type\":\"object\",\"writeOnly\":true,\"properties\":{}},\"subFilter\":{\"description\":\"子条件\",\"items\":{\"$ref\":\"#/components/schemas/FilterVO\",\"type\":\"string\"},\"type\":\"array\"},\"symbol\":{\"description\":\"运算符，可选值为：>、>=、<、<=、>、<、=、<>、!=、IN、NOTIN、LIKE、IS；当运算符为 IS 时，条件值只能为NULL或NOT NULL\",\"type\":\"string\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/FilterVO\"},\"groupFields\":{\"description\":\"分组字段group by\",\"items\":{\"description\":\"分组字段group by\",\"type\":\"string\"},\"type\":\"array\"},\"groupFilter\":{\"description\":\"筛选器\",\"properties\":{\"key\":{\"description\":\"条件项\",\"type\":\"string\"},\"logic\":{\"description\":\"逻辑操作符，可选值为：AND、OR\",\"type\":\"string\"},\"realValue\":{\"description\":\"条件值\",\"items\":{\"description\":\"条件值\",\"type\":\"object\",\"properties\":{}},\"type\":\"array\"},\"singleValue\":{\"type\":\"object\",\"writeOnly\":true,\"properties\":{}},\"subFilter\":{\"description\":\"子条件\",\"items\":{\"$ref\":\"#/components/schemas/FilterVO\",\"type\":\"string\"},\"type\":\"array\"},\"symbol\":{\"description\":\"运算符，可选值为：>、>=、<、<=、>、<、=、<>、!=、IN、NOTIN、LIKE、IS；当运算符为 IS 时，条件值只能为NULL或NOT NULL\",\"type\":\"string\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/FilterVO\"},\"sort\":{\"additionalProperties\":{\"description\":\"排序字段，key=字段名，value=排序方式（ASC、DESC）\",\"type\":\"string\"},\"description\":\"排序字段，key=字段名，value=排序方式（ASC、DESC）\",\"type\":\"object\",\"properties\":{}}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/QueryVO\"}},\"type\":\"object\",\"$$ref\":\"#/components/schemas/RdbQueryPageInput\"}",
|
||||||
|
"project_id": 1193,
|
||||||
|
"catid": 18705,
|
||||||
|
"markdown": "",
|
||||||
|
"uid": 1103,
|
||||||
|
"add_time": 1745736911,
|
||||||
|
"up_time": 1745737021,
|
||||||
|
"__v": 0
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
]
|
||||||
BIN
assets/images/dms1/.DS_Store
vendored
BIN
assets/images/dms1/.DS_Store
vendored
Binary file not shown.
Binary file not shown.
@ -13,13 +13,13 @@ class StatusCode200Check(BaseAPITestCase):
|
|||||||
# applicable_methods = None
|
# applicable_methods = None
|
||||||
# applicable_paths_regex = None
|
# applicable_paths_regex = None
|
||||||
execution_order = 10 # 示例执行顺序
|
execution_order = 10 # 示例执行顺序
|
||||||
use_llm_for_body: bool = True
|
# use_llm_for_body: bool = True
|
||||||
use_llm_for_path_params: bool = True
|
# use_llm_for_path_params: bool = True
|
||||||
use_llm_for_query_params: bool = True
|
# use_llm_for_query_params: bool = True
|
||||||
use_llm_for_headers: bool = True
|
# use_llm_for_headers: bool = True
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||||
super().__init__(endpoint_spec, global_api_spec, json_schema_validator=json_schema_validator)
|
super().__init__(endpoint_spec, global_api_spec, json_schema_validator=json_schema_validator, llm_service=llm_service)
|
||||||
self.logger.info(f"测试用例 {self.id} ({self.name}) 已针对端点 '{self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')}' 初始化。")
|
self.logger.info(f"测试用例 {self.id} ({self.name}) 已针对端点 '{self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')}' 初始化。")
|
||||||
|
|
||||||
def validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> list[ValidationResult]:
|
def validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> list[ValidationResult]:
|
||||||
@ -50,42 +50,3 @@ class StatusCode200Check(BaseAPITestCase):
|
|||||||
)
|
)
|
||||||
self.logger.warning(f"状态码验证失败: 期望 {expected_status_code}, 实际 {actual_status_code} for {request_context.url}")
|
self.logger.warning(f"状态码验证失败: 期望 {expected_status_code}, 实际 {actual_status_code} for {request_context.url}")
|
||||||
return results
|
return results
|
||||||
|
|
||||||
class HeaderExistenceCheck(BaseAPITestCase):
|
|
||||||
id = "TC-HEADER-001"
|
|
||||||
name = "检查响应中是否存在 'X-Request-ID' 头"
|
|
||||||
description = "验证 API 响应是否包含 'X-Request-ID' 头。"
|
|
||||||
severity = TestSeverity.MEDIUM
|
|
||||||
tags = ["header", "observability"]
|
|
||||||
execution_order = 10 # 示例执行顺序
|
|
||||||
use_llm_for_body = False
|
|
||||||
|
|
||||||
EXPECTED_HEADER = "X-Request-ID" # 示例，可以根据实际需要修改
|
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
|
||||||
super().__init__(endpoint_spec, global_api_spec, json_schema_validator=json_schema_validator)
|
|
||||||
self.logger.info(f"测试用例 {self.id} ({self.name}) 已初始化 for endpoint {self.endpoint_spec.get('path')}")
|
|
||||||
|
|
||||||
def validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> list[ValidationResult]:
|
|
||||||
results = []
|
|
||||||
if self.EXPECTED_HEADER in response_context.headers:
|
|
||||||
results.append(
|
|
||||||
ValidationResult(
|
|
||||||
passed=True,
|
|
||||||
message=f"响应头中找到了期望的 '{self.EXPECTED_HEADER}'。"
|
|
||||||
)
|
|
||||||
)
|
|
||||||
self.logger.info(f"请求头 '{self.EXPECTED_HEADER}' 存在于 {request_context.url} 的响应中。")
|
|
||||||
else:
|
|
||||||
results.append(
|
|
||||||
ValidationResult(
|
|
||||||
passed=False,
|
|
||||||
message=f"响应头中未找到期望的 '{self.EXPECTED_HEADER}'。",
|
|
||||||
details={
|
|
||||||
"expected_header": self.EXPECTED_HEADER,
|
|
||||||
"actual_headers": list(response_context.headers.keys())
|
|
||||||
}
|
|
||||||
)
|
|
||||||
)
|
|
||||||
self.logger.warning(f"请求头 '{self.EXPECTED_HEADER}' 未在 {request_context.url} 的响应中找到。")
|
|
||||||
return results
|
|
||||||
Binary file not shown.
@ -13,8 +13,8 @@ class ResponseSchemaValidationCase(BaseAPITestCase):
|
|||||||
# This test is generally applicable, especially for GET requests or successful POST/PUT.
|
# This test is generally applicable, especially for GET requests or successful POST/PUT.
|
||||||
# It might need refinement based on specific endpoint characteristics (e.g., no response body for DELETE)
|
# It might need refinement based on specific endpoint characteristics (e.g., no response body for DELETE)
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||||
super().__init__(endpoint_spec, global_api_spec, json_schema_validator)
|
super().__init__(endpoint_spec, global_api_spec, json_schema_validator, llm_service=llm_service)
|
||||||
self.logger.info(f"测试用例 '{self.id}' 已为端点 '{self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')}' 初始化。")
|
self.logger.info(f"测试用例 '{self.id}' 已为端点 '{self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')}' 初始化。")
|
||||||
|
|
||||||
def validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> List[ValidationResult]:
|
def validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> List[ValidationResult]:
|
||||||
|
|||||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
@ -11,68 +11,19 @@ class MissingRequiredFieldBodyCase(BaseAPITestCase):
|
|||||||
tags = ["error-handling", "appendix-b", "4003", "required-fields", "request-body"]
|
tags = ["error-handling", "appendix-b", "4003", "required-fields", "request-body"]
|
||||||
execution_order = 210 # Before query, same as original combined
|
execution_order = 210 # Before query, same as original combined
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||||
super().__init__(endpoint_spec, global_api_spec, json_schema_validator)
|
super().__init__(endpoint_spec, global_api_spec, json_schema_validator, llm_service=llm_service)
|
||||||
self.logger.setLevel(logging.DEBUG) # Ensure detailed logging for this class
|
self.logger = logging.getLogger(f"testcase.{self.id}")
|
||||||
|
self.target_field_path: Optional[List[str]] = None
|
||||||
|
self.original_value_at_path: Any = None
|
||||||
self.removed_field_path: Optional[List[str]] = None # Path to the removed field, e.g., ['level1', 'level2_field']
|
self.removed_field_path: Optional[List[str]] = None # Path to the removed field, e.g., ['level1', 'level2_field']
|
||||||
self.original_body_schema: Optional[Dict[str, Any]] = None
|
self.original_body_schema: Optional[Dict[str, Any]] = None
|
||||||
self._try_find_removable_body_field()
|
self._try_find_removable_body_field()
|
||||||
|
|
||||||
def _resolve_ref_if_present(self, schema_to_resolve: Dict[str, Any]) -> Dict[str, Any]:
|
def _resolve_ref_if_present(self, schema_to_resolve: Dict[str, Any]) -> Dict[str, Any]:
|
||||||
ref_value = None
|
# 根据用户进一步要求，方法体简化为直接返回，不进行任何 $ref/$ $$ref 的检查。
|
||||||
if isinstance(schema_to_resolve, dict):
|
# self.logger.debug(f"_resolve_ref_if_present called. Returning schema as-is per new configuration.")
|
||||||
if "$ref" in schema_to_resolve:
|
return schema_to_resolve
|
||||||
ref_value = schema_to_resolve["$ref"]
|
|
||||||
elif "$$ref" in schema_to_resolve:
|
|
||||||
ref_value = schema_to_resolve["$$ref"]
|
|
||||||
|
|
||||||
if ref_value:
|
|
||||||
self.logger.debug(f"发现引用 '{ref_value}'，尝试解析...")
|
|
||||||
try:
|
|
||||||
actual_global_spec_dict = None
|
|
||||||
if hasattr(self.global_api_spec, 'spec') and isinstance(self.global_api_spec.spec, dict):
|
|
||||||
actual_global_spec_dict = self.global_api_spec.spec
|
|
||||||
elif isinstance(self.global_api_spec, dict):
|
|
||||||
actual_global_spec_dict = self.global_api_spec
|
|
||||||
|
|
||||||
if not actual_global_spec_dict:
|
|
||||||
self.logger.warning(f"无法从 self.global_api_spec (类型: {type(self.global_api_spec)}) 获取用于解析引用的字典。")
|
|
||||||
return schema_to_resolve
|
|
||||||
|
|
||||||
resolved_schema = None
|
|
||||||
if ref_value.startswith("#/components/schemas/"):
|
|
||||||
schema_name = ref_value.split("/")[-1]
|
|
||||||
components = actual_global_spec_dict.get("components")
|
|
||||||
if components and isinstance(components.get("schemas"), dict):
|
|
||||||
resolved_schema = components["schemas"].get(schema_name)
|
|
||||||
if resolved_schema and isinstance(resolved_schema, dict):
|
|
||||||
self.logger.info(f"成功从 #/components/schemas/ 解析引用 '{ref_value}'。")
|
|
||||||
return resolved_schema
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"解析引用 '{ref_value}' (路径: #/components/schemas/) 失败：未找到或找到的不是字典: {schema_name}")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"尝试从 #/components/schemas/ 解析引用 '{ref_value}' 失败：无法找到 'components.schemas' 结构。")
|
|
||||||
|
|
||||||
# 如果从 #/components/schemas/ 未成功解析，尝试 #/definitions/
|
|
||||||
if not resolved_schema and ref_value.startswith("#/definitions/"):
|
|
||||||
schema_name = ref_value.split("/")[-1]
|
|
||||||
definitions = actual_global_spec_dict.get("definitions")
|
|
||||||
if definitions and isinstance(definitions, dict):
|
|
||||||
resolved_schema = definitions.get(schema_name)
|
|
||||||
if resolved_schema and isinstance(resolved_schema, dict):
|
|
||||||
self.logger.info(f"成功从 #/definitions/ 解析引用 '{ref_value}'。")
|
|
||||||
return resolved_schema
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"解析引用 '{ref_value}' (路径: #/definitions/) 失败：未找到或找到的不是字典: {schema_name}")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"尝试从 #/definitions/ 解析引用 '{ref_value}' 失败：无法找到 'definitions' 结构。")
|
|
||||||
|
|
||||||
if not resolved_schema:
|
|
||||||
self.logger.warning(f"最终未能通过任一已知路径 (#/components/schemas/ 或 #/definitions/) 解析引用 '{ref_value}'。")
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
self.logger.error(f"解析引用 '{ref_value}' 时发生错误: {e}", exc_info=True)
|
|
||||||
return schema_to_resolve # 返回原始 schema 如果不是 ref 或者所有解析尝试都失败
|
|
||||||
|
|
||||||
def _find_required_field_in_schema_recursive(self, current_schema: Dict[str, Any], current_path: List[str]) -> Optional[List[str]]:
|
def _find_required_field_in_schema_recursive(self, current_schema: Dict[str, Any], current_path: List[str]) -> Optional[List[str]]:
|
||||||
"""递归查找第一个可移除的必填字段的路径。
|
"""递归查找第一个可移除的必填字段的路径。
|
||||||
|
|||||||
@ -10,10 +10,11 @@ class MissingRequiredFieldQueryCase(BaseAPITestCase):
|
|||||||
tags = ["error-handling", "appendix-b", "4003", "required-fields", "query-parameters"]
|
tags = ["error-handling", "appendix-b", "4003", "required-fields", "query-parameters"]
|
||||||
execution_order = 211 # After body, before original combined one might have been
|
execution_order = 211 # After body, before original combined one might have been
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||||
super().__init__(endpoint_spec, global_api_spec, json_schema_validator)
|
super().__init__(endpoint_spec, global_api_spec, json_schema_validator=json_schema_validator, llm_service=llm_service)
|
||||||
self.removed_field_name: Optional[str] = None
|
self.target_param_name: Optional[str] = None
|
||||||
self._try_find_removable_query_param()
|
self._try_find_removable_query_param()
|
||||||
|
self.logger.info(f"测试用例 {self.id} ({self.name}) 已针对端点 '{self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')}' 初始化。Target param to remove: {self.target_param_name}")
|
||||||
|
|
||||||
def _try_find_removable_query_param(self):
|
def _try_find_removable_query_param(self):
|
||||||
query_params_spec_list = self.endpoint_spec.get("parameters", [])
|
query_params_spec_list = self.endpoint_spec.get("parameters", [])
|
||||||
@ -23,8 +24,8 @@ class MissingRequiredFieldQueryCase(BaseAPITestCase):
|
|||||||
if isinstance(param_spec, dict) and param_spec.get("in") == "query" and param_spec.get("required") is True:
|
if isinstance(param_spec, dict) and param_spec.get("in") == "query" and param_spec.get("required") is True:
|
||||||
field_name = param_spec.get("name")
|
field_name = param_spec.get("name")
|
||||||
if field_name:
|
if field_name:
|
||||||
self.removed_field_name = field_name
|
self.target_param_name = field_name
|
||||||
self.logger.info(f"必填字段缺失测试的目标字段 (查询参数): '{self.removed_field_name}'")
|
self.logger.info(f"必填字段缺失测试的目标字段 (查询参数): '{self.target_param_name}'")
|
||||||
return
|
return
|
||||||
self.logger.info('在此端点规范中未找到可用于测试 "必填查询参数缺失" 的字段。')
|
self.logger.info('在此端点规范中未找到可用于测试 "必填查询参数缺失" 的字段。')
|
||||||
|
|
||||||
@ -34,20 +35,20 @@ class MissingRequiredFieldQueryCase(BaseAPITestCase):
|
|||||||
return current_body
|
return current_body
|
||||||
|
|
||||||
def generate_query_params(self, current_query_params: Dict[str, Any]) -> Dict[str, Any]:
|
def generate_query_params(self, current_query_params: Dict[str, Any]) -> Dict[str, Any]:
|
||||||
if self.removed_field_name and isinstance(current_query_params, dict):
|
if self.target_param_name and isinstance(current_query_params, dict):
|
||||||
if self.removed_field_name in current_query_params:
|
if self.target_param_name in current_query_params:
|
||||||
new_params = copy.deepcopy(current_query_params)
|
new_params = copy.deepcopy(current_query_params)
|
||||||
original_value = new_params.pop(self.removed_field_name) # 移除参数
|
original_value = new_params.pop(self.target_param_name) # 移除参数
|
||||||
self.logger.info(f"为进行必填查询参数缺失测试，已从查询参数中移除 '{self.removed_field_name}' (原值: '{original_value}')。")
|
self.logger.info(f"为进行必填查询参数缺失测试，已从查询参数中移除 '{self.target_param_name}' (原值: '{original_value}')。")
|
||||||
return new_params
|
return new_params
|
||||||
else:
|
else:
|
||||||
self.logger.warning(f"计划移除的查询参数 '{self.removed_field_name}' 在当前查询参数中未找到。")
|
self.logger.warning(f"计划移除的查询参数 '{self.target_param_name}' 在当前查询参数中未找到。")
|
||||||
return current_query_params
|
return current_query_params
|
||||||
|
|
||||||
def validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> List[ValidationResult]:
|
def validate_response(self, response_context: APIResponseContext, request_context: APIRequestContext) -> List[ValidationResult]:
|
||||||
results = []
|
results = []
|
||||||
|
|
||||||
if not self.removed_field_name:
|
if not self.target_param_name:
|
||||||
results.append(self.passed("跳过测试：在API规范中未找到合适的必填查询参数用于移除测试。"))
|
results.append(self.passed("跳过测试：在API规范中未找到合适的必填查询参数用于移除测试。"))
|
||||||
self.logger.info("由于未识别到可移除的必填查询参数，跳过此测试用例。")
|
self.logger.info("由于未识别到可移除的必填查询参数，跳过此测试用例。")
|
||||||
return results
|
return results
|
||||||
@ -58,7 +59,7 @@ class MissingRequiredFieldQueryCase(BaseAPITestCase):
|
|||||||
expected_status_codes = [400, 422]
|
expected_status_codes = [400, 422]
|
||||||
specific_error_code_from_appendix_b = "4003"
|
specific_error_code_from_appendix_b = "4003"
|
||||||
|
|
||||||
msg_prefix = f"当移除必填查询参数 '{self.removed_field_name}' 时，"
|
msg_prefix = f"当移除必填查询参数 '{self.target_param_name}' 时，"
|
||||||
|
|
||||||
if status_code in expected_status_codes:
|
if status_code in expected_status_codes:
|
||||||
status_msg = f"{msg_prefix}API响应了预期的错误状态码 {status_code}。"
|
status_msg = f"{msg_prefix}API响应了预期的错误状态码 {status_code}。"
|
||||||
@ -77,8 +78,8 @@ class MissingRequiredFieldQueryCase(BaseAPITestCase):
|
|||||||
else:
|
else:
|
||||||
results.append(self.failed(
|
results.append(self.failed(
|
||||||
message=f"{msg_prefix}期望API返回状态码 {expected_status_codes} 中的一个，但实际收到 {status_code}。",
|
message=f"{msg_prefix}期望API返回状态码 {expected_status_codes} 中的一个，但实际收到 {status_code}。",
|
||||||
details={"status_code": status_code, "response_body": json_content, "removed_field": f"query.{self.removed_field_name}"}
|
details={"status_code": status_code, "response_body": json_content, "removed_field": f"query.{self.target_param_name}"}
|
||||||
))
|
))
|
||||||
self.logger.warning(f"必填查询参数缺失测试失败：期望状态码 {expected_status_codes}，实际为 {status_code}。移除的参数：'{self.removed_field_name}'")
|
self.logger.warning(f"必填查询参数缺失测试失败：期望状态码 {expected_status_codes}，实际为 {status_code}。移除的参数：'{self.target_param_name}'")
|
||||||
|
|
||||||
return results
|
return results
|
||||||
@ -11,15 +11,20 @@ class TypeMismatchBodyCase(BaseAPITestCase):
|
|||||||
tags = ["error-handling", "appendix-b", "4001", "request-body"]
|
tags = ["error-handling", "appendix-b", "4001", "request-body"]
|
||||||
execution_order = 202 # Slightly after query param one
|
execution_order = 202 # Slightly after query param one
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||||
super().__init__(endpoint_spec, global_api_spec, json_schema_validator)
|
super().__init__(endpoint_spec, global_api_spec, json_schema_validator, llm_service=llm_service)
|
||||||
self.logger.setLevel(logging.DEBUG)
|
self.logger.setLevel(logging.DEBUG)
|
||||||
self.target_field_path: Optional[List[str]] = None
|
self.target_field_path: Optional[List[str]] = None
|
||||||
self.original_field_type: Optional[str] = None
|
self.original_field_type: Optional[str] = None
|
||||||
# Location is always 'body' for this class
|
# Location is always 'body' for this class
|
||||||
self.target_field_location: str = "body"
|
self.target_field_location: str = "body"
|
||||||
self.target_field_schema: Optional[Dict[str, Any]] = None
|
self.target_field_schema: Optional[Dict[str, Any]] = None
|
||||||
|
self.json_schema_validator = json_schema_validator
|
||||||
|
self.original_value_at_path: Any = None
|
||||||
|
self.mismatched_value: Any = None
|
||||||
|
self._try_find_mismatch_target_in_body()
|
||||||
|
|
||||||
|
def _try_find_mismatch_target_in_body(self):
|
||||||
self.logger.critical(f"{self.id} __INIT__ >>> STARTED")
|
self.logger.critical(f"{self.id} __INIT__ >>> STARTED")
|
||||||
self.logger.debug(f"开始为端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 初始化请求体类型不匹配测试的目标字段查找。")
|
self.logger.debug(f"开始为端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 初始化请求体类型不匹配测试的目标字段查找。")
|
||||||
|
|
||||||
@ -64,58 +69,8 @@ class TypeMismatchBodyCase(BaseAPITestCase):
|
|||||||
self.logger.info(f"最终，在端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 的请求体中，均未找到可用于测试类型不匹配的字段。")
|
self.logger.info(f"最终，在端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 的请求体中，均未找到可用于测试类型不匹配的字段。")
|
||||||
|
|
||||||
def _resolve_ref_if_present(self, schema_to_resolve: Dict[str, Any]) -> Dict[str, Any]:
|
def _resolve_ref_if_present(self, schema_to_resolve: Dict[str, Any]) -> Dict[str, Any]:
|
||||||
ref_value = None
|
# 根据用户进一步要求，方法体简化为直接返回，不进行任何 $ref/$ $$ref 的检查。
|
||||||
if isinstance(schema_to_resolve, dict):
|
# self.logger.debug(f"_resolve_ref_if_present called. Returning schema as-is per new configuration.")
|
||||||
if "$ref" in schema_to_resolve:
|
|
||||||
ref_value = schema_to_resolve["$ref"]
|
|
||||||
elif "$$ref" in schema_to_resolve:
|
|
||||||
ref_value = schema_to_resolve["$$ref"]
|
|
||||||
|
|
||||||
if ref_value:
|
|
||||||
self.logger.debug(f"发现引用 '{ref_value}'，尝试解析...")
|
|
||||||
try:
|
|
||||||
actual_global_spec_dict = None
|
|
||||||
if hasattr(self.global_api_spec, 'spec') and isinstance(self.global_api_spec.spec, dict):
|
|
||||||
actual_global_spec_dict = self.global_api_spec.spec
|
|
||||||
elif isinstance(self.global_api_spec, dict):
|
|
||||||
actual_global_spec_dict = self.global_api_spec
|
|
||||||
|
|
||||||
if not actual_global_spec_dict:
|
|
||||||
self.logger.warning(f"无法从 self.global_api_spec (类型: {type(self.global_api_spec)}) 获取用于解析引用的字典。")
|
|
||||||
return schema_to_resolve
|
|
||||||
|
|
||||||
resolved_schema = None
|
|
||||||
if ref_value.startswith("#/components/schemas/"):
|
|
||||||
schema_name = ref_value.split("/")[-1]
|
|
||||||
components = actual_global_spec_dict.get("components")
|
|
||||||
if components and isinstance(components.get("schemas"), dict):
|
|
||||||
resolved_schema = components["schemas"].get(schema_name)
|
|
||||||
if resolved_schema and isinstance(resolved_schema, dict):
|
|
||||||
self.logger.info(f"成功从 #/components/schemas/ 解析引用 '{ref_value}'。")
|
|
||||||
return resolved_schema
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"解析引用 '{ref_value}' (路径: #/components/schemas/) 失败：未找到或找到的不是字典: {schema_name}")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"尝试从 #/components/schemas/ 解析引用 '{ref_value}' 失败：无法找到 'components.schemas' 结构。")
|
|
||||||
|
|
||||||
if not resolved_schema and ref_value.startswith("#/definitions/"):
|
|
||||||
schema_name = ref_value.split("/")[-1]
|
|
||||||
definitions = actual_global_spec_dict.get("definitions")
|
|
||||||
if definitions and isinstance(definitions, dict):
|
|
||||||
resolved_schema = definitions.get(schema_name)
|
|
||||||
if resolved_schema and isinstance(resolved_schema, dict):
|
|
||||||
self.logger.info(f"成功从 #/definitions/ 解析引用 '{ref_value}'。")
|
|
||||||
return resolved_schema
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"解析引用 '{ref_value}' (路径: #/definitions/) 失败：未找到或找到的不是字典: {schema_name}")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"尝试从 #/definitions/ 解析引用 '{ref_value}' 失败：无法找到 'definitions' 结构。")
|
|
||||||
|
|
||||||
if not resolved_schema:
|
|
||||||
self.logger.warning(f"最终未能通过任一已知路径 (#/components/schemas/ 或 #/definitions/) 解析引用 '{ref_value}'。")
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
self.logger.error(f"解析引用 '{ref_value}' 时发生错误: {e}", exc_info=True)
|
|
||||||
return schema_to_resolve
|
return schema_to_resolve
|
||||||
|
|
||||||
def _find_target_field_in_schema(self, schema_to_search: Dict[str, Any], base_path_for_log: str) -> bool:
|
def _find_target_field_in_schema(self, schema_to_search: Dict[str, Any], base_path_for_log: str) -> bool:
|
||||||
|
|||||||
@ -11,14 +11,19 @@ class TypeMismatchQueryParamCase(BaseAPITestCase):
|
|||||||
tags = ["error-handling", "appendix-b", "4001", "query-parameters"]
|
tags = ["error-handling", "appendix-b", "4001", "query-parameters"]
|
||||||
execution_order = 201 # Slightly after the combined one might have been
|
execution_order = 201 # Slightly after the combined one might have been
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||||
super().__init__(endpoint_spec, global_api_spec, json_schema_validator)
|
super().__init__(endpoint_spec, global_api_spec, json_schema_validator, llm_service=llm_service)
|
||||||
self.logger.setLevel(logging.DEBUG)
|
self.logger.setLevel(logging.DEBUG)
|
||||||
self.target_field_path: Optional[List[str]] = None
|
self.target_field_path: Optional[List[str]] = None
|
||||||
self.original_field_type: Optional[str] = None
|
self.original_field_type: Optional[str] = None
|
||||||
# Location is always 'query' for this class
|
# Location is always 'query' for this class
|
||||||
self.target_field_location: str = "query"
|
self.target_field_location: str = "query"
|
||||||
self.target_field_schema: Optional[Dict[str, Any]] = None
|
self.target_field_schema: Optional[Dict[str, Any]] = None
|
||||||
|
self.original_value_at_path: Any = None
|
||||||
|
self.mismatched_value: Any = None
|
||||||
|
|
||||||
|
# 调用新方法来查找目标字段
|
||||||
|
self._try_find_mismatch_target_in_query()
|
||||||
|
|
||||||
self.logger.critical(f"{self.id} __INIT__ >>> STARTED")
|
self.logger.critical(f"{self.id} __INIT__ >>> STARTED")
|
||||||
self.logger.debug(f"开始为端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 初始化查询参数类型不匹配测试的目标字段查找。")
|
self.logger.debug(f"开始为端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 初始化查询参数类型不匹配测试的目标字段查找。")
|
||||||
@ -78,59 +83,63 @@ class TypeMismatchQueryParamCase(BaseAPITestCase):
|
|||||||
if not self.target_field_path:
|
if not self.target_field_path:
|
||||||
self.logger.info(f"最终，在端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 的查询参数中，均未找到可用于测试类型不匹配的字段。")
|
self.logger.info(f"最终，在端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 的查询参数中，均未找到可用于测试类型不匹配的字段。")
|
||||||
|
|
||||||
|
def _try_find_mismatch_target_in_query(self):
|
||||||
|
self.logger.critical(f"{self.id} _try_find_mismatch_target_in_query >>> STARTED")
|
||||||
|
self.logger.debug(f"开始为端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 初始化查询参数类型不匹配测试的目标字段查找。")
|
||||||
|
|
||||||
|
parameters = self.endpoint_spec.get("parameters", [])
|
||||||
|
self.logger.critical(f"{self.id} _try_find_mismatch_target_in_query >>> Parameters to be processed: {parameters}")
|
||||||
|
self.logger.debug(f"传入的参数列表 (在 {self.id}中): {parameters}")
|
||||||
|
|
||||||
|
for param_spec in parameters:
|
||||||
|
if param_spec.get("in") == "query":
|
||||||
|
param_name = param_spec.get("name")
|
||||||
|
if not param_name:
|
||||||
|
self.logger.warning("发现一个没有名称的查询参数定义，已跳过。")
|
||||||
|
continue
|
||||||
|
|
||||||
|
self.logger.debug(f"检查查询参数: '{param_name}'")
|
||||||
|
|
||||||
|
param_type = param_spec.get("type")
|
||||||
|
param_schema = param_spec.get("schema")
|
||||||
|
|
||||||
|
# Scenario 1: Simple type directly in param_spec (e.g., type: string)
|
||||||
|
if param_type in ["string", "number", "integer", "boolean"]:
|
||||||
|
self.target_field_path = [param_name]
|
||||||
|
self.original_field_type = param_type
|
||||||
|
self.target_field_schema = param_spec
|
||||||
|
self.logger.info(f"目标字段(查询参数 - 简单类型): {param_name}，原始类型: {self.original_field_type}")
|
||||||
|
break
|
||||||
|
# Scenario 2: Schema defined for the query parameter (OpenAPI 3.0 style, or complex objects in query)
|
||||||
|
elif isinstance(param_schema, dict):
|
||||||
|
self.logger.debug(f"查询参数 '{param_name}' 包含嵌套 schema，尝试在其内部查找简单类型字段。")
|
||||||
|
resolved_param_schema = self._resolve_ref_if_present(param_schema)
|
||||||
|
if resolved_param_schema.get("type") == "object":
|
||||||
|
properties = resolved_param_schema.get("properties", {})
|
||||||
|
for prop_name, prop_details_orig in properties.items():
|
||||||
|
prop_details = self._resolve_ref_if_present(prop_details_orig)
|
||||||
|
if prop_details.get("type") in ["string", "number", "integer", "boolean"]:
|
||||||
|
self.target_field_path = [param_name, prop_name]
|
||||||
|
self.original_field_type = prop_details.get("type")
|
||||||
|
self.target_field_schema = prop_details
|
||||||
|
self.logger.info(f"目标字段(查询参数 - 对象属性): {param_name}.{prop_name}，原始类型: {self.original_field_type}")
|
||||||
|
break
|
||||||
|
if self.target_field_path: break
|
||||||
|
elif resolved_param_schema.get("type") in ["string", "number", "integer", "boolean"]:
|
||||||
|
self.target_field_path = [param_name]
|
||||||
|
self.original_field_type = resolved_param_schema.get("type")
|
||||||
|
self.target_field_schema = resolved_param_schema
|
||||||
|
self.logger.info(f"目标字段(查询参数 - schema为简单类型): {param_name}，原始类型: {self.original_field_type}")
|
||||||
|
break
|
||||||
|
else:
|
||||||
|
self.logger.debug(f"查询参数 '{param_name}' (type: {param_type}, schema: {param_schema}) 不是直接的简单类型，也无直接可用的对象型 schema 属性。")
|
||||||
|
|
||||||
|
if not self.target_field_path:
|
||||||
|
self.logger.info(f"最终，在端点 {self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')} 的查询参数中，均未找到可用于测试类型不匹配的字段。")
|
||||||
|
|
||||||
def _resolve_ref_if_present(self, schema_to_resolve: Dict[str, Any]) -> Dict[str, Any]:
|
def _resolve_ref_if_present(self, schema_to_resolve: Dict[str, Any]) -> Dict[str, Any]:
|
||||||
ref_value = None
|
# 根据用户进一步要求，方法体简化为直接返回，不进行任何 $ref/$ $$ref 的检查。
|
||||||
if isinstance(schema_to_resolve, dict):
|
# self.logger.debug(f"_resolve_ref_if_present called. Returning schema as-is per new configuration.")
|
||||||
if "$ref" in schema_to_resolve:
|
|
||||||
ref_value = schema_to_resolve["$ref"]
|
|
||||||
elif "$$ref" in schema_to_resolve:
|
|
||||||
ref_value = schema_to_resolve["$$ref"]
|
|
||||||
|
|
||||||
if ref_value:
|
|
||||||
self.logger.debug(f"发现引用 '{ref_value}'，尝试解析...")
|
|
||||||
try:
|
|
||||||
actual_global_spec_dict = None
|
|
||||||
if hasattr(self.global_api_spec, 'spec') and isinstance(self.global_api_spec.spec, dict):
|
|
||||||
actual_global_spec_dict = self.global_api_spec.spec
|
|
||||||
elif isinstance(self.global_api_spec, dict):
|
|
||||||
actual_global_spec_dict = self.global_api_spec
|
|
||||||
|
|
||||||
if not actual_global_spec_dict:
|
|
||||||
self.logger.warning(f"无法从 self.global_api_spec (类型: {type(self.global_api_spec)}) 获取用于解析引用的字典。")
|
|
||||||
return schema_to_resolve
|
|
||||||
|
|
||||||
resolved_schema = None
|
|
||||||
if ref_value.startswith("#/components/schemas/"):
|
|
||||||
schema_name = ref_value.split("/")[-1]
|
|
||||||
components = actual_global_spec_dict.get("components")
|
|
||||||
if components and isinstance(components.get("schemas"), dict):
|
|
||||||
resolved_schema = components["schemas"].get(schema_name)
|
|
||||||
if resolved_schema and isinstance(resolved_schema, dict):
|
|
||||||
self.logger.info(f"成功从 #/components/schemas/ 解析引用 '{ref_value}'。")
|
|
||||||
return resolved_schema
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"解析引用 '{ref_value}' (路径: #/components/schemas/) 失败：未找到或找到的不是字典: {schema_name}")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"尝试从 #/components/schemas/ 解析引用 '{ref_value}' 失败：无法找到 'components.schemas' 结构。")
|
|
||||||
|
|
||||||
if not resolved_schema and ref_value.startswith("#/definitions/"):
|
|
||||||
schema_name = ref_value.split("/")[-1]
|
|
||||||
definitions = actual_global_spec_dict.get("definitions")
|
|
||||||
if definitions and isinstance(definitions, dict):
|
|
||||||
resolved_schema = definitions.get(schema_name)
|
|
||||||
if resolved_schema and isinstance(resolved_schema, dict):
|
|
||||||
self.logger.info(f"成功从 #/definitions/ 解析引用 '{ref_value}'。")
|
|
||||||
return resolved_schema
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"解析引用 '{ref_value}' (路径: #/definitions/) 失败：未找到或找到的不是字典: {schema_name}")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"尝试从 #/definitions/ 解析引用 '{ref_value}' 失败：无法找到 'definitions' 结构。")
|
|
||||||
|
|
||||||
if not resolved_schema:
|
|
||||||
self.logger.warning(f"最终未能通过任一已知路径 (#/components/schemas/ 或 #/definitions/) 解析引用 '{ref_value}'。")
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
self.logger.error(f"解析引用 '{ref_value}' 时发生错误: {e}", exc_info=True)
|
|
||||||
return schema_to_resolve
|
return schema_to_resolve
|
||||||
|
|
||||||
# No generate_request_body, or it simply returns current_body
|
# No generate_request_body, or it simply returns current_body
|
||||||
|
|||||||
Binary file not shown.
@ -0,0 +1,247 @@
|
|||||||
|
import re
|
||||||
|
import json # 确保导入json
|
||||||
|
from typing import Dict, Any, Optional, List
|
||||||
|
from ddms_compliance_suite.test_framework_core import BaseAPITestCase, TestSeverity, ValidationResult, APIRequestContext
|
||||||
|
# LLMService的导入路径需要根据您的项目结构确认
|
||||||
|
# 假设 LLMService 在 ddms_compliance_suite.llm_utils.llm_service
|
||||||
|
try:
|
||||||
|
from ddms_compliance_suite.llm_utils.llm_service import LLMService
|
||||||
|
except ImportError:
|
||||||
|
LLMService = None
|
||||||
|
# print("LLMService not found, PathVerbNounCheckCase will be skipped or limited.")
|
||||||
|
|
||||||
|
class ComprehensiveURLCheckLLMCase(BaseAPITestCase):
|
||||||
|
id = "TC-NORMATIVE-URL-LLM-COMPREHENSIVE-001"
|
||||||
|
name = "综合URL规范与RESTful风格检查 (LLM)"
|
||||||
|
description = (
|
||||||
|
"使用LLM统一评估API路径是否符合以下规范：\n"
|
||||||
|
"1. 路径参数命名 (例如，全小写蛇形命名法)。\n"
|
||||||
|
"2. URL路径结构 (例如，/{领域}/{版本号}/资源类型)。\n"
|
||||||
|
"3. URL版本号嵌入 (例如，包含 /v1/)。\n"
|
||||||
|
"4. RESTful风格与可读性 (名词表示资源，HTTP方法表示动作，易理解性)。"
|
||||||
|
)
|
||||||
|
severity = TestSeverity.MEDIUM # 综合性检查，可能包含不同严重级别的问题
|
||||||
|
tags = ["normative-spec", "url", "restful", "llm", "readability", "naming-convention", "structure", "versioning", "static-check"]
|
||||||
|
execution_order = 60 # 更新执行顺序
|
||||||
|
|
||||||
|
# 此测试用例可以覆盖所有路径，但其有效性依赖LLM
|
||||||
|
# applicable_methods = None
|
||||||
|
# applicable_paths_regex = None
|
||||||
|
|
||||||
|
# 这个标志可以用来在测试用例级别控制是否实际调用LLM，即使全局LLM服务可用
|
||||||
|
# 如果您希望总是尝试（只要LLMService能初始化），可以不设置这个，或者在逻辑中检查 self.llm_service 是否存在
|
||||||
|
# use_llm_for_path_analysis: bool = True
|
||||||
|
|
||||||
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[LLMService] = None):
|
||||||
|
super().__init__(endpoint_spec, global_api_spec, json_schema_validator)
|
||||||
|
self.llm_service = llm_service # 存储注入的 LLMService 实例
|
||||||
|
if not self.llm_service:
|
||||||
|
self.logger.warning(f"LLMService 未注入或初始化失败，测试用例 {self.id} 将无法执行LLM路径分析。")
|
||||||
|
|
||||||
|
def _get_llm_service_from_orchestrator(self) -> Optional[Any]:
|
||||||
|
# 在实际框架中，测试用例可能无法直接访问编排器来获取LLM服务。
|
||||||
|
# 这种依赖注入通常在测试用例实例化时或方法调用时处理。
|
||||||
|
# 此处为一个占位符，理想情况下APITestOrchestrator会将llm_service实例传给需要它的测试用例，
|
||||||
|
# 或测试用例通过某种服务定位器获取。
|
||||||
|
# 暂时我们假设，如果全局配置了LLM，它就能用。
|
||||||
|
# 真实的实现需要APITestOrchestrator在执行此测试用例前，将llm_service实例注入。
|
||||||
|
# 为了能运行，我们先返回None，并在下面逻辑中处理。
|
||||||
|
# 或者，修改 Orchestrator 将其注入到 self.global_api_spec 或 self.endpoint_spec (不推荐)
|
||||||
|
# 最好的方式是在 __init__ 中接收一个 llm_service: Optional[LLMService] 参数。
|
||||||
|
# 但这需要修改 BaseAPITestCase 和 APITestOrchestrator 的 __init__ 和调用逻辑。
|
||||||
|
|
||||||
|
# 临时的解决方法：依赖 APITestOrchestrator 初始化时是否成功创建了 LLMService。
|
||||||
|
# 这仍然是一个间接的检查。一个更直接的方式是在Orchestrator执行此测试用例时传入。
|
||||||
|
if hasattr(self, '_orchestrator_llm_service_instance') and self._orchestrator_llm_service_instance:
|
||||||
|
return self._orchestrator_llm_service_instance
|
||||||
|
|
||||||
|
# 如果没有明确注入，我们只能依赖全局LLMService是否被加载
|
||||||
|
if LLMService is not None:
|
||||||
|
# 这里不能直接实例化一个新的LLMService，因为它需要API Key等配置，这些配置在Orchestrator那里。
|
||||||
|
# 这个测试用例需要依赖Orchestrator来提供一个已经配置好的LLMService实例。
|
||||||
|
# 此处返回一个指示：如果LLM功能应该被使用，则需要Orchestrator提供服务。
|
||||||
|
return "NEEDS_INJECTION"
|
||||||
|
return None
|
||||||
|
|
||||||
|
def _extract_path_param_names(self, path_template: str) -> List[str]:
|
||||||
|
"""从路径模板中提取路径参数名称。例如 /users/{user_id}/items/{item_id} -> ['user_id', 'item_id']"""
|
||||||
|
return re.findall(r'\{([^}]+)\}', path_template)
|
||||||
|
|
||||||
|
def validate_request_url(self, url: str, request_context: APIRequestContext) -> List[ValidationResult]:
|
||||||
|
results: List[ValidationResult] = []
|
||||||
|
path_template = self.endpoint_spec.get('path', '')
|
||||||
|
http_method = request_context.method.upper()
|
||||||
|
operation_id = self.endpoint_spec.get('operationId', self.endpoint_spec.get('title', '')) # 获取operationId或title
|
||||||
|
|
||||||
|
if not self.llm_service:
|
||||||
|
results.append(ValidationResult(
|
||||||
|
passed=True, # 标记为通过以避免阻塞，但消息表明跳过
|
||||||
|
message=f"路径 '{path_template}' 的LLM综合URL检查已跳过：LLM服务不可用。",
|
||||||
|
details={"path_template": path_template, "http_method": http_method, "reason": "LLM Service not available or not injected."}
|
||||||
|
))
|
||||||
|
self.logger.warning(f"LLM综合URL检查已跳过对路径 '{path_template}' 的检查：LLM服务不可用。")
|
||||||
|
return results
|
||||||
|
|
||||||
|
path_param_names = self._extract_path_param_names(path_template)
|
||||||
|
path_params_str = ", ".join(path_param_names) if path_param_names else "无"
|
||||||
|
|
||||||
|
# - 接口名称 (OperationId 或 Title): {operation_id if operation_id else '请你自己从路径模板中提取'}
|
||||||
|
|
||||||
|
# 构建给LLM的Prompt，要求JSON输出
|
||||||
|
prompt_instruction = f"""
|
||||||
|
请扮演一位资深的API设计评审员。我将提供一个API端点的路径模板、HTTP方法以及可能的接口名称。
|
||||||
|
请根据以下石油行业API设计规范评估此API端点，并以严格的JSON格式返回您的评估结果。
|
||||||
|
JSON对象应包含一个名为 "assessments" 的键，其值为一个对象列表，每个对象代表对一个标准的评估，包含 "standard_name" (字符串), "is_compliant" (布尔值), 和 "reason" (字符串) 三个键。
|
||||||
|
|
||||||
|
API端点信息:
|
||||||
|
- HTTP方法: {http_method}
|
||||||
|
- 路径模板: {path_template}
|
||||||
|
- 路径中提取的参数名: [{path_params_str}]
|
||||||
|
|
||||||
|
评估标准:
|
||||||
|
|
||||||
|
1. **接口名称规范 (接口名称需要你从路径模板中提取，一般是路径中除了参数名以外的最后的一个单词)**:
|
||||||
|
- 规则: 采用'动词+名词'结构，明确业务语义 (例如: GetWellLog, SubmitSeismicJob)。
|
||||||
|
- standard_name: "interface_naming_convention"
|
||||||
|
|
||||||
|
2. **HTTP方法使用规范**:
|
||||||
|
- 规则: 遵循RESTful规范：GET用于数据检索, POST用于创建资源, PUT用于更新资源, DELETE用于删除资源。
|
||||||
|
- standard_name: "http_method_usage"
|
||||||
|
|
||||||
|
3. **URL路径结构规范**:
|
||||||
|
- 规则: 格式为 `<前缀>/<专业领域>/v<版本号>/<资源类型>` (例如: /logging/v1.2/wells, /seismicprospecting/v1.0/datasets)。
|
||||||
|
- 前缀: 示例: /api/dms
|
||||||
|
- 专业领域: 专业领域示例: seismicprospecting, welllogging, reservoirevaluation
|
||||||
|
- 版本号: 语义化版本，例如 v1, v1.0, v2.1.3。
|
||||||
|
- 资源类型: 通常为名词复数。
|
||||||
|
- standard_name: "url_path_structure"
|
||||||
|
|
||||||
|
4. **URL路径参数命名规范**:
|
||||||
|
- 规则: 路径参数（如果存在）必须使用全小写字母(可以是一个单词）或小写字母加下划线命名（这是多个单词的情况），并能反映资源的唯一标识 (例如: {{well_id}},{{version}},{{schema}})。
|
||||||
|
- standard_name: "url_path_parameter_naming"
|
||||||
|
|
||||||
|
5. **资源命名规范 (在路径中)**:
|
||||||
|
- 规则: 资源集合应使用名词的复数形式表示 (例如 `/wells`, `/logs`)；应优先使用石油行业的标准术语 (例如用 `trajectory` 而非 `path` 来表示井轨迹)。
|
||||||
|
- standard_name: "resource_naming_in_path"
|
||||||
|
- standard_name: "resource"
|
||||||
|
- standard_name: "schema"
|
||||||
|
- standard_name: "version"
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
请确保您的输出是一个可以被 `json.loads()` 直接解析的JSON对象。
|
||||||
|
例如:
|
||||||
|
{{
|
||||||
|
"assessments": [
|
||||||
|
{{
|
||||||
|
"standard_name": "interface_naming_convention",
|
||||||
|
"is_compliant": true,
|
||||||
|
"reason": "接口名称 'GetWellboreTrajectory' 符合动词+名词结构。"
|
||||||
|
}},
|
||||||
|
{{
|
||||||
|
"standard_name": "http_method_usage",
|
||||||
|
"is_compliant": true,
|
||||||
|
"reason": "GET方法用于检索资源，符合规范。"
|
||||||
|
}}
|
||||||
|
// ... 其他标准的评估 ...
|
||||||
|
]
|
||||||
|
}}
|
||||||
|
"""
|
||||||
|
|
||||||
|
# 6. **路径可读性与整体RESTful风格**:
|
||||||
|
# - 规则: 路径整体是否具有良好的可读性、易于理解其功能，并且符合RESTful设计原则？（综合评估，可参考前面几点）
|
||||||
|
# - standard_name: "general_readability_and_restfulness"
|
||||||
|
|
||||||
|
messages = [
|
||||||
|
{"role": "system", "content": "你是一位API设计评审专家，专注于评估API的URL规范性和RESTful风格。你的输出必须是严格的JSON格式。"},
|
||||||
|
{"role": "user", "content": prompt_instruction}
|
||||||
|
]
|
||||||
|
|
||||||
|
self.logger.info(f"向LLM发送请求，评估路径: {path_template} ({http_method})")
|
||||||
|
# 假设 _execute_chat_completion_request 支持 response_format={"type": "json_object"} (如果LLM API支持)
|
||||||
|
# 否则，我们需要解析文本输出。为简化，这里假设LLM会遵循JSON格式指令。
|
||||||
|
llm_response_str = self.llm_service._execute_chat_completion_request(
|
||||||
|
messages=messages,
|
||||||
|
max_tokens=1024, # 根据评估结果的复杂度调整
|
||||||
|
temperature=0.2 # 低温以获得更确定的、结构化的输出
|
||||||
|
)
|
||||||
|
|
||||||
|
if not llm_response_str:
|
||||||
|
results.append(ValidationResult(
|
||||||
|
passed=False, # 执行失败
|
||||||
|
message=f"未能从LLM获取对路径 '{path_template}' 的评估。",
|
||||||
|
details={"path_template": path_template, "http_method": http_method, "reason": "LLM did not return a response."}
|
||||||
|
))
|
||||||
|
self.logger.error(f"LLM对路径 '{path_template}' 的评估请求未返回任何内容。")
|
||||||
|
return results
|
||||||
|
|
||||||
|
self.logger.debug(f"LLM对路径 '{path_template}' 的原始响应: {llm_response_str}")
|
||||||
|
|
||||||
|
try:
|
||||||
|
# 尝试清理并解析LLM响应
|
||||||
|
# 有时LLM可能在JSON前后添加 "```json" 和 "```"
|
||||||
|
cleaned_response_str = llm_response_str.strip()
|
||||||
|
if cleaned_response_str.startswith("```json"):
|
||||||
|
cleaned_response_str = cleaned_response_str[7:]
|
||||||
|
if cleaned_response_str.endswith("```"):
|
||||||
|
cleaned_response_str = cleaned_response_str[:-3]
|
||||||
|
|
||||||
|
llm_assessment_data = json.loads(cleaned_response_str)
|
||||||
|
|
||||||
|
if "assessments" not in llm_assessment_data or not isinstance(llm_assessment_data["assessments"], list):
|
||||||
|
raise ValueError("LLM响应JSON中缺少 'assessments' 列表或格式不正确。")
|
||||||
|
|
||||||
|
found_assessments = False
|
||||||
|
for assessment in llm_assessment_data["assessments"]:
|
||||||
|
standard_name = assessment.get("standard_name", "未知标准")
|
||||||
|
is_compliant = assessment.get("is_compliant", False)
|
||||||
|
reason = assessment.get("reason", "LLM未提供原因。")
|
||||||
|
found_assessments = True
|
||||||
|
|
||||||
|
results.append(ValidationResult(
|
||||||
|
passed=is_compliant,
|
||||||
|
message=f"LLM评估 - {standard_name}: {reason}",
|
||||||
|
details={
|
||||||
|
"standard_name": standard_name,
|
||||||
|
"is_compliant_by_llm": is_compliant,
|
||||||
|
"llm_reason": reason,
|
||||||
|
"path_template": path_template,
|
||||||
|
"http_method": http_method
|
||||||
|
}
|
||||||
|
))
|
||||||
|
log_level = self.logger.info if is_compliant else self.logger.warning
|
||||||
|
log_level(f"LLM评估 - 标准 '{standard_name}' for '{path_template}': {'符合' if is_compliant else '不符合'}。原因: {reason}")
|
||||||
|
|
||||||
|
if not found_assessments:
|
||||||
|
results.append(ValidationResult(
|
||||||
|
passed=False,
|
||||||
|
message=f"LLM返回的评估结果中不包含任何有效的评估项。",
|
||||||
|
details={"path_template": path_template, "http_method": http_method, "raw_llm_response": llm_response_str}
|
||||||
|
))
|
||||||
|
|
||||||
|
|
||||||
|
except json.JSONDecodeError as e_json:
|
||||||
|
results.append(ValidationResult(
|
||||||
|
passed=False, # 执行失败
|
||||||
|
message=f"无法将LLM对路径 '{path_template}' 的评估响应解析为JSON: {e_json}",
|
||||||
|
details={"path_template": path_template, "http_method": http_method, "raw_llm_response": llm_response_str, "error": str(e_json)}
|
||||||
|
))
|
||||||
|
self.logger.error(f"LLM对路径 '{path_template}' 的响应JSON解析失败: {e_json}. Raw response: {llm_response_str}")
|
||||||
|
except ValueError as e_val: # 自定义错误，如缺少 'assessments'
|
||||||
|
results.append(ValidationResult(
|
||||||
|
passed=False, # 执行失败
|
||||||
|
message=f"LLM对路径 '{path_template}' 的评估响应JSON结构不符合预期: {e_val}",
|
||||||
|
details={"path_template": path_template, "http_method": http_method, "raw_llm_response": llm_response_str, "error": str(e_val)}
|
||||||
|
))
|
||||||
|
self.logger.error(f"LLM对路径 '{path_template}' 的响应JSON结构错误: {e_val}. Raw response: {llm_response_str}")
|
||||||
|
except Exception as e_generic:
|
||||||
|
results.append(ValidationResult(
|
||||||
|
passed=False, # 执行失败
|
||||||
|
message=f"处理LLM对路径 '{path_template}' 的评估响应时发生未知错误: {e_generic}",
|
||||||
|
details={"path_template": path_template, "http_method": http_method, "raw_llm_response": llm_response_str, "error": str(e_generic)}
|
||||||
|
))
|
||||||
|
self.logger.error(f"处理LLM对路径 '{path_template}' 的响应时发生未知错误: {e_generic}", exc_info=True)
|
||||||
|
|
||||||
|
return results
|
||||||
|
|
||||||
|
|
||||||
Binary file not shown.
@ -12,8 +12,8 @@ class HTTPSMandatoryCase(BaseAPITestCase):
|
|||||||
|
|
||||||
# 此测试会修改URL为HTTP，应适用于大多数端点。
|
# 此测试会修改URL为HTTP，应适用于大多数端点。
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||||
super().__init__(endpoint_spec, global_api_spec, json_schema_validator)
|
super().__init__(endpoint_spec, global_api_spec, json_schema_validator, llm_service=llm_service)
|
||||||
self.logger.info(f"测试用例 '{self.id}' 已为端点 '{self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')}' 初始化。")
|
self.logger.info(f"测试用例 '{self.id}' 已为端点 '{self.endpoint_spec.get('method')} {self.endpoint_spec.get('path')}' 初始化。")
|
||||||
|
|
||||||
def modify_request_url(self, current_url: str) -> str:
|
def modify_request_url(self, current_url: str) -> str:
|
||||||
|
|||||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
@ -1,355 +1,481 @@
|
|||||||
"""Input Parser Module"""
|
|
||||||
|
|
||||||
import json
|
import json
|
||||||
import os
|
|
||||||
from typing import Any, Dict, Optional, List, Union
|
|
||||||
from pydantic import BaseModel # For defining the structure of parsed inputs
|
|
||||||
from dataclasses import dataclass, field
|
|
||||||
import logging
|
import logging
|
||||||
|
from typing import List, Dict, Any, Optional, Union # Ensure Union is imported
|
||||||
|
|
||||||
logger = logging.getLogger("InputParser")
|
logger = logging.getLogger(__name__)
|
||||||
|
|
||||||
class ParsedOpenAPISpec(BaseModel):
|
class BaseEndpoint:
|
||||||
# Placeholder for OpenAPI spec details relevant to the compliance suite
|
"""所有端点对象的基类，可以包含一些通用属性或方法。"""
|
||||||
spec: Dict[str, Any]
|
def __init__(self, method: str, path: str):
|
||||||
info: Dict[str, Any] # Swagger 'info' object with title, version, etc.
|
self.method = method
|
||||||
paths: Dict[str, Dict[str, Any]] # API paths and their operations
|
self.path = path
|
||||||
tags: Optional[List[Dict[str, str]]] = None # API tags
|
|
||||||
basePath: Optional[str] = None # Base path for all APIs
|
|
||||||
swagger_version: str # Swagger specification version
|
|
||||||
|
|
||||||
@dataclass
|
def to_dict(self) -> Dict[str, Any]:
|
||||||
class YAPIEndpoint:
|
# 基类可以提供一个默认的 to_dict 实现或要求子类实现
|
||||||
"""YAPI API端点信息"""
|
raise NotImplementedError("Subclasses must implement to_dict")
|
||||||
path: str
|
|
||||||
method: str
|
|
||||||
title: str = ""
|
|
||||||
description: str = ""
|
|
||||||
category_name: str = ""
|
|
||||||
req_params: List[Dict[str, Any]] = field(default_factory=list)
|
|
||||||
req_query: List[Dict[str, Any]] = field(default_factory=list)
|
|
||||||
req_headers: List[Dict[str, Any]] = field(default_factory=list)
|
|
||||||
req_body_type: str = ""
|
|
||||||
req_body_other: str = ""
|
|
||||||
res_body_type: str = ""
|
|
||||||
res_body: str = ""
|
|
||||||
|
|
||||||
@dataclass
|
class YAPIEndpoint(BaseEndpoint): # Inherit from BaseEndpoint
|
||||||
class ParsedYAPISpec:
|
def __init__(self, data: Dict[str, Any], category_name: Optional[str] = None, category_id: Optional[int] = None):
|
||||||
|
super().__init__(method=data.get("method", "GET").upper(), path=data.get("path", ""))
|
||||||
|
self._raw_data = data
|
||||||
|
self.title: str = data.get("title", "")
|
||||||
|
self.desc: Optional[str] = data.get("desc")
|
||||||
|
self._id: int = data.get("_id")
|
||||||
|
self.project_id: int = data.get("project_id")
|
||||||
|
self.catid: int = data.get("catid")
|
||||||
|
|
||||||
|
self.req_params: List[Dict[str, Any]] = data.get("req_params", [])
|
||||||
|
self.req_query: List[Dict[str, Any]] = data.get("req_query", [])
|
||||||
|
self.req_headers: List[Dict[str, Any]] = data.get("req_headers", [])
|
||||||
|
self.req_body_form: List[Dict[str, Any]] = data.get("req_body_form", [])
|
||||||
|
|
||||||
|
self.req_body_type: Optional[str] = data.get("req_body_type")
|
||||||
|
self.req_body_is_json_schema: bool = data.get("req_body_is_json_schema", False)
|
||||||
|
self.req_body_other: Optional[str] = data.get("req_body_other")
|
||||||
|
|
||||||
|
self.res_body_type: Optional[str] = data.get("res_body_type")
|
||||||
|
self.res_body_is_json_schema: bool = data.get("res_body_is_json_schema", False)
|
||||||
|
self.res_body: Optional[str] = data.get("res_body")
|
||||||
|
|
||||||
|
self.status: str = data.get("status", "undone")
|
||||||
|
self.api_opened: bool = data.get("api_opened", False)
|
||||||
|
self.uid: int = data.get("uid")
|
||||||
|
|
||||||
|
self.category_name = category_name
|
||||||
|
self.category_id = category_id if category_id is not None else self.catid
|
||||||
|
|
||||||
|
self._parsed_req_body_schema: Optional[Dict[str, Any]] = None
|
||||||
|
if self.req_body_type == "json" and self.req_body_other and self.req_body_is_json_schema:
|
||||||
|
try:
|
||||||
|
self._parsed_req_body_schema = json.loads(self.req_body_other)
|
||||||
|
except json.JSONDecodeError as e:
|
||||||
|
logger.error(f"YAPIEndpoint (ID: {self._id}, Title: {self.title}): Failed to parse req_body_other as JSON during init: {e}. Content: {self.req_body_other[:200]}")
|
||||||
|
|
||||||
|
self._parsed_res_body_schema: Optional[Dict[str, Any]] = None
|
||||||
|
if self.res_body_type == "json" and self.res_body and self.res_body_is_json_schema:
|
||||||
|
try:
|
||||||
|
self._parsed_res_body_schema = json.loads(self.res_body)
|
||||||
|
except json.JSONDecodeError as e:
|
||||||
|
logger.error(f"YAPIEndpoint (ID: {self._id}, Title: {self.title}): Failed to parse res_body as JSON during init: {e}. Content: {self.res_body[:200]}")
|
||||||
|
|
||||||
|
def to_dict(self) -> Dict[str, Any]:
|
||||||
|
endpoint_dict = {
|
||||||
|
"method": self.method,
|
||||||
|
"path": self.path,
|
||||||
|
"title": self.title,
|
||||||
|
"summary": self.title,
|
||||||
|
"description": self.desc or "",
|
||||||
|
"operationId": f"{self.method.lower()}_{self.path.replace('/', '_').replace('{', '').replace('}', '')}_{self._id}",
|
||||||
|
"tags": [self.category_name or str(self.catid)],
|
||||||
|
"parameters": [],
|
||||||
|
"requestBody": None,
|
||||||
|
"responses": {},
|
||||||
|
"_source_format": "yapi",
|
||||||
|
"_yapi_id": self._id,
|
||||||
|
"_yapi_raw_data": self._raw_data # Keep raw data for debugging or deeper inspection if needed
|
||||||
|
}
|
||||||
|
|
||||||
|
# Path parameters from req_params
|
||||||
|
for p_spec in self.req_params:
|
||||||
|
param_name = p_spec.get("name")
|
||||||
|
if not param_name: continue
|
||||||
|
endpoint_dict["parameters"].append({
|
||||||
|
"name": param_name,
|
||||||
|
"in": "path",
|
||||||
|
"required": True, # Path parameters are always required
|
||||||
|
"description": p_spec.get("desc", ""),
|
||||||
|
"schema": {"type": "string", "example": p_spec.get("example", f"example_{param_name}")}
|
||||||
|
})
|
||||||
|
|
||||||
|
# Query parameters from req_query
|
||||||
|
for q_spec in self.req_query:
|
||||||
|
param_name = q_spec.get("name")
|
||||||
|
if not param_name: continue
|
||||||
|
is_required = q_spec.get("required") == "1" # YAPI uses "1" for true
|
||||||
|
param_schema = {"type": "string"} # Default to string, YAPI doesn't specify types well here
|
||||||
|
if "example" in q_spec: param_schema["example"] = q_spec["example"]
|
||||||
|
# Add other fields from YAPI query spec if needed (e.g., desc)
|
||||||
|
endpoint_dict["parameters"].append({
|
||||||
|
"name": param_name,
|
||||||
|
"in": "query",
|
||||||
|
"required": is_required,
|
||||||
|
"description": q_spec.get("desc", ""),
|
||||||
|
"schema": param_schema
|
||||||
|
})
|
||||||
|
|
||||||
|
# Header parameters from req_headers
|
||||||
|
for h_spec in self.req_headers:
|
||||||
|
param_name = h_spec.get("name")
|
||||||
|
if not param_name or param_name.lower() == 'content-type': continue # Content-Type is handled by requestBody
|
||||||
|
is_required = h_spec.get("required") == "1"
|
||||||
|
default_value = h_spec.get("value") # YAPI uses 'value' for default/example header value
|
||||||
|
param_schema = {"type": "string"}
|
||||||
|
if default_value:
|
||||||
|
if is_required: # If required, it's more like an example of what's expected
|
||||||
|
param_schema["example"] = default_value
|
||||||
|
else: # If not required, it's a default value
|
||||||
|
param_schema["default"] = default_value
|
||||||
|
|
||||||
|
endpoint_dict["parameters"].append({
|
||||||
|
"name": param_name,
|
||||||
|
"in": "header",
|
||||||
|
"required": is_required,
|
||||||
|
"description": h_spec.get("desc", ""),
|
||||||
|
"schema": param_schema
|
||||||
|
})
|
||||||
|
|
||||||
|
# Request body
|
||||||
|
if self.req_body_type == "json" and self._parsed_req_body_schema:
|
||||||
|
endpoint_dict["requestBody"] = {
|
||||||
|
"content": {
|
||||||
|
"application/json": {
|
||||||
|
"schema": self._parsed_req_body_schema
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
elif self.req_body_type == "form" and self.req_body_form:
|
||||||
|
properties = {}
|
||||||
|
required_form_params = []
|
||||||
|
for form_param in self.req_body_form:
|
||||||
|
name = form_param.get("name")
|
||||||
|
if not name: continue
|
||||||
|
properties[name] = {
|
||||||
|
"type": "string", # YAPI form params are typically strings, file uploads are different
|
||||||
|
"description": form_param.get("desc","")
|
||||||
|
}
|
||||||
|
if form_param.get("example"): properties[name]["example"] = form_param.get("example")
|
||||||
|
if form_param.get("required") == "1": required_form_params.append(name)
|
||||||
|
|
||||||
|
endpoint_dict["requestBody"] = {
|
||||||
|
"content": {
|
||||||
|
"application/x-www-form-urlencoded": {
|
||||||
|
"schema": {
|
||||||
|
"type": "object",
|
||||||
|
"properties": properties,
|
||||||
|
"required": required_form_params if required_form_params else None # OpenAPI: omit if empty
|
||||||
|
}
|
||||||
|
}
|
||||||
|
# YAPI also supports req_body_type = 'file', which would map to multipart/form-data
|
||||||
|
# This example focuses on json and basic form.
|
||||||
|
}
|
||||||
|
}
|
||||||
|
# Add other req_body_types if necessary (e.g., raw, file)
|
||||||
|
|
||||||
|
# Responses
|
||||||
|
# YAPI has a simpler response structure. We'll map its res_body to a default success response (e.g., 200 or 201).
|
||||||
|
default_success_status = "200"
|
||||||
|
if self.method == "POST": default_success_status = "201" # Common practice for POST success
|
||||||
|
|
||||||
|
if self.res_body_type == "json" and self._parsed_res_body_schema:
|
||||||
|
endpoint_dict["responses"][default_success_status] = {
|
||||||
|
"description": "Successful Operation (from YAPI res_body)",
|
||||||
|
"content": {
|
||||||
|
"application/json": {
|
||||||
|
"schema": self._parsed_res_body_schema
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
elif self.res_body_type == "json" and not self._parsed_res_body_schema and self.res_body: # Schema parsing failed but text exists
|
||||||
|
endpoint_dict["responses"][default_success_status] = {
|
||||||
|
"description": "Successful Operation (Schema parsing error, raw text might be available)",
|
||||||
|
"content": {"application/json": {"schema": {"type": "object", "description": "Schema parsing failed for YAPI res_body."}}} # Placeholder
|
||||||
|
}
|
||||||
|
else: # No JSON schema, or other res_body_type
|
||||||
|
endpoint_dict["responses"][default_success_status] = {
|
||||||
|
"description": "Successful Operation (No specific schema provided in YAPI for this response)"
|
||||||
|
}
|
||||||
|
|
||||||
|
# Ensure there's always a default response if nothing specific was added
|
||||||
|
if not endpoint_dict["responses"]:
|
||||||
|
endpoint_dict["responses"]["default"] = {"description": "Default response from YAPI definition"}
|
||||||
|
|
||||||
|
return endpoint_dict
|
||||||
|
|
||||||
|
def __repr__(self):
|
||||||
|
return f"<YAPIEndpoint ID:{self._id} Method:{self.method} Path:{self.path} Title:'{self.title}'>"
|
||||||
|
|
||||||
|
class SwaggerEndpoint(BaseEndpoint): # Inherit from BaseEndpoint
|
||||||
|
def __init__(self, path: str, method: str, data: Dict[str, Any], global_spec: Dict[str, Any]):
|
||||||
|
super().__init__(method=method.upper(), path=path)
|
||||||
|
self._raw_data = data
|
||||||
|
self._global_spec = global_spec # Store for $ref resolution
|
||||||
|
self.summary: Optional[str] = data.get("summary")
|
||||||
|
self.description: Optional[str] = data.get("description")
|
||||||
|
self.operation_id: Optional[str] = data.get("operationId")
|
||||||
|
self.tags: List[str] = data.get("tags", [])
|
||||||
|
# Parameters, requestBody, responses are processed by to_dict
|
||||||
|
|
||||||
|
def _resolve_ref(self, ref_path: str) -> Optional[Dict[str, Any]]:
|
||||||
|
"""Resolves a $ref path within the global OpenAPI/Swagger spec."""
|
||||||
|
if not ref_path.startswith("#/"):
|
||||||
|
logger.warning(f"Unsupported $ref path: {ref_path}. Only local refs '#/...' are currently supported.")
|
||||||
|
return None
|
||||||
|
|
||||||
|
parts = ref_path[2:].split('/') # Remove '#/' and split
|
||||||
|
current_level = self._global_spec
|
||||||
|
try:
|
||||||
|
for part in parts:
|
||||||
|
# Decode URI component encoding if present (e.g. "~0" for "~", "~1" for "/")
|
||||||
|
part = part.replace("~1", "/").replace("~0", "~")
|
||||||
|
current_level = current_level[part]
|
||||||
|
# It's crucial to return a copy if the resolved ref will be modified,
|
||||||
|
# or ensure modifications happen on copies later.
|
||||||
|
# For now, returning as is, assuming downstream processing is careful or uses copies.
|
||||||
|
if isinstance(current_level, dict):
|
||||||
|
return current_level # Potentially json.loads(json.dumps(current_level)) for a deep copy
|
||||||
|
else: # Resolved to a non-dict, which might be valid for some simple refs but unusual for schemas
|
||||||
|
logger.warning(f"$ref '{ref_path}' resolved to a non-dictionary type: {type(current_level)}. Value: {str(current_level)[:100]}")
|
||||||
|
return {"type": "string", "description": f"Resolved $ref '{ref_path}' to non-dict: {str(current_level)[:100]}"} # Placeholder
|
||||||
|
except (KeyError, TypeError, AttributeError) as e:
|
||||||
|
logger.error(f"Failed to resolve $ref '{ref_path}': {e}", exc_info=True)
|
||||||
|
return None
|
||||||
|
|
||||||
|
def _process_schema_or_ref(self, schema_like: Any) -> Optional[Dict[str, Any]]:
|
||||||
|
"""
|
||||||
|
Processes a schema part, resolving $refs and recursively processing nested structures.
|
||||||
|
Returns a new dictionary with resolved refs, or None if resolution fails badly.
|
||||||
|
"""
|
||||||
|
if not isinstance(schema_like, dict):
|
||||||
|
if schema_like is None: return None
|
||||||
|
logger.warning(f"Expected a dictionary for schema processing, got {type(schema_like)}. Value: {str(schema_like)[:100]}")
|
||||||
|
return {"type": "string", "description": f"Schema was not a dict: {str(schema_like)[:100]}"} # Placeholder for non-dict schema
|
||||||
|
|
||||||
|
# If it's a $ref, resolve it.
|
||||||
|
if "$ref" in schema_like:
|
||||||
|
return self._resolve_ref(schema_like["$ref"]) # This will be the new base schema_like
|
||||||
|
|
||||||
|
# Create a copy to avoid modifying the original spec during processing
|
||||||
|
processed_schema = schema_like.copy()
|
||||||
|
|
||||||
|
# Recursively process 'properties' for object schemas
|
||||||
|
if "properties" in processed_schema and isinstance(processed_schema["properties"], dict):
|
||||||
|
new_properties = {}
|
||||||
|
for prop_name, prop_schema in processed_schema["properties"].items():
|
||||||
|
resolved_prop = self._process_schema_or_ref(prop_schema)
|
||||||
|
if resolved_prop is not None: # Only add if resolution was successful
|
||||||
|
new_properties[prop_name] = resolved_prop
|
||||||
|
# else: logger.warning(f"Failed to process property '{prop_name}' in {self.operation_id or self.path}")
|
||||||
|
processed_schema["properties"] = new_properties
|
||||||
|
|
||||||
|
# Recursively process 'items' for array schemas
|
||||||
|
if "items" in processed_schema and isinstance(processed_schema["items"], dict): # 'items' should be a schema object
|
||||||
|
resolved_items = self._process_schema_or_ref(processed_schema["items"])
|
||||||
|
if resolved_items is not None:
|
||||||
|
processed_schema["items"] = resolved_items
|
||||||
|
# else: logger.warning(f"Failed to process 'items' schema in {self.operation_id or self.path}")
|
||||||
|
|
||||||
|
# Handle allOf, anyOf, oneOf by trying to merge or process them (simplistic merge for allOf)
|
||||||
|
# This is a complex area of JSON Schema. This is a very basic attempt.
|
||||||
|
if "allOf" in processed_schema and isinstance(processed_schema["allOf"], list):
|
||||||
|
merged_all_of_props = {}
|
||||||
|
merged_all_of_required = set()
|
||||||
|
temp_schema_for_all_of = {"type": processed_schema.get("type", "object"), "properties": {}, "required": []}
|
||||||
|
|
||||||
|
for sub_schema_data in processed_schema["allOf"]:
|
||||||
|
resolved_sub_schema = self._process_schema_or_ref(sub_schema_data)
|
||||||
|
if resolved_sub_schema and isinstance(resolved_sub_schema, dict):
|
||||||
|
if "properties" in resolved_sub_schema:
|
||||||
|
temp_schema_for_all_of["properties"].update(resolved_sub_schema["properties"])
|
||||||
|
if "required" in resolved_sub_schema and isinstance(resolved_sub_schema["required"], list):
|
||||||
|
merged_all_of_required.update(resolved_sub_schema["required"])
|
||||||
|
# Copy other top-level keywords from the resolved_sub_schema if needed, e.g. description
|
||||||
|
for key, value in resolved_sub_schema.items():
|
||||||
|
if key not in ["properties", "required", "type", "$ref", "allOf", "anyOf", "oneOf"]:
|
||||||
|
if key not in temp_schema_for_all_of or temp_schema_for_all_of[key] is None: # prioritize existing
|
||||||
|
temp_schema_for_all_of[key] = value
|
||||||
|
|
||||||
|
if temp_schema_for_all_of["properties"]:
|
||||||
|
processed_schema["properties"] = {**processed_schema.get("properties",{}), **temp_schema_for_all_of["properties"]}
|
||||||
|
if merged_all_of_required:
|
||||||
|
current_required = set(processed_schema.get("required", []))
|
||||||
|
current_required.update(merged_all_of_required)
|
||||||
|
processed_schema["required"] = sorted(list(current_required))
|
||||||
|
del processed_schema["allOf"] # Remove allOf after processing
|
||||||
|
# Copy other merged attributes back to processed_schema
|
||||||
|
for key, value in temp_schema_for_all_of.items():
|
||||||
|
if key not in ["properties", "required", "type", "$ref", "allOf", "anyOf", "oneOf"]:
|
||||||
|
if key not in processed_schema or processed_schema[key] is None:
|
||||||
|
processed_schema[key] = value
|
||||||
|
|
||||||
|
|
||||||
|
# anyOf, oneOf are harder as they represent choices. For now, we might just list them or pick first.
|
||||||
|
# For simplicity in to_dict, we might not fully expand them but ensure refs inside are resolved.
|
||||||
|
for keyword in ["anyOf", "oneOf"]:
|
||||||
|
if keyword in processed_schema and isinstance(processed_schema[keyword], list):
|
||||||
|
processed_sub_list = []
|
||||||
|
for sub_item in processed_schema[keyword]:
|
||||||
|
resolved_sub = self._process_schema_or_ref(sub_item)
|
||||||
|
if resolved_sub:
|
||||||
|
processed_sub_list.append(resolved_sub)
|
||||||
|
if processed_sub_list: # only update if some were resolved
|
||||||
|
processed_schema[keyword] = processed_sub_list
|
||||||
|
|
||||||
|
return processed_schema
|
||||||
|
|
||||||
|
def to_dict(self) -> Dict[str, Any]:
|
||||||
|
endpoint_data = {
|
||||||
|
"method": self.method,
|
||||||
|
"path": self.path,
|
||||||
|
"summary": self.summary or "",
|
||||||
|
"title": self.summary or self.operation_id or "", # Fallback for title
|
||||||
|
"description": self.description or "",
|
||||||
|
"operationId": self.operation_id or f"{self.method.lower()}_{self.path.replace('/', '_').replace('{', '').replace('}', '')}",
|
||||||
|
"tags": self.tags,
|
||||||
|
"parameters": [],
|
||||||
|
"requestBody": None,
|
||||||
|
"responses": {},
|
||||||
|
"_source_format": "swagger/openapi",
|
||||||
|
"_swagger_raw_data": self._raw_data, # Keep raw for debugging
|
||||||
|
"_global_api_spec_for_resolution": self._global_spec # For test cases that might need to resolve further
|
||||||
|
}
|
||||||
|
|
||||||
|
# Process parameters
|
||||||
|
if "parameters" in self._raw_data and isinstance(self._raw_data["parameters"], list):
|
||||||
|
for param_data_raw in self._raw_data["parameters"]:
|
||||||
|
# Each param_data_raw could itself be a $ref or contain a schema that is a $ref
|
||||||
|
processed_param_container = self._process_schema_or_ref(param_data_raw)
|
||||||
|
if processed_param_container and isinstance(processed_param_container, dict):
|
||||||
|
# If the parameter itself was a $ref, processed_param_container is the resolved object.
|
||||||
|
# If it contained a schema that was a $ref, that nested schema should be resolved.
|
||||||
|
# We need to ensure 'schema' key exists if 'in' is path, query, header
|
||||||
|
if "schema" in processed_param_container and isinstance(processed_param_container["schema"], dict):
|
||||||
|
# schema was present, process it further (it might have been already by _process_schema_or_ref if it was a complex object)
|
||||||
|
# but if _process_schema_or_ref was called on param_data_raw which wasn't a ref itself,
|
||||||
|
# the internal 'schema' ref might not have been re-processed with full context.
|
||||||
|
# However, the recursive nature of _process_schema_or_ref should handle nested $refs.
|
||||||
|
pass # Assume it's processed by the main call to _process_schema_or_ref on param_data_raw
|
||||||
|
elif "content" in processed_param_container: # Parameter described by Content Object (OpenAPI 3.x)
|
||||||
|
pass # Content object schemas should have been resolved by _process_schema_or_ref
|
||||||
|
|
||||||
|
endpoint_data["parameters"].append(processed_param_container)
|
||||||
|
|
||||||
|
# Process requestBody
|
||||||
|
if "requestBody" in self._raw_data and isinstance(self._raw_data["requestBody"], dict):
|
||||||
|
processed_rb = self._process_schema_or_ref(self._raw_data["requestBody"])
|
||||||
|
if processed_rb:
|
||||||
|
endpoint_data["requestBody"] = processed_rb
|
||||||
|
|
||||||
|
# Process responses
|
||||||
|
if "responses" in self._raw_data and isinstance(self._raw_data["responses"], dict):
|
||||||
|
for status_code, resp_data_raw in self._raw_data["responses"].items():
|
||||||
|
processed_resp = self._process_schema_or_ref(resp_data_raw)
|
||||||
|
if processed_resp:
|
||||||
|
endpoint_data["responses"][status_code] = processed_resp
|
||||||
|
elif resp_data_raw: # If processing failed but raw exists, keep raw (though this is less ideal)
|
||||||
|
endpoint_data["responses"][status_code] = resp_data_raw
|
||||||
|
logger.warning(f"Kept raw response data for {status_code} due to processing failure for {self.operation_id or self.path}")
|
||||||
|
|
||||||
|
if not endpoint_data["responses"]: # Ensure default response if none processed
|
||||||
|
endpoint_data["responses"]["default"] = {"description": "Default response from Swagger/OpenAPI definition"}
|
||||||
|
|
||||||
|
return endpoint_data
|
||||||
|
|
||||||
|
def __repr__(self):
|
||||||
|
return f"<SwaggerEndpoint Method:{self.method} Path:{self.path} Summary:'{self.summary}'>"
|
||||||
|
|
||||||
|
class ParsedAPISpec:
|
||||||
|
"""解析后的API规范的通用基类"""
|
||||||
|
def __init__(self, spec_type: str, endpoints: List[Union[YAPIEndpoint, SwaggerEndpoint]], spec: Dict[str, Any]):
|
||||||
|
self.spec_type = spec_type
|
||||||
|
self.endpoints = endpoints
|
||||||
|
self.spec = spec # Store the original full spec dictionary, useful for $ref resolution if not pre-resolved
|
||||||
|
|
||||||
|
class ParsedYAPISpec(ParsedAPISpec):
|
||||||
"""解析后的YAPI规范"""
|
"""解析后的YAPI规范"""
|
||||||
endpoints: List[YAPIEndpoint]
|
def __init__(self, endpoints: List[YAPIEndpoint], categories: List[Dict[str, Any]], spec: Dict[str, Any]):
|
||||||
categories: List[Dict[str, Any]]
|
super().__init__(spec_type="yapi", endpoints=endpoints, spec=spec)
|
||||||
total_count: int
|
self.categories = categories
|
||||||
|
|
||||||
@dataclass
|
class ParsedSwaggerSpec(ParsedAPISpec):
|
||||||
class SwaggerEndpoint:
|
"""解析后的Swagger/OpenAPI规范"""
|
||||||
"""Swagger API端点信息"""
|
def __init__(self, endpoints: List[SwaggerEndpoint], tags: List[Dict[str, Any]], spec: Dict[str, Any]):
|
||||||
path: str
|
super().__init__(spec_type="swagger", endpoints=endpoints, spec=spec)
|
||||||
method: str
|
self.tags = tags
|
||||||
summary: str = ""
|
|
||||||
description: str = ""
|
|
||||||
operation_id: str = ""
|
|
||||||
tags: List[str] = field(default_factory=list)
|
|
||||||
parameters: List[Dict[str, Any]] = field(default_factory=list)
|
|
||||||
responses: Dict[str, Any] = field(default_factory=dict)
|
|
||||||
consumes: List[str] = field(default_factory=list)
|
|
||||||
produces: List[str] = field(default_factory=list)
|
|
||||||
request_body: Dict[str, Any] = field(default_factory=dict)
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class ParsedSwaggerSpec:
|
|
||||||
"""解析后的Swagger规范"""
|
|
||||||
endpoints: List[SwaggerEndpoint]
|
|
||||||
info: Dict[str, Any]
|
|
||||||
swagger_version: str
|
|
||||||
host: str = ""
|
|
||||||
base_path: str = ""
|
|
||||||
schemes: List[str] = field(default_factory=list)
|
|
||||||
tags: List[Dict[str, Any]] = field(default_factory=list)
|
|
||||||
categories: List[Dict[str, Any]] = field(default_factory=list)
|
|
||||||
|
|
||||||
class ParsedBusinessLogic(BaseModel):
|
|
||||||
# Placeholder for parsed business logic flow
|
|
||||||
name: str
|
|
||||||
steps: list # List of steps, each could be another Pydantic model
|
|
||||||
|
|
||||||
class InputParser:
|
class InputParser:
|
||||||
"""
|
"""负责解析输入（如YAPI JSON）并提取API端点信息"""
|
||||||
Responsible for parsing DDMS supplier's input materials like API specs, etc.
|
|
||||||
"""
|
|
||||||
|
|
||||||
def __init__(self):
|
def __init__(self):
|
||||||
pass
|
self.logger = logging.getLogger(__name__)
|
||||||
|
|
||||||
def parse_openapi_spec(self, spec_path: str) -> Optional[ParsedOpenAPISpec]:
|
|
||||||
"""
|
|
||||||
Parses an OpenAPI specification from a file path.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
spec_path: The file path of the OpenAPI specification.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
A ParsedOpenAPISpec object containing the parsed specification,
|
|
||||||
or None if parsing fails.
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
# Check if file exists
|
|
||||||
if not os.path.exists(spec_path):
|
|
||||||
print(f"Error: File not found: {spec_path}")
|
|
||||||
return None
|
|
||||||
|
|
||||||
# Read and parse JSON file
|
|
||||||
with open(spec_path, 'r', encoding='utf-8') as f:
|
|
||||||
swagger_data = json.load(f)
|
|
||||||
|
|
||||||
# Extract basic information
|
|
||||||
swagger_version = swagger_data.get('swagger', swagger_data.get('openapi', 'Unknown'))
|
|
||||||
info = swagger_data.get('info', {})
|
|
||||||
paths = swagger_data.get('paths', {})
|
|
||||||
tags = swagger_data.get('tags', [])
|
|
||||||
base_path = swagger_data.get('basePath', '')
|
|
||||||
|
|
||||||
# Create and return ParsedOpenAPISpec
|
|
||||||
return ParsedOpenAPISpec(
|
|
||||||
spec=swagger_data,
|
|
||||||
info=info,
|
|
||||||
paths=paths,
|
|
||||||
tags=tags,
|
|
||||||
basePath=base_path,
|
|
||||||
swagger_version=swagger_version
|
|
||||||
)
|
|
||||||
|
|
||||||
except FileNotFoundError:
|
|
||||||
print(f"File not found: {spec_path}")
|
|
||||||
return None
|
|
||||||
except json.JSONDecodeError as e:
|
|
||||||
print(f"Error parsing JSON from {spec_path}: {e}")
|
|
||||||
return None
|
|
||||||
except Exception as e:
|
|
||||||
print(f"Error parsing OpenAPI spec from {spec_path}: {e}")
|
|
||||||
return None
|
|
||||||
|
|
||||||
def parse_yapi_spec(self, file_path: str) -> Optional[ParsedYAPISpec]:
|
def parse_yapi_spec(self, file_path: str) -> Optional[ParsedYAPISpec]:
|
||||||
"""
|
self.logger.info(f"Parsing YAPI spec from: {file_path}")
|
||||||
解析YAPI规范文件
|
all_endpoints: List[YAPIEndpoint] = []
|
||||||
|
yapi_categories: List[Dict[str, Any]] = []
|
||||||
Args:
|
raw_spec_data_list: Optional[List[Dict[str, Any]]] = None # YAPI export is a list of categories
|
||||||
file_path: YAPI JSON文件路径
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
Optional[ParsedYAPISpec]: 解析后的YAPI规范，如果解析失败则返回None
|
|
||||||
"""
|
|
||||||
if not os.path.isfile(file_path):
|
|
||||||
logger.error(f"文件不存在: {file_path}")
|
|
||||||
return None
|
|
||||||
|
|
||||||
try:
|
try:
|
||||||
with open(file_path, 'r', encoding='utf-8') as f:
|
with open(file_path, 'r', encoding='utf-8') as f:
|
||||||
yapi_data = json.load(f)
|
raw_spec_data_list = json.load(f)
|
||||||
|
|
||||||
if not isinstance(yapi_data, list):
|
if not isinstance(raw_spec_data_list, list):
|
||||||
logger.error(f"无效的YAPI文件格式: 顶层元素应该是数组")
|
self.logger.error(f"YAPI spec file {file_path} does not contain a JSON list as expected for categories.")
|
||||||
return None
|
return None
|
||||||
|
|
||||||
endpoints = []
|
for category_data in raw_spec_data_list:
|
||||||
categories = []
|
|
||||||
|
|
||||||
# 处理分类
|
|
||||||
for category_data in yapi_data:
|
|
||||||
if not isinstance(category_data, dict):
|
if not isinstance(category_data, dict):
|
||||||
logger.warning(f"YAPI 分类条目格式不正确，应为字典类型，已跳过: {category_data}")
|
self.logger.warning(f"Skipping non-dictionary item in YAPI spec list: {str(category_data)[:100]}")
|
||||||
continue
|
continue
|
||||||
|
cat_name = category_data.get("name")
|
||||||
|
cat_id = category_data.get("_id", category_data.get("id")) # YAPI uses _id
|
||||||
|
yapi_categories.append({"name": cat_name, "description": category_data.get("desc"), "id": cat_id})
|
||||||
|
|
||||||
category_name = category_data.get('name', '')
|
for endpoint_data in category_data.get("list", []):
|
||||||
category_desc = category_data.get('desc', '')
|
if not isinstance(endpoint_data, dict):
|
||||||
|
self.logger.warning(f"Skipping non-dictionary endpoint item in category '{cat_name}': {str(endpoint_data)[:100]}")
|
||||||
# 添加到分类列表
|
|
||||||
categories.append({
|
|
||||||
'name': category_name,
|
|
||||||
'desc': category_desc
|
|
||||||
})
|
|
||||||
|
|
||||||
# 处理API接口
|
|
||||||
api_list = category_data.get('list', [])
|
|
||||||
if not isinstance(api_list, list):
|
|
||||||
logger.warning(f"分类 '{category_name}' 中的 API列表 (list) 格式不正确，应为数组类型，已跳过。")
|
|
||||||
continue
|
|
||||||
|
|
||||||
for api_item in api_list:
|
|
||||||
if not isinstance(api_item, dict):
|
|
||||||
logger.warning(f"分类 '{category_name}' 中的 API条目格式不正确，应为字典类型，已跳过: {api_item}")
|
|
||||||
continue
|
continue
|
||||||
|
try:
|
||||||
|
yapi_endpoint = YAPIEndpoint(endpoint_data, category_name=cat_name, category_id=cat_id)
|
||||||
|
all_endpoints.append(yapi_endpoint)
|
||||||
|
except Exception as e_ep:
|
||||||
|
self.logger.error(f"Error processing YAPI endpoint data (ID: {endpoint_data.get('_id', 'N/A')}, Title: {endpoint_data.get('title', 'N/A')}). Error: {e_ep}", exc_info=True)
|
||||||
|
|
||||||
# 提取API信息
|
# The 'spec' for ParsedYAPISpec should be a dict representing the whole document.
|
||||||
path = api_item.get('path', '')
|
# Since YAPI export is a list of categories, we wrap it.
|
||||||
if not path:
|
yapi_full_spec_dict = {"yapi_categories": raw_spec_data_list}
|
||||||
logger.info(f"分类 '{category_name}' 中的 API条目缺少 'path'，使用空字符串。 API: {api_item.get('title', '未命名')}")
|
return ParsedYAPISpec(endpoints=all_endpoints, categories=yapi_categories, spec=yapi_full_spec_dict)
|
||||||
method = api_item.get('method', 'GET')
|
except FileNotFoundError:
|
||||||
if api_item.get('method') is None: # 仅当原始数据中完全没有 method 字段时记录
|
self.logger.error(f"YAPI spec file not found: {file_path}")
|
||||||
logger.info(f"分类 '{category_name}' 中的 API条目 '{path}' 缺少 'method'，使用默认值 'GET'。")
|
except json.JSONDecodeError as e:
|
||||||
title = api_item.get('title', '')
|
self.logger.error(f"Error decoding JSON from YAPI spec file {file_path}: {e}")
|
||||||
if not title:
|
|
||||||
logger.info(f"分类 '{category_name}' 中的 API条目 '{path}' ({method}) 缺少 'title'，使用空字符串。")
|
|
||||||
description = api_item.get('desc', '')
|
|
||||||
|
|
||||||
# 提取请求参数
|
|
||||||
req_params = api_item.get('req_params', [])
|
|
||||||
req_query = api_item.get('req_query', [])
|
|
||||||
req_headers = api_item.get('req_headers', [])
|
|
||||||
|
|
||||||
# 提取请求体信息
|
|
||||||
req_body_type = api_item.get('req_body_type', '')
|
|
||||||
req_body_other = api_item.get('req_body_other', '')
|
|
||||||
|
|
||||||
# 提取响应体信息
|
|
||||||
res_body_type = api_item.get('res_body_type', '')
|
|
||||||
res_body = api_item.get('res_body', '')
|
|
||||||
|
|
||||||
# 创建端点对象
|
|
||||||
endpoint = YAPIEndpoint(
|
|
||||||
path=path,
|
|
||||||
method=method,
|
|
||||||
title=title,
|
|
||||||
description=description,
|
|
||||||
category_name=category_name,
|
|
||||||
req_params=req_params,
|
|
||||||
req_query=req_query,
|
|
||||||
req_headers=req_headers,
|
|
||||||
req_body_type=req_body_type,
|
|
||||||
req_body_other=req_body_other,
|
|
||||||
res_body_type=res_body_type,
|
|
||||||
res_body=res_body
|
|
||||||
)
|
|
||||||
|
|
||||||
endpoints.append(endpoint)
|
|
||||||
|
|
||||||
return ParsedYAPISpec(
|
|
||||||
endpoints=endpoints,
|
|
||||||
categories=categories,
|
|
||||||
total_count=len(endpoints)
|
|
||||||
)
|
|
||||||
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"解析YAPI文件时出错: {str(e)}")
|
self.logger.error(f"An unexpected error occurred while parsing YAPI spec {file_path}: {e}", exc_info=True)
|
||||||
return None
|
return None
|
||||||
|
|
||||||
def parse_swagger_spec(self, file_path: str) -> Optional[ParsedSwaggerSpec]:
|
def parse_swagger_spec(self, file_path: str) -> Optional[ParsedSwaggerSpec]:
|
||||||
"""
|
self.logger.info(f"Parsing Swagger/OpenAPI spec from: {file_path}")
|
||||||
解析Swagger规范文件
|
all_endpoints: List[SwaggerEndpoint] = []
|
||||||
|
swagger_tags: List[Dict[str, Any]] = []
|
||||||
Args:
|
raw_spec_data_dict: Optional[Dict[str, Any]] = None # Swagger/OpenAPI is a single root object
|
||||||
file_path: Swagger JSON文件路径
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
Optional[ParsedSwaggerSpec]: 解析后的Swagger规范，如果解析失败则返回None
|
|
||||||
"""
|
|
||||||
if not os.path.isfile(file_path):
|
|
||||||
logger.error(f"文件不存在: {file_path}")
|
|
||||||
return None
|
|
||||||
|
|
||||||
try:
|
try:
|
||||||
with open(file_path, 'r', encoding='utf-8') as f:
|
with open(file_path, 'r', encoding='utf-8') as f:
|
||||||
swagger_data = json.load(f)
|
# TODO: Add YAML support if needed, e.g., using PyYAML
|
||||||
|
raw_spec_data_dict = json.load(f)
|
||||||
|
|
||||||
if not isinstance(swagger_data, dict):
|
if not isinstance(raw_spec_data_dict, dict):
|
||||||
logger.error(f"无效的Swagger文件格式: 顶层元素应该是对象")
|
self.logger.error(f"Swagger spec file {file_path} does not contain a JSON object as expected.")
|
||||||
return None
|
return None
|
||||||
|
|
||||||
# 提取基本信息
|
swagger_tags = raw_spec_data_dict.get("tags", [])
|
||||||
swagger_version = swagger_data.get('swagger', swagger_data.get('openapi', ''))
|
paths = raw_spec_data_dict.get("paths", {})
|
||||||
info = swagger_data.get('info', {})
|
|
||||||
host = swagger_data.get('host', '')
|
|
||||||
base_path = swagger_data.get('basePath', '')
|
|
||||||
schemes = swagger_data.get('schemes', [])
|
|
||||||
tags = swagger_data.get('tags', [])
|
|
||||||
|
|
||||||
# 创建分类列表
|
for path, path_item_obj in paths.items():
|
||||||
categories = []
|
if not isinstance(path_item_obj, dict): continue
|
||||||
for tag in tags:
|
for method, operation_obj in path_item_obj.items():
|
||||||
categories.append({
|
# Common methods, can be extended
|
||||||
'name': tag.get('name', ''),
|
if method.lower() not in ["get", "post", "put", "delete", "patch", "options", "head", "trace"]:
|
||||||
'desc': tag.get('description', '')
|
continue # Skip non-standard HTTP methods or extensions like 'parameters' at path level
|
||||||
})
|
if not isinstance(operation_obj, dict): continue
|
||||||
|
try:
|
||||||
# 处理API路径
|
# Pass the full raw_spec_data_dict for $ref resolution within SwaggerEndpoint
|
||||||
paths = swagger_data.get('paths', {})
|
swagger_endpoint = SwaggerEndpoint(path, method, operation_obj, global_spec=raw_spec_data_dict)
|
||||||
endpoints = []
|
all_endpoints.append(swagger_endpoint)
|
||||||
|
except Exception as e_ep:
|
||||||
for path, path_item in paths.items():
|
self.logger.error(f"Error processing Swagger endpoint: {method.upper()} {path}. Error: {e_ep}", exc_info=True)
|
||||||
if not isinstance(path_item, dict):
|
|
||||||
continue
|
|
||||||
|
|
||||||
# 处理每个HTTP方法 (GET, POST, PUT, DELETE等)
|
|
||||||
for method, operation in path_item.items():
|
|
||||||
if method in ['get', 'post', 'put', 'delete', 'patch', 'options', 'head', 'trace']:
|
|
||||||
if not isinstance(operation, dict):
|
|
||||||
continue
|
|
||||||
|
|
||||||
# 提取操作信息
|
|
||||||
summary = operation.get('summary', '')
|
|
||||||
description = operation.get('description', '')
|
|
||||||
operation_id = operation.get('operationId', '')
|
|
||||||
operation_tags = operation.get('tags', [])
|
|
||||||
|
|
||||||
# 提取参数信息
|
|
||||||
parameters = operation.get('parameters', [])
|
|
||||||
|
|
||||||
# 提取响应信息
|
|
||||||
responses = operation.get('responses', {})
|
|
||||||
|
|
||||||
# 提取请求和响应的内容类型
|
|
||||||
consumes = operation.get('consumes', swagger_data.get('consumes', []))
|
|
||||||
produces = operation.get('produces', swagger_data.get('produces', []))
|
|
||||||
|
|
||||||
# 提取请求体信息 (OpenAPI 3.0 格式)
|
|
||||||
request_body = operation.get('requestBody', {})
|
|
||||||
|
|
||||||
# 创建端点对象
|
|
||||||
endpoint = SwaggerEndpoint(
|
|
||||||
path=path,
|
|
||||||
method=method.upper(),
|
|
||||||
summary=summary,
|
|
||||||
description=description,
|
|
||||||
operation_id=operation_id,
|
|
||||||
tags=operation_tags,
|
|
||||||
parameters=parameters,
|
|
||||||
responses=responses,
|
|
||||||
consumes=consumes,
|
|
||||||
produces=produces,
|
|
||||||
request_body=request_body
|
|
||||||
)
|
|
||||||
|
|
||||||
endpoints.append(endpoint)
|
|
||||||
|
|
||||||
# 创建返回对象
|
|
||||||
return ParsedSwaggerSpec(
|
|
||||||
endpoints=endpoints,
|
|
||||||
info=info,
|
|
||||||
swagger_version=swagger_version,
|
|
||||||
host=host,
|
|
||||||
base_path=base_path,
|
|
||||||
schemes=schemes,
|
|
||||||
tags=tags,
|
|
||||||
categories=categories
|
|
||||||
)
|
|
||||||
|
|
||||||
|
return ParsedSwaggerSpec(endpoints=all_endpoints, tags=swagger_tags, spec=raw_spec_data_dict)
|
||||||
|
except FileNotFoundError:
|
||||||
|
self.logger.error(f"Swagger spec file not found: {file_path}")
|
||||||
|
except json.JSONDecodeError as e:
|
||||||
|
self.logger.error(f"Error decoding JSON from Swagger spec file {file_path}: {e}")
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"解析Swagger文件时出错: {str(e)}")
|
self.logger.error(f"An unexpected error occurred while parsing Swagger spec {file_path}: {e}", exc_info=True)
|
||||||
return None
|
return None
|
||||||
|
|
||||||
def parse_business_logic_flow(self, flow_description: str) -> Optional[ParsedBusinessLogic]:
|
|
||||||
"""
|
|
||||||
Parses a business logic flow description.
|
|
||||||
The format of this description is TBD and this parser would need to be built accordingly.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
flow_description: The string content describing the business logic flow.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
A ParsedBusinessLogic object or None if parsing fails.
|
|
||||||
"""
|
|
||||||
print(f"[InputParser] Placeholder: Parsing business logic flow. Content: {flow_description[:100]}...")
|
|
||||||
# Placeholder: Actual parsing logic will depend on the defined format.
|
|
||||||
return ParsedBusinessLogic(name="Example Flow", steps=["Step 1 API call", "Step 2 Validate Response"])
|
|
||||||
|
|
||||||
# Add other parsers as needed (e.g., for data object definitions)
|
|
||||||
Binary file not shown.
@ -20,22 +20,22 @@ logger = logging.getLogger(__name__)
|
|||||||
class ValidationResult:
|
class ValidationResult:
|
||||||
"""Validation result container"""
|
"""Validation result container"""
|
||||||
|
|
||||||
def __init__(self, is_valid: bool, errors: List[str] = None, warnings: List[str] = None):
|
def __init__(self, passed: bool, errors: List[str] = None, warnings: List[str] = None):
|
||||||
"""
|
"""
|
||||||
Initialize a validation result
|
Initialize a validation result
|
||||||
|
|
||||||
Args:
|
Args:
|
||||||
is_valid: Whether the data is valid according to the schema
|
passed: Whether the data is valid according to the schema
|
||||||
errors: List of error messages (if any)
|
errors: List of error messages (if any)
|
||||||
warnings: List of warning messages (if any)
|
warnings: List of warning messages (if any)
|
||||||
"""
|
"""
|
||||||
self.is_valid = is_valid
|
self.passed = passed
|
||||||
self.errors = errors or []
|
self.errors = errors or []
|
||||||
self.warnings = warnings or []
|
self.warnings = warnings or []
|
||||||
|
|
||||||
def __str__(self) -> str:
|
def __str__(self) -> str:
|
||||||
"""String representation of validation result"""
|
"""String representation of validation result"""
|
||||||
status = "Valid" if self.is_valid else "Invalid"
|
status = "Valid" if self.passed else "Invalid"
|
||||||
result = f"Validation Result: {status}\n"
|
result = f"Validation Result: {status}\n"
|
||||||
|
|
||||||
if self.errors:
|
if self.errors:
|
||||||
|
|||||||
@ -93,18 +93,20 @@ class BaseAPITestCase:
|
|||||||
use_llm_for_query_params: bool = False
|
use_llm_for_query_params: bool = False
|
||||||
use_llm_for_headers: bool = False
|
use_llm_for_headers: bool = False
|
||||||
|
|
||||||
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None):
|
def __init__(self, endpoint_spec: Dict[str, Any], global_api_spec: Dict[str, Any], json_schema_validator: Optional[Any] = None, llm_service: Optional[Any] = None):
|
||||||
"""
|
"""
|
||||||
初始化测试用例。
|
初始化测试用例。
|
||||||
Args:
|
Args:
|
||||||
endpoint_spec: 当前被测API端点的详细定义 (来自YAPI/Swagger解析结果)。
|
endpoint_spec: 当前被测API端点的详细定义 (来自YAPI/Swagger解析结果)。
|
||||||
global_api_spec: 完整的API规范文档 (来自YAPI/Swagger解析结果)。
|
global_api_spec: 完整的API规范文档 (来自YAPI/Swagger解析结果)。
|
||||||
json_schema_validator: APITestOrchestrator 传入的 JSONSchemaValidator 实例 (可选)。
|
json_schema_validator: APITestOrchestrator 传入的 JSONSchemaValidator 实例 (可选)。
|
||||||
|
llm_service: APITestOrchestrator 传入的 LLMService 实例 (可选)。
|
||||||
"""
|
"""
|
||||||
self.endpoint_spec = endpoint_spec
|
self.endpoint_spec = endpoint_spec
|
||||||
self.global_api_spec = global_api_spec
|
self.global_api_spec = global_api_spec
|
||||||
self.logger = logging.getLogger(f"testcase.{self.id}")
|
self.logger = logging.getLogger(f"testcase.{self.id}")
|
||||||
self.json_schema_validator = json_schema_validator # 存储传入的校验器实例
|
self.json_schema_validator = json_schema_validator # 存储传入的校验器实例
|
||||||
|
self.llm_service = llm_service # 存储注入的 LLMService 实例
|
||||||
self.logger.debug(f"Test case '{self.id}' initialized for endpoint: {self.endpoint_spec.get('method', '')} {self.endpoint_spec.get('path', '')}")
|
self.logger.debug(f"Test case '{self.id}' initialized for endpoint: {self.endpoint_spec.get('method', '')} {self.endpoint_spec.get('path', '')}")
|
||||||
|
|
||||||
# --- 1. 请求生成与修改阶段 ---
|
# --- 1. 请求生成与修改阶段 ---
|
||||||
@ -120,6 +122,20 @@ class BaseAPITestCase:
|
|||||||
self.logger.debug(f"Hook: generate_request_body, current body type: {type(current_body)}")
|
self.logger.debug(f"Hook: generate_request_body, current body type: {type(current_body)}")
|
||||||
return current_body
|
return current_body
|
||||||
|
|
||||||
|
def generate_path_params(self, current_path_params: Dict[str, Any]) -> Dict[str, Any]:
|
||||||
|
"""
|
||||||
|
允许测试用例修改或生成路径参数。
|
||||||
|
这些参数将用于替换URL中的占位符，例如 /users/{userId}。
|
||||||
|
|
||||||
|
Args:
|
||||||
|
current_path_params: 从API规范或编排器默认逻辑生成的初始路径参数。
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
最终要使用的路径参数字典。
|
||||||
|
"""
|
||||||
|
self.logger.debug(f"Hook: generate_path_params, current: {current_path_params}")
|
||||||
|
return current_path_params
|
||||||
|
|
||||||
# --- 1.5. 请求URL修改阶段 (新增钩子) ---
|
# --- 1.5. 请求URL修改阶段 (新增钩子) ---
|
||||||
def modify_request_url(self, current_url: str) -> str:
|
def modify_request_url(self, current_url: str) -> str:
|
||||||
"""
|
"""
|
||||||
@ -180,26 +196,40 @@ class BaseAPITestCase:
|
|||||||
results.append(self.failed(f"{context_message_prefix} schema validation skipped: Validator not available."))
|
results.append(self.failed(f"{context_message_prefix} schema validation skipped: Validator not available."))
|
||||||
return results
|
return results
|
||||||
|
|
||||||
is_valid, errors = self.json_schema_validator.validate(data_to_validate, schema_definition)
|
# validator_result 是 JSONSchemaValidator 内部定义的 ValidationResult 对象
|
||||||
|
validator_result = self.json_schema_validator.validate(data_to_validate, schema_definition)
|
||||||
|
|
||||||
if is_valid:
|
if validator_result.passed:
|
||||||
results.append(self.passed(f"{context_message_prefix} conforms to the JSON schema."))
|
success_message = f"{context_message_prefix} conforms to the JSON schema."
|
||||||
|
# 可以选择性地将 validator 的警告信息添加到 details
|
||||||
|
current_details = {}
|
||||||
|
if validator_result.warnings:
|
||||||
|
current_details["schema_warnings"] = validator_result.warnings
|
||||||
|
# 如果 validator_result 有其他有用的成功信息，也可以加入 message 或 details
|
||||||
|
results.append(self.passed(success_message, details=current_details if current_details else None))
|
||||||
else:
|
else:
|
||||||
error_messages = []
|
# 从 validator_result.errors 构建 message 和 details
|
||||||
if isinstance(errors, list):
|
error_reason = "Validation failed."
|
||||||
for error in errors: # jsonschema.exceptions.ValidationError 对象
|
if validator_result.errors:
|
||||||
error_messages.append(f"- Path: '{list(error.path)}', Message: {error.message}") # error.path 是一个deque
|
error_reason = "Errors:\n" + "\n".join([f"- {e}" for e in validator_result.errors])
|
||||||
elif isinstance(errors, str): # 兼容旧版或简单错误字符串
|
|
||||||
error_messages.append(errors)
|
full_message = f"{context_message_prefix} does not conform to the JSON schema. {error_reason}"
|
||||||
|
|
||||||
|
current_details = {
|
||||||
|
"schema_errors": validator_result.errors,
|
||||||
|
"validated_data_sample": str(data_to_validate)[:200]
|
||||||
|
}
|
||||||
|
if validator_result.warnings:
|
||||||
|
current_details["schema_warnings"] = validator_result.warnings
|
||||||
|
|
||||||
full_message = f"{context_message_prefix} does not conform to the JSON schema. Errors:\n" + "\n".join(error_messages)
|
|
||||||
results.append(self.failed(
|
results.append(self.failed(
|
||||||
message=full_message,
|
message=full_message,
|
||||||
details={"schema_errors": error_messages, "validated_data_sample": str(data_to_validate)[:200]}
|
details=current_details
|
||||||
))
|
))
|
||||||
self.logger.warning(f"{context_message_prefix} schema validation failed: {full_message}")
|
self.logger.warning(f"{context_message_prefix} schema validation failed: {full_message}")
|
||||||
return results
|
return results
|
||||||
|
|
||||||
|
|
||||||
# --- Helper to easily create a passed ValidationResult ---
|
# --- Helper to easily create a passed ValidationResult ---
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def passed(message: str, details: Optional[Dict[str, Any]] = None) -> ValidationResult:
|
def passed(message: str, details: Optional[Dict[str, Any]] = None) -> ValidationResult:
|
||||||
|
|||||||
@ -640,21 +640,22 @@ class APITestOrchestrator:
|
|||||||
validation_results: List[ValidationResult] = []
|
validation_results: List[ValidationResult] = []
|
||||||
overall_status: ExecutedTestCaseResult.Status
|
overall_status: ExecutedTestCaseResult.Status
|
||||||
execution_message = ""
|
execution_message = ""
|
||||||
|
test_case_instance: Optional[BaseAPITestCase] = None # Initialize to None
|
||||||
|
|
||||||
# 将 endpoint_spec 转换为字典，如果它还不是的话
|
# 将 endpoint_spec 转换为字典，如果它还不是的话
|
||||||
endpoint_spec_dict: Dict[str, Any]
|
endpoint_spec_dict: Dict[str, Any]
|
||||||
if isinstance(endpoint_spec, dict):
|
if isinstance(endpoint_spec, dict):
|
||||||
endpoint_spec_dict = endpoint_spec
|
endpoint_spec_dict = endpoint_spec
|
||||||
self.logger.debug(f"endpoint_spec 已经是字典类型。")
|
# self.logger.debug(f"endpoint_spec 已经是字典类型。")
|
||||||
elif hasattr(endpoint_spec, 'to_dict') and callable(endpoint_spec.to_dict):
|
elif hasattr(endpoint_spec, 'to_dict') and callable(endpoint_spec.to_dict):
|
||||||
try:
|
try:
|
||||||
endpoint_spec_dict = endpoint_spec.to_dict()
|
endpoint_spec_dict = endpoint_spec.to_dict()
|
||||||
self.logger.debug(f"成功通过 to_dict() 方法将类型为 {type(endpoint_spec)} 的 endpoint_spec 转换为字典。")
|
# self.logger.debug(f"成功通过 to_dict() 方法将类型为 {type(endpoint_spec)} 的 endpoint_spec 转换为字典。")
|
||||||
if not endpoint_spec_dict: # 如果 to_dict() 返回空字典
|
if not endpoint_spec_dict: # 如果 to_dict() 返回空字典
|
||||||
self.logger.warning(f"endpoint_spec.to_dict() (类型: {type(endpoint_spec)}) 返回了一个空字典。")
|
# self.logger.warning(f"endpoint_spec.to_dict() (类型: {type(endpoint_spec)}) 返回了一个空字典。")
|
||||||
# 尝试备用转换
|
# 尝试备用转换
|
||||||
if isinstance(endpoint_spec, (YAPIEndpoint, SwaggerEndpoint)):
|
if isinstance(endpoint_spec, (YAPIEndpoint, SwaggerEndpoint)):
|
||||||
self.logger.debug(f"尝试从 {type(endpoint_spec).__name__} 对象的属性手动构建 endpoint_spec_dict。")
|
# self.logger.debug(f"尝试从 {type(endpoint_spec).__name__} 对象的属性手动构建 endpoint_spec_dict。")
|
||||||
endpoint_spec_dict = {
|
endpoint_spec_dict = {
|
||||||
"method": getattr(endpoint_spec, 'method', 'UNKNOWN_METHOD').upper(),
|
"method": getattr(endpoint_spec, 'method', 'UNKNOWN_METHOD').upper(),
|
||||||
"path": getattr(endpoint_spec, 'path', 'UNKNOWN_PATH'),
|
"path": getattr(endpoint_spec, 'path', 'UNKNOWN_PATH'),
|
||||||
@ -667,7 +668,7 @@ class APITestOrchestrator:
|
|||||||
"_original_object_type": type(endpoint_spec).__name__
|
"_original_object_type": type(endpoint_spec).__name__
|
||||||
}
|
}
|
||||||
if not any(endpoint_spec_dict.values()): # 如果手动构建后仍基本为空
|
if not any(endpoint_spec_dict.values()): # 如果手动构建后仍基本为空
|
||||||
self.logger.error(f"手动从属性构建 endpoint_spec_dict (类型: {type(endpoint_spec)}) 后仍然为空或无效。")
|
# self.logger.error(f"手动从属性构建 endpoint_spec_dict (类型: {type(endpoint_spec)}) 后仍然为空或无效。")
|
||||||
endpoint_spec_dict = {} # 重置为空，触发下方错误处理
|
endpoint_spec_dict = {} # 重置为空，触发下方错误处理
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
self.logger.error(f"调用 endpoint_spec (类型: {type(endpoint_spec)}) 的 to_dict() 方法时出错: {e}。尝试备用转换。")
|
self.logger.error(f"调用 endpoint_spec (类型: {type(endpoint_spec)}) 的 to_dict() 方法时出错: {e}。尝试备用转换。")
|
||||||
@ -691,10 +692,10 @@ class APITestOrchestrator:
|
|||||||
endpoint_spec_dict = {} # 转换失败
|
endpoint_spec_dict = {} # 转换失败
|
||||||
elif hasattr(endpoint_spec, 'data') and isinstance(getattr(endpoint_spec, 'data'), dict): # 兼容 YAPIEndpoint 结构
|
elif hasattr(endpoint_spec, 'data') and isinstance(getattr(endpoint_spec, 'data'), dict): # 兼容 YAPIEndpoint 结构
|
||||||
endpoint_spec_dict = getattr(endpoint_spec, 'data')
|
endpoint_spec_dict = getattr(endpoint_spec, 'data')
|
||||||
self.logger.debug(f"使用了类型为 {type(endpoint_spec)} 的 endpoint_spec 的 .data 属性。")
|
# self.logger.debug(f"使用了类型为 {type(endpoint_spec)} 的 endpoint_spec 的 .data 属性。")
|
||||||
else: # 如果没有 to_dict, 也不是已知可直接访问 .data 的类型，则尝试最后的通用转换或手动构建
|
else: # 如果没有 to_dict, 也不是已知可直接访问 .data 的类型，则尝试最后的通用转换或手动构建
|
||||||
if isinstance(endpoint_spec, (YAPIEndpoint, SwaggerEndpoint)):
|
if isinstance(endpoint_spec, (YAPIEndpoint, SwaggerEndpoint)):
|
||||||
self.logger.debug(f"类型为 {type(endpoint_spec).__name__} 的 endpoint_spec 没有 to_dict() 或 data，尝试从属性手动构建。")
|
# self.logger.debug(f"类型为 {type(endpoint_spec).__name__} 的 endpoint_spec 没有 to_dict() 或 data，尝试从属性手动构建。")
|
||||||
endpoint_spec_dict = {
|
endpoint_spec_dict = {
|
||||||
"method": getattr(endpoint_spec, 'method', 'UNKNOWN_METHOD').upper(),
|
"method": getattr(endpoint_spec, 'method', 'UNKNOWN_METHOD').upper(),
|
||||||
"path": getattr(endpoint_spec, 'path', 'UNKNOWN_PATH'),
|
"path": getattr(endpoint_spec, 'path', 'UNKNOWN_PATH'),
|
||||||
@ -795,7 +796,8 @@ class APITestOrchestrator:
|
|||||||
test_case_instance = test_case_class(
|
test_case_instance = test_case_class(
|
||||||
endpoint_spec=endpoint_spec_dict,
|
endpoint_spec=endpoint_spec_dict,
|
||||||
global_api_spec=global_spec_dict,
|
global_api_spec=global_spec_dict,
|
||||||
json_schema_validator=self.validator
|
json_schema_validator=self.validator,
|
||||||
|
llm_service=self.llm_service # Pass the orchestrator's LLM service instance
|
||||||
)
|
)
|
||||||
self.logger.info(f"开始执行测试用例 '{test_case_instance.id}' ({test_case_instance.name}) for endpoint '{endpoint_spec_dict.get('method', 'N/A')} {endpoint_spec_dict.get('path', 'N/A')}'")
|
self.logger.info(f"开始执行测试用例 '{test_case_instance.id}' ({test_case_instance.name}) for endpoint '{endpoint_spec_dict.get('method', 'N/A')} {endpoint_spec_dict.get('path', 'N/A')}'")
|
||||||
|
|
||||||
@ -928,226 +930,199 @@ class APITestOrchestrator:
|
|||||||
)
|
)
|
||||||
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
self.logger.error(f"执行测试用例 '{test_case_class.id if test_case_instance else test_case_class.__name__}' 时发生严重错误: {e}", exc_info=True)
|
self.logger.error(f"执行测试用例 '{test_case_class.id if hasattr(test_case_class, 'id') else test_case_class.__name__}' (在实例化阶段或之前) 时发生严重错误: {e}", exc_info=True)
|
||||||
|
# 如果 test_case_instance 在实例化时失败，它将是 None
|
||||||
|
tc_id_for_log = test_case_instance.id if test_case_instance else (test_case_class.id if hasattr(test_case_class, 'id') else "unknown_tc_id_instantiation_error")
|
||||||
|
tc_name_for_log = test_case_instance.name if test_case_instance else (test_case_class.name if hasattr(test_case_class, 'name') else test_case_class.__name__)
|
||||||
|
# 实例化失败，严重性默认为CRITICAL
|
||||||
|
tc_severity_for_log = test_case_instance.severity if test_case_instance else TestSeverity.CRITICAL
|
||||||
|
|
||||||
tc_duration = time.monotonic() - start_time
|
tc_duration = time.monotonic() - start_time
|
||||||
|
# validation_results 可能在此阶段为空，或包含来自先前步骤的条目（如果错误发生在实例化之后）
|
||||||
return ExecutedTestCaseResult(
|
return ExecutedTestCaseResult(
|
||||||
test_case_id=test_case_instance.id if test_case_instance else test_case_class.id if hasattr(test_case_class, 'id') else "unknown_tc_id",
|
test_case_id=tc_id_for_log,
|
||||||
test_case_name=test_case_instance.name if test_case_instance else test_case_class.name if hasattr(test_case_class, 'name') else "Unknown Test Case Name",
|
test_case_name=tc_name_for_log,
|
||||||
test_case_severity=test_case_instance.severity if test_case_instance else TestSeverity.CRITICAL,
|
test_case_severity=tc_severity_for_log,
|
||||||
status=ExecutedTestCaseResult.Status.ERROR,
|
status=ExecutedTestCaseResult.Status.ERROR,
|
||||||
validation_points=validation_results,
|
validation_points=validation_results, # Ensure validation_results is defined (it is, at the start of the function)
|
||||||
message=f"测试用例执行时发生内部错误: {str(e)}",
|
message=f"测试用例执行时发生内部错误 (可能在实例化期间): {str(e)}",
|
||||||
duration=tc_duration
|
duration=tc_duration
|
||||||
)
|
)
|
||||||
|
|
||||||
def _prepare_initial_request_data(
|
def _prepare_initial_request_data(
|
||||||
self,
|
self,
|
||||||
endpoint_spec: Dict[str, Any],
|
endpoint_spec: Dict[str, Any], # 已经转换为字典
|
||||||
test_case_instance: Optional[BaseAPITestCase] = None
|
test_case_instance: Optional[BaseAPITestCase] = None # 传入测试用例实例以便访问其LLM配置
|
||||||
) -> Tuple[str, Dict[str, Any], Dict[str, Any], Dict[str, Any], Optional[Any]]:
|
) -> APIRequestContext: # 返回 APIRequestContext 对象
|
||||||
"""
|
"""
|
||||||
根据OpenAPI端点规格和测试用例实例准备初始请求数据。
|
根据API端点规范，准备初始的请求数据，包括URL（模板）、路径参数、查询参数、头部和请求体。
|
||||||
包含端点级别的LLM参数缓存逻辑。
|
这些数据将作为测试用例中 generate_* 方法的输入。
|
||||||
"""
|
"""
|
||||||
method = endpoint_spec.get("method", "get").upper()
|
method = endpoint_spec.get('method', 'GET').upper()
|
||||||
operation_id = endpoint_spec.get("operationId", f"{method}_{endpoint_spec.get('path', '')}")
|
path_template = endpoint_spec.get('path', '/') # 这是路径模板, e.g., /users/{id}
|
||||||
endpoint_cache_key = f"{method}_{endpoint_spec.get('path', '')}"
|
operation_id = endpoint_spec.get('operationId') or f"{method}_{path_template.replace('/', '_').replace('{', '_').replace('}','')}"
|
||||||
|
|
||||||
self.logger.info(f"[{operation_id}] 开始为端点 {endpoint_cache_key} 准备初始请求数据 (TC: {test_case_instance.id if test_case_instance else 'N/A'})")
|
initial_path_params: Dict[str, Any] = {}
|
||||||
|
initial_query_params: Dict[str, Any] = {}
|
||||||
|
initial_headers: Dict[str, str] = {}
|
||||||
|
initial_body: Optional[Any] = None
|
||||||
|
|
||||||
# 尝试从缓存加载参数
|
parameters = endpoint_spec.get('parameters', [])
|
||||||
if endpoint_cache_key in self.llm_endpoint_params_cache:
|
|
||||||
cached_params = self.llm_endpoint_params_cache[endpoint_cache_key]
|
|
||||||
self.logger.info(f"[{operation_id}] 从缓存加载了端点 '{endpoint_cache_key}' 的LLM参数。")
|
|
||||||
# 直接从缓存中获取各类参数，如果存在的话
|
|
||||||
path_params_data = cached_params.get("path_params", {})
|
|
||||||
query_params_data = cached_params.get("query_params", {})
|
|
||||||
headers_data = cached_params.get("headers", {})
|
|
||||||
body_data = cached_params.get("body") # Body可能是None
|
|
||||||
|
|
||||||
# 即使从缓存加载，仍需确保默认头部（如Accept, Content-Type）存在或被正确设置
|
# 1. 处理路径参数
|
||||||
# Content-Type应基于body_data是否存在来决定
|
path_param_specs = [p for p in parameters if p.get('in') == 'path']
|
||||||
default_headers = {"Accept": "application/json"}
|
for param_spec in path_param_specs:
|
||||||
if body_data is not None and method not in ["GET", "DELETE", "HEAD", "OPTIONS"]:
|
name = param_spec.get('name')
|
||||||
default_headers["Content-Type"] = "application/json"
|
if not name: continue
|
||||||
|
|
||||||
headers_data = {**default_headers, **headers_data} # 合并，缓存中的优先
|
should_use_llm = self._should_use_llm_for_param_type("path_params", test_case_instance)
|
||||||
|
if should_use_llm and self.llm_service:
|
||||||
|
self.logger.info(f"Attempting LLM generation for path parameter '{name}' in '{operation_id}'")
|
||||||
|
# generated_value = self.llm_service.generate_data_for_parameter(param_spec, endpoint_spec, "path")
|
||||||
|
# initial_path_params[name] = generated_value if generated_value is not None else f"llm_placeholder_for_{name}"
|
||||||
|
initial_path_params[name] = f"llm_path_{name}" # Placeholder
|
||||||
|
else:
|
||||||
|
if 'example' in param_spec:
|
||||||
|
initial_path_params[name] = param_spec['example']
|
||||||
|
elif param_spec.get('schema') and 'example' in param_spec['schema']:
|
||||||
|
initial_path_params[name] = param_spec['schema']['example'] # OpenAPI 3.0 `parameter.schema.example`
|
||||||
|
elif 'default' in param_spec.get('schema', {}):
|
||||||
|
initial_path_params[name] = param_spec['schema']['default']
|
||||||
|
elif 'default' in param_spec: # OpenAPI 2.0 `parameter.default`
|
||||||
|
initial_path_params[name] = param_spec['default']
|
||||||
|
else:
|
||||||
|
schema = param_spec.get('schema', {})
|
||||||
|
param_type = schema.get('type', 'string')
|
||||||
|
if param_type == 'integer': initial_path_params[name] = 123
|
||||||
|
elif param_type == 'number': initial_path_params[name] = 1.23
|
||||||
|
elif param_type == 'boolean': initial_path_params[name] = True
|
||||||
|
elif param_type == 'string' and schema.get('format') == 'uuid': initial_path_params[name] = str(UUID(int=0)) # Example UUID
|
||||||
|
elif param_type == 'string' and schema.get('format') == 'date': initial_path_params[name] = dt.date.today().isoformat()
|
||||||
|
elif param_type == 'string' and schema.get('format') == 'date-time': initial_path_params[name] = dt.datetime.now().isoformat()
|
||||||
|
else: initial_path_params[name] = f"param_{name}"
|
||||||
|
self.logger.debug(f"Initial path param for '{operation_id}': {name} = {initial_path_params.get(name)}")
|
||||||
|
|
||||||
self.logger.debug(f"[{operation_id}] (缓存加载) 准备的请求数据: method={method}, path_params={path_params_data}, query_params={query_params_data}, headers={list(headers_data.keys())}, body_type={type(body_data).__name__}")
|
# 2. 处理查询参数
|
||||||
return method, path_params_data, query_params_data, headers_data, body_data
|
query_param_specs = [p for p in parameters if p.get('in') == 'query']
|
||||||
|
for param_spec in query_param_specs:
|
||||||
|
name = param_spec.get('name')
|
||||||
|
if not name: continue
|
||||||
|
should_use_llm = self._should_use_llm_for_param_type("query_params", test_case_instance)
|
||||||
|
if should_use_llm and self.llm_service:
|
||||||
|
self.logger.info(f"Attempting LLM generation for query parameter '{name}' in '{operation_id}'")
|
||||||
|
initial_query_params[name] = f"llm_query_{name}" # Placeholder
|
||||||
|
else:
|
||||||
|
if 'example' in param_spec:
|
||||||
|
initial_query_params[name] = param_spec['example']
|
||||||
|
elif param_spec.get('schema') and 'example' in param_spec['schema']:
|
||||||
|
initial_query_params[name] = param_spec['schema']['example']
|
||||||
|
elif 'default' in param_spec.get('schema', {}):
|
||||||
|
initial_query_params[name] = param_spec['schema']['default']
|
||||||
|
elif 'default' in param_spec:
|
||||||
|
initial_query_params[name] = param_spec['default']
|
||||||
|
else:
|
||||||
|
initial_query_params[name] = f"query_val_{name}" # Simplified default
|
||||||
|
self.logger.debug(f"Initial query param for '{operation_id}': {name} = {initial_query_params.get(name)}")
|
||||||
|
|
||||||
# 缓存未命中，需要生成参数
|
# 3. 处理请求头参数 (包括规范定义的和标准的 Content-Type/Accept)
|
||||||
self.logger.info(f"[{operation_id}] 端点 '{endpoint_cache_key}' 的参数未在缓存中找到，开始生成。")
|
header_param_specs = [p for p in parameters if p.get('in') == 'header']
|
||||||
generated_params_for_endpoint: Dict[str, Any] = {}
|
for param_spec in header_param_specs:
|
||||||
|
name = param_spec.get('name')
|
||||||
|
if not name: continue
|
||||||
|
# 标准头 Content-Type 和 Accept 会在后面专门处理
|
||||||
|
if name.lower() in ['content-type', 'accept', 'authorization']:
|
||||||
|
self.logger.debug(f"Skipping standard header '{name}' in parameter processing for '{operation_id}'. It will be handled separately.")
|
||||||
|
continue
|
||||||
|
|
||||||
path_params_data: Dict[str, Any] = {}
|
should_use_llm = self._should_use_llm_for_param_type("headers", test_case_instance)
|
||||||
query_params_data: Dict[str, Any] = {}
|
if should_use_llm and self.llm_service:
|
||||||
headers_data_generated: Dict[str, Any] = {} # LLM或常规生成的，不含默认
|
self.logger.info(f"Attempting LLM generation for header '{name}' in '{operation_id}'")
|
||||||
body_data: Optional[Any] = None
|
initial_headers[name] = f"llm_header_{name}" # Placeholder
|
||||||
|
else:
|
||||||
|
if 'example' in param_spec:
|
||||||
|
initial_headers[name] = str(param_spec['example'])
|
||||||
|
elif param_spec.get('schema') and 'example' in param_spec['schema']:
|
||||||
|
initial_headers[name] = str(param_spec['schema']['example'])
|
||||||
|
elif 'default' in param_spec.get('schema', {}):
|
||||||
|
initial_headers[name] = str(param_spec['schema']['default'])
|
||||||
|
elif 'default' in param_spec:
|
||||||
|
initial_headers[name] = str(param_spec['default'])
|
||||||
|
else:
|
||||||
|
initial_headers[name] = f"header_val_{name}"
|
||||||
|
self.logger.debug(f"Initial custom header param for '{operation_id}': {name} = {initial_headers.get(name)}")
|
||||||
|
|
||||||
# 提取各类参数的定义列表
|
# 3.1 设置 Content-Type
|
||||||
path_params_spec_list = [p for p in endpoint_spec.get("parameters", []) if p.get("in") == "path"]
|
# 优先从 requestBody.content 获取 (OpenAPI 3.x)
|
||||||
query_params_spec_list = [p for p in endpoint_spec.get("parameters", []) if p.get("in") == "query"]
|
request_body_spec = endpoint_spec.get('requestBody', {})
|
||||||
headers_spec_list = [p for p in endpoint_spec.get("parameters", []) if p.get("in") == "header"]
|
if 'content' in request_body_spec:
|
||||||
request_body_spec = endpoint_spec.get("requestBody", {}).get("content", {}).get("application/json", {}).get("schema")
|
content_types = list(request_body_spec['content'].keys())
|
||||||
|
if content_types:
|
||||||
|
# 优先选择 application/json 如果存在
|
||||||
|
initial_headers['Content-Type'] = next((ct for ct in content_types if 'json' in ct.lower()), content_types[0])
|
||||||
|
elif 'consumes' in endpoint_spec: # 然后是 consumes (OpenAPI 2.0)
|
||||||
|
consumes = endpoint_spec['consumes']
|
||||||
|
if consumes:
|
||||||
|
initial_headers['Content-Type'] = next((c for c in consumes if 'json' in c.lower()), consumes[0])
|
||||||
|
elif method in ['POST', 'PUT', 'PATCH'] and not initial_headers.get('Content-Type'):
|
||||||
|
initial_headers['Content-Type'] = 'application/json' # 默认对于这些方法
|
||||||
|
self.logger.debug(f"Initial Content-Type for '{operation_id}': {initial_headers.get('Content-Type')}")
|
||||||
|
|
||||||
# --- 1. 处理路径参数 ---
|
# 3.2 设置 Accept
|
||||||
param_type_key = "path_params"
|
# 优先从 responses.<code>.content 获取 (OpenAPI 3.x)
|
||||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and path_params_spec_list:
|
responses_spec = endpoint_spec.get('responses', {})
|
||||||
self.logger.info(f"[{operation_id}] 尝试使用LLM生成路径参数。")
|
accept_header_set = False
|
||||||
object_schema, model_name = self._build_object_schema_for_params(path_params_spec_list, f"DynamicPathParamsFor_{operation_id}")
|
for code, response_def in responses_spec.items():
|
||||||
if object_schema and model_name:
|
if 'content' in response_def:
|
||||||
try:
|
accept_types = list(response_def['content'].keys())
|
||||||
PydanticModel = self._create_pydantic_model_from_schema(object_schema, model_name)
|
if accept_types:
|
||||||
if PydanticModel:
|
initial_headers['Accept'] = next((at for at in accept_types if 'json' in at.lower() or '*/*' in at), accept_types[0])
|
||||||
llm_generated = self.llm_service.generate_parameters_from_schema(
|
accept_header_set = True
|
||||||
PydanticModel,
|
break
|
||||||
prompt_instruction=f"Generate valid path parameters for API operation: {operation_id}. Description: {endpoint_spec.get('description', '') or endpoint_spec.get('summary', 'N/A')}"
|
if not accept_header_set and 'produces' in endpoint_spec: # 然后是 produces (OpenAPI 2.0)
|
||||||
)
|
produces = endpoint_spec['produces']
|
||||||
if isinstance(llm_generated, dict):
|
if produces:
|
||||||
path_params_data = llm_generated
|
initial_headers['Accept'] = next((p for p in produces if 'json' in p.lower() or '*/*' in p), produces[0])
|
||||||
self.logger.info(f"[{operation_id}] LLM成功生成路径参数: {path_params_data}")
|
accept_header_set = True
|
||||||
else:
|
if not accept_header_set and not initial_headers.get('Accept'):
|
||||||
self.logger.warning(f"[{operation_id}] LLM为路径参数返回了非字典类型: {type(llm_generated)}。回退到常规生成。")
|
initial_headers['Accept'] = 'application/json, */*' # 更通用的默认值
|
||||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
self.logger.debug(f"Initial Accept header for '{operation_id}': {initial_headers.get('Accept')}")
|
||||||
else:
|
|
||||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
|
||||||
except Exception as e:
|
|
||||||
self.logger.error(f"[{operation_id}] LLM生成路径参数失败: {e}。回退到常规生成。", exc_info=True)
|
|
||||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
|
||||||
else: # _build_object_schema_for_params 返回 None
|
|
||||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
|
||||||
else: # 不使用LLM或LLM服务不可用，或者 path_params_spec_list 为空但仍需确保path_params_data被赋值
|
|
||||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and not path_params_spec_list:
|
|
||||||
self.logger.info(f"[{operation_id}] 配置为路径参数使用LLM，但没有定义路径参数规格。")
|
|
||||||
# 对于不使用LLM或LLM不适用的情况，或者 spec_list 为空的情况，都执行常规生成（如果 spec_list 非空则会记录）
|
|
||||||
if path_params_spec_list and not self._should_use_llm_for_param_type(param_type_key, test_case_instance):
|
|
||||||
self.logger.info(f"[{operation_id}] 使用常规方法或LLM未启用，为路径参数。")
|
|
||||||
path_params_data = self._generate_params_from_list(path_params_spec_list, operation_id, "path")
|
|
||||||
generated_params_for_endpoint[param_type_key] = path_params_data
|
|
||||||
|
|
||||||
# --- 2. 处理查询参数 ---
|
# 4. 处理请求体 (Body)
|
||||||
param_type_key = "query_params"
|
request_body_schema: Optional[Dict[str, Any]] = None
|
||||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and query_params_spec_list:
|
# 确定请求体 schema 的来源，优先 OpenAPI 3.x 的 requestBody
|
||||||
self.logger.info(f"[{operation_id}] 尝试使用LLM生成查询参数。")
|
content_type_for_body_schema = initial_headers.get('Content-Type', 'application/json').split(';')[0].strip()
|
||||||
object_schema, model_name = self._build_object_schema_for_params(query_params_spec_list, f"DynamicQueryParamsFor_{operation_id}")
|
|
||||||
if object_schema and model_name:
|
|
||||||
try:
|
|
||||||
PydanticModel = self._create_pydantic_model_from_schema(object_schema, model_name)
|
|
||||||
if PydanticModel:
|
|
||||||
llm_generated = self.llm_service.generate_parameters_from_schema(
|
|
||||||
PydanticModel,
|
|
||||||
prompt_instruction=f"Generate valid query parameters for API operation: {operation_id}. Description: {endpoint_spec.get('description', '') or endpoint_spec.get('summary', 'N/A')}"
|
|
||||||
)
|
|
||||||
if isinstance(llm_generated, dict):
|
|
||||||
query_params_data = llm_generated
|
|
||||||
self.logger.info(f"[{operation_id}] LLM成功生成查询参数: {query_params_data}")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"[{operation_id}] LLM为查询参数返回了非字典类型: {type(llm_generated)}。回退到常规生成。")
|
|
||||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
|
||||||
else:
|
|
||||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
|
||||||
except Exception as e:
|
|
||||||
self.logger.error(f"[{operation_id}] LLM生成查询参数失败: {e}。回退到常规生成。", exc_info=True)
|
|
||||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
|
||||||
else: # _build_object_schema_for_params 返回 None
|
|
||||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
|
||||||
else: # 不使用LLM或LLM服务不可用，或者 query_params_spec_list 为空
|
|
||||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and not query_params_spec_list:
|
|
||||||
self.logger.info(f"[{operation_id}] 配置为查询参数使用LLM，但没有定义查询参数规格。")
|
|
||||||
if query_params_spec_list and not self._should_use_llm_for_param_type(param_type_key, test_case_instance):
|
|
||||||
self.logger.info(f"[{operation_id}] 使用常规方法或LLM未启用，为查询参数。")
|
|
||||||
query_params_data = self._generate_params_from_list(query_params_spec_list, operation_id, "query")
|
|
||||||
generated_params_for_endpoint[param_type_key] = query_params_data
|
|
||||||
|
|
||||||
# --- 3. 处理头部参数 ---
|
if 'content' in request_body_spec and content_type_for_body_schema in request_body_spec['content']:
|
||||||
param_type_key = "headers"
|
request_body_schema = request_body_spec['content'][content_type_for_body_schema].get('schema')
|
||||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and headers_spec_list:
|
elif 'parameters' in endpoint_spec: # OpenAPI 2.0 (Swagger) body parameter
|
||||||
self.logger.info(f"[{operation_id}] 尝试使用LLM生成头部参数。")
|
body_param = next((p for p in parameters if p.get('in') == 'body'), None)
|
||||||
object_schema, model_name = self._build_object_schema_for_params(headers_spec_list, f"DynamicHeadersFor_{operation_id}")
|
if body_param and 'schema' in body_param:
|
||||||
if object_schema and model_name:
|
request_body_schema = body_param['schema']
|
||||||
try:
|
|
||||||
PydanticModel = self._create_pydantic_model_from_schema(object_schema, model_name)
|
|
||||||
if PydanticModel:
|
|
||||||
llm_generated = self.llm_service.generate_parameters_from_schema(
|
|
||||||
PydanticModel,
|
|
||||||
prompt_instruction=f"Generate valid HTTP headers for API operation: {operation_id}. Description: {endpoint_spec.get('description', '') or endpoint_spec.get('summary', 'N/A')}"
|
|
||||||
)
|
|
||||||
if isinstance(llm_generated, dict):
|
|
||||||
headers_data_generated = llm_generated # Store LLM generated ones separately first
|
|
||||||
self.logger.info(f"[{operation_id}] LLM成功生成头部参数: {headers_data_generated}")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"[{operation_id}] LLM为头部参数返回了非字典类型: {type(llm_generated)}。回退到常规生成。")
|
|
||||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
|
||||||
else:
|
|
||||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
|
||||||
except Exception as e:
|
|
||||||
self.logger.error(f"[{operation_id}] LLM生成头部参数失败: {e}。回退到常规生成。", exc_info=True)
|
|
||||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
|
||||||
else: # _build_object_schema_for_params 返回 None
|
|
||||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
|
||||||
else: # 不使用LLM或LLM服务不可用，或者 headers_spec_list 为空
|
|
||||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and not headers_spec_list:
|
|
||||||
self.logger.info(f"[{operation_id}] 配置为头部参数使用LLM，但没有定义头部参数规格。")
|
|
||||||
if headers_spec_list and not self._should_use_llm_for_param_type(param_type_key, test_case_instance):
|
|
||||||
self.logger.info(f"[{operation_id}] 使用常规方法或LLM未启用，为头部参数。")
|
|
||||||
headers_data_generated = self._generate_params_from_list(headers_spec_list, operation_id, "header")
|
|
||||||
generated_params_for_endpoint[param_type_key] = headers_data_generated
|
|
||||||
|
|
||||||
# --- 4. 处理请求体 ---
|
if request_body_schema:
|
||||||
param_type_key = "body"
|
should_use_llm_for_body = self._should_use_llm_for_param_type("body", test_case_instance)
|
||||||
if self._should_use_llm_for_param_type(param_type_key, test_case_instance) and request_body_spec:
|
if should_use_llm_for_body and self.llm_service:
|
||||||
self.logger.info(f"[{operation_id}] 尝试使用LLM生成请求体。")
|
self.logger.info(f"Attempting LLM generation for request body of '{operation_id}' with schema...")
|
||||||
model_name = f"DynamicBodyFor_{operation_id}"
|
initial_body = self.llm_service.generate_data_from_schema(request_body_schema, endpoint_spec, "requestBody")
|
||||||
try:
|
if initial_body is None:
|
||||||
PydanticModel = self._create_pydantic_model_from_schema(request_body_spec, model_name)
|
self.logger.warning(f"LLM failed to generate request body for '{operation_id}'. Falling back to default schema generator.")
|
||||||
if PydanticModel:
|
initial_body = self._generate_data_from_schema(request_body_schema, context_name=f"{operation_id}_body", operation_id=operation_id)
|
||||||
llm_generated_body = self.llm_service.generate_parameters_from_schema(
|
else:
|
||||||
PydanticModel,
|
initial_body = self._generate_data_from_schema(request_body_schema, context_name=f"{operation_id}_body", operation_id=operation_id)
|
||||||
prompt_instruction=f"Generate a valid JSON request body for API operation: {operation_id}. Description: {endpoint_spec.get('description', '') or endpoint_spec.get('summary', 'N/A')}. Schema: {json.dumps(request_body_spec, indent=2)}"
|
self.logger.debug(f"Initial request body generated for '{operation_id}' (type: {type(initial_body)})")
|
||||||
)
|
else:
|
||||||
if isinstance(llm_generated_body, dict):
|
self.logger.debug(f"No request body schema found or applicable for '{operation_id}' with Content-Type '{content_type_for_body_schema}'. Initial body is None.")
|
||||||
try:
|
|
||||||
body_data = PydanticModel(**llm_generated_body).model_dump(by_alias=True)
|
|
||||||
self.logger.info(f"[{operation_id}] LLM成功生成并验证请求体。")
|
|
||||||
except ValidationError as ve:
|
|
||||||
self.logger.error(f"[{operation_id}] LLM生成的请求体未能通过Pydantic模型验证: {ve}。回退到常规生成。")
|
|
||||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
|
||||||
elif isinstance(llm_generated_body, BaseModel): # LLM直接返回模型实例
|
|
||||||
body_data = llm_generated_body.model_dump(by_alias=True)
|
|
||||||
self.logger.info(f"[{operation_id}] LLM成功生成请求体 (模型实例)。")
|
|
||||||
else:
|
|
||||||
self.logger.warning(f"[{operation_id}] LLM为请求体返回了非预期类型: {type(llm_generated_body)}。回退到常规生成。")
|
|
||||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
|
||||||
else: # _create_pydantic_model_from_schema 返回 None
|
|
||||||
self.logger.warning(f"[{operation_id}] 未能为请求体创建Pydantic模型。回退到常规生成。")
|
|
||||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
|
||||||
except Exception as e:
|
|
||||||
self.logger.error(f"[{operation_id}] LLM生成请求体失败: {e}。回退到常规生成。", exc_info=True)
|
|
||||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
|
||||||
elif request_body_spec: # 不使用LLM但有body spec
|
|
||||||
self.logger.info(f"[{operation_id}] 使用常规方法或LLM未启用/不适用，为请求体。")
|
|
||||||
body_data = self._generate_data_from_schema(request_body_spec, "requestBody", operation_id)
|
|
||||||
else: # 没有requestBody定义
|
|
||||||
self.logger.info(f"[{operation_id}] 端点没有定义请求体。")
|
|
||||||
body_data = None # 明确设为None
|
|
||||||
generated_params_for_endpoint[param_type_key] = body_data
|
|
||||||
|
|
||||||
# 合并最终的头部 (默认头部 + 生成的头部)
|
# 构造并返回APIRequestContext
|
||||||
final_headers = {"Accept": "application/json"}
|
return APIRequestContext(
|
||||||
if body_data is not None and method not in ["GET", "DELETE", "HEAD", "OPTIONS"]:
|
method=method,
|
||||||
final_headers["Content-Type"] = "application/json"
|
url=path_template, # 传递路径模板, e.g. /items/{itemId}
|
||||||
final_headers.update(headers_data_generated) # headers_data_generated 是从LLM或常规生成的
|
path_params=initial_path_params,
|
||||||
|
query_params=initial_query_params,
|
||||||
# 将本次生成的所有参数存入缓存
|
headers=initial_headers,
|
||||||
self.llm_endpoint_params_cache[endpoint_cache_key] = generated_params_for_endpoint
|
body=initial_body,
|
||||||
self.logger.info(f"[{operation_id}] 端点 '{endpoint_cache_key}' 的参数已生成并存入缓存。")
|
endpoint_spec=endpoint_spec # 传递原始的 endpoint_spec 字典
|
||||||
|
)
|
||||||
# 确保路径参数中的值都是字符串 (URL部分必须是字符串)
|
|
||||||
path_params_data_str = {k: str(v) if v is not None else "" for k, v in path_params_data.items()}
|
|
||||||
|
|
||||||
self.logger.debug(f"[{operation_id}] (新生成) 准备的请求数据: method={method}, path_params={path_params_data_str}, query_params={query_params_data}, headers={list(final_headers.keys())}, body_type={type(body_data).__name__}")
|
|
||||||
return method, path_params_data_str, query_params_data, final_headers, body_data
|
|
||||||
|
|
||||||
def _build_object_schema_for_params(self, params_spec_list: List[Dict[str, Any]], model_name_base: str) -> Tuple[Optional[Dict[str, Any]], str]:
|
def _build_object_schema_for_params(self, params_spec_list: List[Dict[str, Any]], model_name_base: str) -> Tuple[Optional[Dict[str, Any]], str]:
|
||||||
"""
|
"""
|
||||||
@ -1490,4 +1465,34 @@ class APITestOrchestrator:
|
|||||||
self.logger.debug(f"{log_prefix}_generate_data_from_schema: 未知或不支持的 schema 类型 '{schema_type}' for{context_log}. Schema: {schema}")
|
self.logger.debug(f"{log_prefix}_generate_data_from_schema: 未知或不支持的 schema 类型 '{schema_type}' for{context_log}. Schema: {schema}")
|
||||||
return None
|
return None
|
||||||
|
|
||||||
|
def _format_url_with_path_params(self, path_template: str, path_params: Dict[str, Any]) -> str:
|
||||||
|
"""
|
||||||
|
使用提供的路径参数格式化URL路径模板。
|
||||||
|
例如: path_template='/users/{userId}/items/{itemId}', path_params={'userId': 123, 'itemId': 'abc'}
|
||||||
|
会返回 '/users/123/items/abc'
|
||||||
|
同时处理 base_url.
|
||||||
|
"""
|
||||||
|
# 首先确保 path_template 不以 '/' 开头，如果 self.base_url 已经以 '/' 结尾
|
||||||
|
# 或者确保它们之间只有一个 '/'
|
||||||
|
formatted_path = path_template
|
||||||
|
for key, value in path_params.items():
|
||||||
|
placeholder = f"{{{key}}}"
|
||||||
|
if placeholder in formatted_path:
|
||||||
|
formatted_path = formatted_path.replace(placeholder, str(value))
|
||||||
|
else:
|
||||||
|
self.logger.warning(f"路径参数 '{key}' 在路径模板 '{path_template}' 中未找到占位符。")
|
||||||
|
|
||||||
|
# 拼接 base_url 和格式化后的路径
|
||||||
|
# 确保 base_url 和 path 之间只有一个斜杠
|
||||||
|
if self.base_url.endswith('/') and formatted_path.startswith('/'):
|
||||||
|
url = self.base_url + formatted_path[1:]
|
||||||
|
elif not self.base_url.endswith('/') and not formatted_path.startswith('/'):
|
||||||
|
if formatted_path: # 避免在 base_url 后添加不必要的 '/' (如果 formatted_path 为空)
|
||||||
|
url = self.base_url + '/' + formatted_path
|
||||||
|
else:
|
||||||
|
url = self.base_url
|
||||||
|
else:
|
||||||
|
url = self.base_url + formatted_path
|
||||||
|
return url
|
||||||
|
|
||||||
|
|
||||||
|
|||||||
953
test_report.json
953
test_report.json
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Reference in New Issue
Block a user