refactor: 重构执行引擎为上下文驱动架构
- 优化 WorkflowExecutor 与 Exchange支持 ExecutionEnv 资源注入。 - 实现 Session 级别连接复用与变量池内存镜像化，消除重复 I/O 开销。 - 引入 ChainMap 实现动态上下文切换，解决参数化变量与全局提取变量的优先级覆盖。 - 完善变量提取与断言逻辑，确保跨用例变量流转的可靠性。
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170
core/creator.py
170
core/creator.py
@@ -16,25 +16,20 @@ from pathlib import Path
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from dataclasses import dataclass
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from core import settings
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from core.executor import WorkflowExecutor
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from core.session import Session
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from core.exchange import Exchange
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from pydantic import ValidationError
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from commons.file_processors.yaml_processor import YamlProcessor as FileHandle,YamlLoadError
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from core.models import CaseInfo # 导入之前定义的 Pydantic 模型
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from commons.file_processors.yaml_processor import YamlProcessor as FileHandle, YamlLoadError
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from core.models import RawSchema # 导入之前定义的 Pydantic 模型
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from typing import Any, List, Type, Generator, Union
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logger = logging.getLogger(__name__)
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# 初始化全局组件
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session = Session(settings.base_url)
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exchanger = Exchange(settings.DATA_DIR / "extract.yaml") # 指向 data/extract.yaml
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executor = WorkflowExecutor(session, exchanger)
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@dataclass
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class CaseEntity:
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"""用例执行实体：解耦模型数据与执行上下文"""
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step_data: CaseInfo
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step_data: RawSchema
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row_context: dict[str, Any]
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@@ -53,7 +48,7 @@ class CaseDataLoader:
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"""
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@staticmethod
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def fetch_yaml_files(cases_dir: str) -> Generator[Path, None, None]:
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def fetch_yaml_files(cases_dir: Union[str, Path]) -> Generator[Path, None, None]:
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"""扫描目录并迭代返回 (文件路径, 原始内容)"""
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base_path = Path(cases_dir)
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if not base_path.exists():
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@@ -68,7 +63,7 @@ class CaseDataLoader:
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加载单个 YAML 文件并转化为 CaseInfo 列表
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包含参数化数据的自动拆解逻辑
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"""
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entities = []
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entities: List[CaseEntity] = []
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try:
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# 1. 使用重构后的 YamlProcessor 加载原始字典
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processor = FileHandle(file_path)
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@@ -76,67 +71,45 @@ class CaseDataLoader:
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if not raw_data:
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return []
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# 1. 提取参数化数据
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parametrize_data = raw_data.pop("parametrize", None)
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# 2. 实例化唯一的模板对象 (Pydantic 校验)
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# 此时占位符 ${var} 会被 SmartInt/SmartDict 校验器放行
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template_case = CaseInfo(**raw_data)
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# 2. 检查是否存在参数化字段
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if parametrize_data and isinstance(parametrize_data, list) and len(parametrize_data) >= 2:
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# 3. 参数化拆分
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headers = parametrize_data[0]
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for row in parametrize_data[1:]:
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row_map = dict(zip(headers, row))
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# 包装为实体，存入引用而非副本
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entities.append(CaseEntity(step_data=template_case, row_context=row_map))
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else:
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# 普通用例，上下文为空
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entities.append(CaseEntity(step_data=template_case, row_context={}))
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entities = cls._parse_parametrize(raw_data)
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except YamlLoadError:
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# YamlProcessor 已经记录了 error 日志，这里直接跳过
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pass
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except ValidationError as e:
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logger.error(f"用例格式校验失败 [{file_path.name}]:\n{e.json()}")
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logger.error(f"用例基础格式校验失败 [{file_path.name}]:\n{e.json()}")
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except Exception as e:
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logger.error(f"加载用例发生未知异常 [{file_path.name}]: {e}")
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return entities
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@staticmethod
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def _parse_parametrize(raw_data: dict[str, Any]) -> List[CaseInfo]:
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def _parse_parametrize(raw_data: dict[str, Any]) -> List[CaseEntity]:
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"""
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解析参数化逻辑：将 raw_data 中的 parametrize 展开为多个 CaseInfo 实例
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"""
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param_content = raw_data.pop("parametrize")
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if len(param_content) < 2:
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logger.warning(f"参数化数据不足（需包含 Header 和至少一行 Data）: {raw_data.get('title')}")
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return [CaseInfo(**raw_data)]
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entities = []
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parametrize_data = raw_data.pop("parametrize", None)
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# 第一行作为变量名 (Headers)，后续作为数据行
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headers = param_content[0]
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data_rows = param_content[1:]
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# 2. 实例化唯一的模板对象 (Pydantic 校验)
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template_case = RawSchema.model_validate(raw_data)
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# template_case = CaseTemplate(**raw_data)
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case_list = []
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for row in data_rows:
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# 将变量名和对应行数据打包成字典，例如 {"username": "user1", "title": "测试1"}
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row_map = dict(zip(headers, row))
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# 2. 检查是否存在参数化字段
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if parametrize_data and isinstance(parametrize_data, list) and len(parametrize_data) >= 2:
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# 3. 参数化拆分
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headers = parametrize_data[0]
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for row in parametrize_data[1:]:
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row_map = dict(zip(headers, row))
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# 包装为实体，存入引用而非副本
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# 修正: 使用 model_copy() 避免多个用例共享同一个 Pydantic 模型实例，防止意外修改
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entities.append(CaseEntity(step_data=template_case.model_copy(), row_context=row_map))
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else:
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# 普通用例，上下文为空
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entities.append(CaseEntity(step_data=template_case.model_copy(), row_context={}))
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# 深拷贝原始模板，避免多行数据互相干扰
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case_tmp = raw_data.copy()
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# 关键优化：如果参数化里包含 'title'，自动更新顶层的 title 字段
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# 注意：此处仅做初步合并，更复杂的 ${var} 替换由 WorkflowExecutor 的 Exchanger 完成
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if "title" in row_map:
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case_tmp["title"] = row_map["title"]
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# 将当前行的数据注入到 CaseInfo 中（此处可以暂存在字段中，或由执行器处理）
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# 为了保持模型兼容，我们把 row_map 的信息合入 case_tmp
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case_list.append(CaseInfo(**case_tmp))
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return case_list
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return entities
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@classmethod
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def get_all_cases(cls, cases_dir: Union[str, Path]) -> List[CaseEntity]:
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@@ -149,19 +122,6 @@ class CaseDataLoader:
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all_cases.extend(cls.load_cases(file))
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return all_cases
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# @staticmethod
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# def parse_parametrize(raw_data: Dict, default_name: str) -> Tuple[List[str], List[List[Any]], List[str]]:
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# """解析参数化结构，返回 (字段名列表, 数据值列表, ID列表)"""
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# if "parametrize" in raw_data:
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# fields = raw_data["parametrize"][0]
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# values = raw_data["parametrize"][1:]
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# ids = [f"{v[0]}" for v in values]
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# else:
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# fields = ["case_data"]
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# values = [[raw_data]]
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# ids = [raw_data.get("title", default_name)]
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# return fields, values, ids
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class CaseGenerator:
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"""
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@@ -170,67 +130,43 @@ class CaseGenerator:
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"""
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@classmethod
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def build_and_register(cls, target_cls: Type[TestTemplateBase], cases_dir: str):
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def build_and_register(cls, target_cls: Type[TestTemplateBase], cases_dir: Union[str, Path]):
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# 1. 通过 Loader 获取数据
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all_cases=CaseDataLoader.get_all_cases(cases_dir)
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all_cases = CaseDataLoader.get_all_cases(cases_dir)
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for index, case_info in enumerate(all_cases):
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dynamic_test_method=cls._create_case_method(case_info)
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# for file_path, raw_data in CaseDataLoader.get_all_cases(cases_dir):
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# # 2. 解析参数化信息
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# fields, values, ids = CaseDataLoader.parse_parametrize(raw_data, file_path.stem)
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#
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# # 3. 生成执行函数 (闭包)
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# dynamic_test_method = cls._create_case_method(raw_data, fields, values, ids)
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#
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# # 4. 挂载
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# method_name = f"test_{file_path.stem}"
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case_title = case_info.row_context.get("title") or case_info.step_data.title
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method_name = f"test_case_{index}_{case_info.title[:20]}"
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safe_name = "".join([c if c.isalnum() else "_" for c in method_name])
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# setattr(target_cls, method_name, dynamic_test_method)
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setattr(target_cls, safe_name, dynamic_test_method)
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dynamic_test_method = cls._create_case_method(title=case_title, entity=case_info)
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safe_title = "".join([c if c.isalnum() else "_" for c in case_title])[:50]
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method_name = f"test_{index:03d}_{safe_title}"
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print(method_name)
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setattr(target_cls, method_name, dynamic_test_method)
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print(target_cls.__dict__)
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logger.debug(f"Successfully registered: {method_name}")
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@staticmethod
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# def _create_case_method(case_template: Dict, fields: List[str], values: List[Any], ids: List[str]):
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def _create_case_method(entity: CaseEntity):
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def _create_case_method(title, entity: CaseEntity):
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"""封装具体的 pytest 执行节点"""
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case_template = entity.step_data
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context = entity.row_context
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# 预取 Allure 层级信息
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# epic = case_template.get("epic", settings.allure_epic)
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# feature = case_template.get("feature", settings.allure_feature)
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# story = case_template.get("story", settings.allure_story)
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epic = case_template.epic or settings.allure_epic
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feature = case_template.feature or settings.allure_feature
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story = case_template.story or settings.allure_story
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@allure.epic(epic)
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@allure.feature(feature)
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@allure.story(story)
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# @pytest.mark.parametrize("case_args", values, ids=ids)
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# def build_actual_case(instance: TestTemplateBase, case_args: List[Any]):
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def build_actual_case(instance: TestTemplateBase):
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# 数据组装
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# current_params = dict(zip(fields, case_args))
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# case_exec_data = {**case_template, **current_params}
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# case_title = current_params.get("title", "未命名用例")
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case_title = context.get("title") or case_template.title or "未命名用例"
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def build_actual_case(instance: TestTemplateBase, api_env):
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# --- 1. 动态设置 Allure 报告属性 ---
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allure.dynamic.epic(case_template.epic or settings.allure_epic)
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allure.dynamic.feature(case_template.feature or settings.allure_feature)
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allure.dynamic.story(case_template.story or settings.allure_story)
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allure.dynamic.title(title)
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# 日志记录 (利用 instance 标注来源)
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logger.info(f"🚀 [Runner] Class: {instance.__class__.__name__} | Case: {case_title}")
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logger.info(f"[Runner] Class: {instance.__class__.__name__} | Case: {title}")
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try:
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WorkflowExecutor.perform(case_template, api_env, context=context)
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# 执行与断言
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allure.dynamic.title(case_title)
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# executor.perform(case_exec_data)
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executor.perform(case_template,context=context)
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# 手动链路装饰 (Allure)
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# run_actual_case = allure.epic(epic)(run_actual_case)
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# run_actual_case = allure.feature(feature)(run_actual_case)
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# run_actual_case = allure.story(story)(run_actual_case)
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except Exception as e:
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# 可以在这里记录更详细的运行上下文快照
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logger.error(f"Case 执行失败: {title} | 错误: {e}")
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raise
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return build_actual_case
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@@ -238,6 +174,6 @@ class CaseGenerator:
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if __name__ == '__main__':
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from settings import TEST_CASE_DIR
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print(CaseDataLoader.get_all_cases(TEST_CASE_DIR))
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# print(CaseDataLoader.get_all_cases(TEST_CASE_DIR))
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# --- 引导执行 ---
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# CaseGenerator.build_and_register(TestTemplateBase, settings.TEST_CASE_DIR)
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CaseGenerator.build_and_register(TestTemplateBase, settings.TEST_CASE_DIR)
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