fix(exchange,case_validator),refactor(),feat(model): 解决 Pydantic 模型初始化与变量占位符的类型冲突,优化变量替换逻辑,重构 CaseInfo 模型并引入延迟校验机制
- 引入 SmartInt 和 SmartDict 类型，支持 YAML 占位符与业务类型的自动转换。 - 优化 CaseInfo 互斥校验逻辑，确保 request 与 api_action 二选一。 - 统一使用 Pydantic V2 的 model_config 规范。 - 将变量替换时机提前至模型实例化之前，支持占位符在校验前完成真实值注入， 保证了 int/bool 等字段的类型转换正确性。 - 优化断言渲染时机，支持响应提取值关联。
This commit is contained in:
180
core/creator.py
180
core/creator.py
@@ -12,14 +12,16 @@
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import logging
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import allure
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import pytest
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from pathlib import Path
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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 commons.exchange import Exchange
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from commons.file_processors.yaml_processor import YamlProcessor as FileHandle
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from typing import Any, Dict, List, Type, Generator, Tuple
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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 typing import Any, List, Type, Generator, Union
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logger = logging.getLogger(__name__)
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@@ -39,29 +41,107 @@ class TestTemplateBase:
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class CaseDataLoader:
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"""
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职责 1: 数据加载器
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负责与底层存储（YAML文件）打交道，输出标准化的原始数据对象
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测试用例加载器
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职责：扫描文件系统 -> 载入 YAML -> 拆解参数化 -> 封装为 CaseInfo 模型
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"""
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@staticmethod
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def fetch_yaml_cases(cases_dir: str) -> Generator[Tuple[Path, Dict], None, None]:
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def fetch_yaml_files(cases_dir: str) -> 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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yaml_files = Path(cases_dir).glob("**/test_*.yaml")
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for file_path in yaml_files:
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yield file_path, FileHandle(file_path)
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base_path = Path(cases_dir)
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if not base_path.exists():
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logger.error(f"📂 测试目录不存在: {base_path}")
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return
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# 匹配所有以 test_ 开头的 yaml 文件
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yield from base_path.rglob("test_*.yaml")
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@classmethod
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def load_cases(cls, file_path: Path) -> List[CaseInfo]:
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"""
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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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cases = []
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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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raw_data = processor.load()
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if not raw_data:
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return []
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# 2. 检查是否存在参数化字段
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if "parametrize" in raw_data and isinstance(raw_data["parametrize"], list):
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cases.extend(cls._parse_parametrize(raw_data))
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else:
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# 3. 普通单条用例封装
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cases.append(CaseInfo(**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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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 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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def _parse_parametrize(raw_data: dict[str, Any]) -> List[CaseInfo]:
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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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# 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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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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# 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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@classmethod
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def get_all_cases(cls, cases_dir: Union[str, Path]) -> List[CaseInfo]:
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"""
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全量获取接口：供 CaseGenerator 调用
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"""
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all_cases = []
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for file in cls.fetch_yaml_files(cases_dir):
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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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@@ -73,43 +153,56 @@ class CaseGenerator:
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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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# 1. 通过 Loader 获取数据
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for file_path, raw_data in CaseDataLoader.fetch_yaml_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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# 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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# 4. 挂载
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method_name = f"test_{file_path.stem}"
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setattr(target_cls, method_name, dynamic_test_method)
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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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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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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(case_template: Dict, fields: List[str], values: List[Any], ids: List[str]):
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def _create_case_method(case_template: CaseInfo):
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"""封装具体的 pytest 执行节点"""
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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.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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# @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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# 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 = case_template.title or "未命名用例"
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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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# 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_exec_data)
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executor.perform(case_template)
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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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@@ -120,5 +213,8 @@ 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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# --- 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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