feat(core): 增强 Exchange，实现智能变量替换与类型保持
- 优化 conftest.py 增加异常日志记录和测试报告环境信息 - 其他优化
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@@ -1,80 +0,0 @@
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#!/usr/bin/env python
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# coding=utf-8
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"""
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@author: CNWei
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@Software: PyCharm
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@contact: t6i888@163.com
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@file: case_handler
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@date: 2025/5/26 22:13
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@desc:
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"""
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import json
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import logging
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from dataclasses import dataclass, asdict
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from commons.models import TestCaseModel
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logger = logging.getLogger(__name__)
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@dataclass
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class TestCaseHandle(TestCaseModel):
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@classmethod
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def new(cls, testcase: dict) -> 'TestCaseHandle':
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try:
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instance = cls(**testcase)
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return instance
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except (TypeError, ValueError) as e:
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logger.warning(f"解析错误：{e}")
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raise e
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def to_string(self) -> str:
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"""
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将 字典 转换为 json 格式的字符串。
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:return:
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json 格式的字符串。
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"""
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try:
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res = json.dumps(asdict(self), ensure_ascii=False)
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return res
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except TypeError as e:
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logger.error(f"将数据转换为 json 字符串时出错: {e}")
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raise e
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@staticmethod
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def to_dict(json_str: str) -> dict:
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"""
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将 json 格式的字符串转换为 字典.
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:param
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json_str: json 格式的字符串。
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:return:
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"""
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try:
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res = json.loads(json_str)
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return res
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except json.JSONDecodeError as e:
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logger.error(f"将 json 字符串转换为字典时出错: {e}")
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raise e
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if __name__ == '__main__':
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from pathlib import Path
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from commons.file_processors import processor_factory
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test_data = Path(r"E:\PyP\InterfaceAutoTest\TestCases\test_1_user.yaml")
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yaml_data = processor_factory.get_processor_class(test_data)
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case_info = TestCaseHandle.new(yaml_data.load())
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print(case_info.to_string())
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print(type(case_info.to_string()))
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print(case_info.to_dict(case_info.to_string()))
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print(type(case_info.to_dict(case_info.to_string())))
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print(type(case_info))
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print(case_info.parametrize)
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for i in case_info.parametrize:
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print(i)
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@@ -1,98 +0,0 @@
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#!/usr/bin/env python
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# coding=utf-8
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"""
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@author: chen wei
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@Software: PyCharm
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@contact: t6i888@163.com
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@file: files.py
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@date: 2024 2024/9/15 21:28
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@desc: 读取和保存yaml文件
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"""
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import logging
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from pathlib import Path
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import yaml
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logger = logging.getLogger(__name__)
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class YamlFile(dict):
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def __init__(self, path=None, data=None):
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super().__init__()
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self.path = Path(path) if path else None
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if data:
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self.update(data)
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elif self.path:
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if self.path.is_dir():
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raise IsADirectoryError(f"The path {self.path} is a directory, not a file.")
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self.load()
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def load(self):
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if not self.path:
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logger.warning("No path specified for YamlFile, cannot load.")
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return self
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if self.path.exists() and self.path.is_file():
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with open(self.path, "r", encoding="utf-8") as f:
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loaded_data = yaml.safe_load(f) or {}
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self.clear()
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self.update(loaded_data)
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else:
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logger.warning(f"File not found at {self.path}, YamlFile initialized as empty.")
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self.clear()
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return self
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def to_yaml(self) -> str:
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return yaml.safe_dump(
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dict(self),
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allow_unicode=True,
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sort_keys=False
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)
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@classmethod
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def by_yaml(cls, yaml_str):
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data = yaml.safe_load(yaml_str) or {}
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return cls(data=data)
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def save(self):
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if not self.path:
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raise ValueError("Cannot save YamlFile instance without a specified path.")
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# 确保父目录存在
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self.path.parent.mkdir(parents=True, exist_ok=True)
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with open(self.path, "w", encoding="utf-8") as f:
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yaml.safe_dump(
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dict(self),
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stream=f,
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allow_unicode=True,
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sort_keys=False
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)
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return self
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if __name__ == '__main__':
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from core.models import CaseInfo
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from core.settings import TEST_CASE_DIR
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# 1. 创建一个用于测试的临时yaml文件
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dummy_path = TEST_CASE_DIR / "test_model_demo.yaml"
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dummy_data = {
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"title": "Get user info",
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"request": {"method": "GET", "url": "/users/1"},
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"validate": [{"equals": ["status_code", 200]}]
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}
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YamlFile(path=dummy_path, data=dummy_data).save()
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print(f"--- 已创建临时测试文件: {dummy_path}")
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# 2. 加载文件并使用Pydantic模型进行校验
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yaml_case = YamlFile(dummy_path)
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print("\n--- 已加载YAML内容 ---\n", yaml_case.to_yaml())
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case_model = CaseInfo(**yaml_case)
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print("\n--- Pydantic模型校验成功 ---")
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print(case_model.model_dump_json(indent=2, by_alias=True))
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# 3. 清理临时文件
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dummy_path.unlink()
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print(f"\n--- 已清理临时文件: {dummy_path}")
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