CNWei
00791809df
- 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。
196 lines
6.9 KiB
Python
196 lines
6.9 KiB
Python
#!/usr/bin/env python
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# coding=utf-8
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"""
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@desc: 变量交换器，用于数据替换和提取
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"""
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import logging
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import re
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from typing import Any, Union, TypeVar
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import jsonpath
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from lxml import etree
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from core.models import RawSchema
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from core.settings import EXTRACT_CACHE
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from core.templates import Template
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from commons.file_processors.yaml_processor import YamlProcessor
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logger = logging.getLogger(__name__)
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# 定义泛型，用于保持返回类型一致
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T = TypeVar("T", bound=Union[dict, list, str, Any])
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class Exchange:
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def __init__(self, variable_cache: dict[str, Any]):
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self._cache = variable_cache
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# 匹配标准变量 ${var}，排除函数调用 ${func()}
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self.var_only_pattern = re.compile(r"^\$\{([a-zA-Z_]\w*)}$")
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@property
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def global_vars(self) -> dict:
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return self._cache
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@global_vars.setter
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def global_vars(self, global_vars: dict) -> None:
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self._cache = global_vars
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def extract(self, resp: Any, var_name: str, attr: str, expr: str, index: int = 0):
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"""
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从响应中提取数据并更新到缓存及文件
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:param resp: Response 对象
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:param var_name: 变量名
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:param attr: 属性名 (json, text, headers 等)
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:param expr: 提取表达式 ($.jsonpath, //xpath, regex)
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:param index: 索引
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"""
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try:
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# 兼容处理 resp.json
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target_data = getattr(resp, attr, None)
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if attr == "json":
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try:
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target_data = resp.json()
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except Exception:
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target_data = {"msg": "not json data"}
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if target_data is None:
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logger.warning(f"提取失败: 响应对象中不存在属性 '{attr}'")
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return
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value = None
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if expr.startswith("$"): # JSONPath
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res = jsonpath.jsonpath(target_data, expr)
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if res: value = res[index]
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elif expr.startswith("/") or expr.startswith("./"): # XPath 模式
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html_content = getattr(resp, "text", "") # 使用 getattr 防护
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if not html_content:
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logger.warning("XPath 提取失败：响应文本为空")
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return
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# 将文本解析为 HTML 树
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# html_content = resp.text
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tree = etree.HTML(html_content)
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res = tree.xpath(expr)
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if res:
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# 获取节点文本或属性值
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target_node = res[index]
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value = target_node.text if hasattr(target_node, 'text') else str(target_node)
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else: # 正则
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res = re.findall(expr, str(target_data))
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if res: value = res[index]
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if value is None:
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logger.warning(f"变量 [{var_name}] 未通过表达式 [{expr}] 提取到数据")
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value = "not data"
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self._cache[var_name] = value
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logger.info(f"变量提取成功: {var_name} -> {value} (Type: {type(value).__name__})")
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except Exception as e:
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logger.error(f"提取变量 [{var_name}] 过程中发生异常: {e}", exc_info=True)
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def _smart_replace(self, content: Any) -> Any:
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"""
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递归替换逻辑：
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- 如果是纯变量占位符 ${token}，则返回变量在缓存中的原始类型 (int, dict, list 等)
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- 如果是混合字符串或函数调用，则调用 Template 渲染为字符串
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"""
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if isinstance(content, dict):
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return {k: self._smart_replace(v) for k, v in content.items()}
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elif isinstance(content, list):
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return [self._smart_replace(i) for i in content]
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elif isinstance(content, str):
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# A. 场景：纯变量（为了保持类型，不走 Template 渲染成字符串）
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# 例子：content = "${order_id}"，如果 order_id 是 int 123，则返回 123
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full_match = self.var_only_pattern.fullmatch(content)
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if full_match:
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var_name = full_match.group(1)
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return self._cache.get(var_name, content)
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# B. 场景：混合文本或函数调用
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# 例子："Bearer ${token}" 或 "${gen_phone()}"
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if "${" in content:
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# 调用你提供的 Template 类
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return Template(content).render(self._cache)
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return content
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def replace(self, data: T) -> T:
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"""
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通用的变量替换入口
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支持输入 dict, list, str 或 Pydantic Model (需先 dump)
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"""
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if not data:
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return data
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logger.debug(f"开始变量替换，原始数据类型: {type(data).__name__}")
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rendered_data = self._smart_replace(data)
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return rendered_data
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if __name__ == "__main__":
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from core.models import RawSchema, HttpAction
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file_handler = YamlProcessor(filepath=EXTRACT_CACHE)
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variable_cache_ = file_handler.load() or {}
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ex = Exchange(variable_cache_)
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# --- 场景 1: 变量提取验证 ---
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class MockResponse:
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def __init__(self):
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self.json_data = {"data": {"token": "auth_123", "user_id": 888}}
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self.text = "<html><body><div id='name'>ChenWei</div></body></html>"
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def json(self): return self.json_data
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mock_resp = MockResponse()
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print(">>> 执行提取...")
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ex.extract(mock_resp, "token", "json", "$.data.token")
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ex.extract(mock_resp, "u_id", "json", "$.data.user_id")
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ex.extract(mock_resp, "user_name", "text", "//div[@id='name']")
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# --- 场景 2: 变量替换与类型保持 ---
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# 定义一个复杂的 CaseInfo
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raw_case = {
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"title": "测试用例",
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"action": {
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"method": "POST",
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"url": "http://api.com/${token}", # 混合文本 -> 应转为 str
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"json_body": {
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"id": "${u_id}", # 纯变量 -> 应保持 int
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"name": "${user_name}", # 纯变量 -> str
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"config": "${existing_var}" # 初始文件变量 -> int
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},
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"timeout": "${existing_var}" # 字符串形式的数字 -> Pydantic 应转回 int
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}
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}
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print("\n>>> 执行替换...")
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new_case_one = ex.replace(raw_case)
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print(new_case_one)
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RawSchema(**new_case_one)
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print(new_case_one.get("action"))
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action = HttpAction(**new_case_one.get("action"))
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print(action)
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# # --- 校验结果 ---
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print("\n--- 验证结果 ---")
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print(f"URL (混合文本): {action.url} | 类型: {type(action.url)}")
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print(f"ID (类型保持): {action.json_body['id']} | 类型: {type(action.json_body['id'])}")
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print(f"Timeout (自动转换): {action.timeout} | 类型: {type(action.timeout)}")
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# #
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assert isinstance(action.json_body['id'], int)
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# #
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assert action.url == "http://api.com/auth_123"
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assert action.timeout == 100
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print("\nExchange 场景全部验证通过！")
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