805 lines
30 KiB
Python
805 lines
30 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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脚本处理器模块
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提供脚本执行和变量设置的处理器
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"""
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#
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# import logging
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# from typing import Dict, Any
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# from services.execution.task_context import TaskContext
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# from utils.logger import get_logger
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# from .model.block_name import ScriptBlockName
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# from .base import BlockHandler, register_handler
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#
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#
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# # 获取日志记录器
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# logger = get_logger("services.execution.handlers.script")
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#
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#
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# # 脚本块处理器
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# @register_handler(ScriptBlockName.SET_TASK_VARIABLES)
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# class SetTaskVariablesBlockHandler(BlockHandler):
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# """设置任务变量块处理器"""
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#
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# async def execute(
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# self,
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# block: Dict[str, Any],
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# input_params: Dict[str, Any],
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# context: TaskContext
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# ) -> Dict[str, Any]:
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# """执行设置任务变量块"""
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# try:
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# # 获取函数名和参数
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# function_name = input_params.get("functionName")
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# function_args = input_params.get("functionArgs", {})
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#
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# if not function_name:
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# result = {
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# "success": False,
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# "message": "缺少函数名"
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# }
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# # 记录执行结果
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# await self._record_task_log(block, result, context)
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# return result
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#
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# # 参数类型验证和转换
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# function_args = self._validate_and_convert_args(function_args)
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#
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# # 调用脚本执行方法
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# logger.info("进入执行脚本功能块")
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# exec_result = await self._execute_script(function_name, function_args, context)
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# # print(exec_result, "=------------------=-")
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# exec_result_output = exec_result.get("output")
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# if exec_result_output:
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# save_result = exec_result_output.get("result")
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# context.set_variable(function_name, save_result)
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# # 如果执行成功，将变量保存到任务记录
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# # if exec_result.get("success", False):
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# # save_result = {function_name: exec_result}
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#
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# await self._save_variables_to_database(context)
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#
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#
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# # 记录执行结果
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# await self._record_task_log(block, exec_result, context)
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# return exec_result
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# except Exception as e:
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# result = {
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# "success": False,
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# "message": f"设置任务变量失败: {str(e)}"
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# }
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# # 记录异常
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# await self._record_task_log(block, result, context)
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# return result
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#
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# async def _execute_script(
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# self,
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# function_name: str,
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# function_args: Any,
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# context: TaskContext
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# ) -> Dict[str, Any]:
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# """
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# 执行指定的脚本函数（通过脚本注册中心）
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#
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# Args:
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# function_name: 要执行的函数名
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# function_args: 函数参数
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# context: 任务上下文
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#
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# Returns:
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# Dict[str, Any]: 执行结果
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# """
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# logger.info(f"执行注册函数: {function_name}")
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#
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# try:
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# # 获取脚本引擎服务
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# from services.online_script.script_engine_service import get_script_engine
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# from services.online_script.script_registry_service import get_global_registry
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#
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# script_engine = get_script_engine()
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# registry = get_global_registry()
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#
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# # 检查函数是否已注册
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# func_info = registry.get_function_info(function_name)
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# if not func_info:
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# return {
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# "success": False,
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# "message": f"函数 {function_name} 未在脚本注册中心注册"
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# }
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#
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# # 获取函数所属的脚本服务ID
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# script_service_id = func_info.get("script_id")
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# if not script_service_id:
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# return {
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# "success": False,
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# "message": f"函数 {function_name} 没有关联的脚本服务"
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# }
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#
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# # 调用脚本引擎执行函数
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# result = await script_engine.execute_script_function(
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# script_id=script_service_id,
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# function_name=function_name,
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# function_args=function_args
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# )
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#
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# if result.get("success"):
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# result_value = result.get("result")
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# logger.info(f"函数 {function_name} 执行结果: {result_value}")
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#
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# # 设置返回值到上下文 - 与ScriptBp不同，这里会更新所有变量
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# if isinstance(result_value, dict):
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# # 如果返回值是字典，将字典中的每个键值对设置为任务变量
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# for key, value in result_value.items():
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# context.set_variable(key, value)
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#
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# result_message = f"脚本函数 {function_name} 执行成功，已更新 {len(result_value)} 个变量"
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# else:
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# # 如果返回值不是字典，将整个返回值设置为scriptResult变量
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# context.set_variable("scriptResult", result_value)
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# result_message = f"脚本函数 {function_name} 执行成功，结果已保存为scriptResult变量"
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#
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# # 构建成功结果
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# return {
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# "success": True,
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# "message": result_message,
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# "output": {
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# "result": result_value,
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# "functionName": function_name,
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# "execution_time_ms": result.get("execution_time_ms", 0)
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# }
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# }
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# else:
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# # 执行失败，返回错误信息
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# return {
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# "success": False,
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# "message": result.get("error", f"执行函数 {function_name} 失败")
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# }
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#
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# except Exception as e:
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# logger.error(f"执行脚本函数时发生异常: {str(e)}", exc_info=True)
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# return {
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# "success": False,
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# "message": f"执行脚本函数 {function_name} 失败: {str(e)}"
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# }
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#
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# async def _save_variables_to_database(self, context: TaskContext) -> None:
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# """
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# 将任务变量保存到数据库的任务记录中
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#
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# Args:
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# context: 任务上下文
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# """
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# try:
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# from sqlalchemy import update
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# from data.models.taskrecord import VWEDTaskRecord
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# from data.session import get_async_session
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# import json
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#
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# # 获取任务记录ID
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# task_record_id = context.task_record_id
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#
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# if not task_record_id:
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# logger.error("无法保存变量，任务记录ID为空")
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# return
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#
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# # 将任务变量转换为JSON字符串
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# variables_json = json.dumps(context.variables, ensure_ascii=False)
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# # 更新数据库记录
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# async with get_async_session() as session:
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# stmt = update(VWEDTaskRecord).where(VWEDTaskRecord.id == task_record_id).values(
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# variables=variables_json
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# )
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# await session.execute(stmt)
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# await session.commit()
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#
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# logger.info(f"已将任务变量保存到数据库记录 {task_record_id}")
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#
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# except Exception as e:
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# logger.error(f"保存任务变量到数据库失败: {str(e)}")
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#
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# def _validate_and_convert_args(self, function_args: Any) -> Any:
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# """
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# 验证并转换函数参数，确保参数是有效的 JSON 格式
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#
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# Args:
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# function_args: 输入的函数参数
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#
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# Returns:
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# Any: 转换后的参数（JSON 对象）
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#
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# Raises:
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# ValueError: 当参数无法转换为有效 JSON 时抛出异常
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# """
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# import json
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#
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# # 如果已经是字典或列表等 JSON 兼容类型，直接返回
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# if isinstance(function_args, (dict, list, int, float, bool)) or function_args is None:
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# return function_args
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#
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# # 如果是字符串，尝试解析为 JSON
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# if isinstance(function_args, str):
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# try:
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# parsed_args = json.loads(function_args)
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# logger.info(f"成功解析参数字符串为 JSON: {parsed_args}")
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# return parsed_args
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# except json.JSONDecodeError as e:
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# error_msg = f"函数参数不是有效的 JSON 格式: {str(e)}"
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# logger.error(error_msg)
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# raise ValueError(error_msg)
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#
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# # 其他类型不支持，抛出异常
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# error_msg = f"不支持的函数参数类型: {type(function_args)}，参数必须是有效的 JSON 格式"
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# logger.error(error_msg)
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# raise ValueError(error_msg)
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#
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#
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# # 脚本块处理器
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# @register_handler(ScriptBlockName.SCRIPT)
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# class ScriptBlockHandler(BlockHandler):
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# """脚本块处理器"""
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#
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# async def execute(
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# self,
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# block: Dict[str, Any],
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# input_params: Dict[str, Any],
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# context: TaskContext
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# ) -> Dict[str, Any]:
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# """执行脚本块"""
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# try:
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# # 获取函数名和参数
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# function_name = input_params.get("functionName")
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# function_args = input_params.get("functionArgs", {})
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#
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# if not function_name:
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# result = {
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# "success": False,
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# "message": "缺少函数名"
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# }
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# # 记录执行结果
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# await self._record_task_log(block, result, context)
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# return result
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#
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# # 参数类型验证和转换
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# function_args = self._validate_and_convert_args(function_args)
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#
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# # 调用脚本执行方法
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# exec_result = await self._execute_script(function_name, function_args, context)
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#
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# # 记录执行结果
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# await self._record_task_log(block, exec_result, context)
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# return exec_result
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# except Exception as e:
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# result = {
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# "success": False,
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# "message": f"脚本执行失败: {str(e)}"
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# }
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# # 记录异常
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# await self._record_task_log(block, result, context)
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# return result
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#
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# async def _execute_script(
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# self,
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# function_name: str,
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# function_args: Any,
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# context: TaskContext
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# ) -> Dict[str, Any]:
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# """
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# 执行指定的脚本函数（通过脚本注册中心）
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#
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# Args:
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# function_name: 要执行的函数名
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# function_args: 函数参数
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# context: 任务上下文
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#
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# Returns:
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# Dict[str, Any]: 执行结果
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# """
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# logger.info(f"执行注册函数: {function_name}")
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#
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# try:
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# # 获取脚本引擎服务
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# from services.online_script.script_engine_service import get_script_engine
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# from services.online_script.script_registry_service import get_global_registry
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#
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# script_engine = get_script_engine()
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# registry = get_global_registry()
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#
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# # 检查函数是否已注册
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# func_info = registry.get_function_info(function_name)
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# if not func_info:
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# return {
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# "success": False,
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# "message": f"函数 {function_name} 未在脚本注册中心注册"
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# }
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#
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# # 获取函数所属的脚本服务ID
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# script_service_id = func_info.get("script_id")
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# if not script_service_id:
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# return {
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# "success": False,
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# "message": f"函数 {function_name} 没有关联的脚本服务"
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# }
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# # 调用脚本引擎执行函数
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# result = await script_engine.execute_script_function(
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# script_id=script_service_id,
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# function_name=function_name,
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# function_args=function_args
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# )
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#
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# if result.get("success"):
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# result_value = result.get("result")
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# logger.info(f"函数 {function_name} 执行结果: {result_value}")
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#
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# # 设置返回值到上下文
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# context.set_variable("scriptResult", result_value)
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#
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# # 构建成功结果
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# return {
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# "success": True,
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# "message": f"脚本函数 {function_name} 执行成功",
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# "output": {
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# "result": result_value,
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# "functionName": function_name,
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# "execution_time_ms": result.get("execution_time_ms", 0)
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# }
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# }
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# else:
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# # 执行失败，返回错误信息
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# return {
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# "success": False,
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# "message": result.get("error", f"执行函数 {function_name} 失败")
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# }
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#
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# except Exception as e:
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# logger.error(f"执行脚本函数时发生异常: {str(e)}", exc_info=True)
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# return {
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# "success": False,
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# "message": f"执行脚本函数 {function_name} 失败: {str(e)}"
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# }
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#
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# def _validate_and_convert_args(self, function_args: Any) -> Any:
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# """
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# 验证并转换函数参数，确保参数是有效的 JSON 格式
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#
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# Args:
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# function_args: 输入的函数参数
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#
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# Returns:
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# Any: 转换后的参数（JSON 对象）
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#
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# Raises:
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# ValueError: 当参数无法转换为有效 JSON 时抛出异常
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# """
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# import json
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#
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# # 如果已经是字典或列表等 JSON 兼容类型，直接返回
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# if isinstance(function_args, (dict, list, int, float, bool)) or function_args is None:
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# return function_args
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#
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# # 如果是字符串，尝试解析为 JSON
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# if isinstance(function_args, str):
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# try:
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# parsed_args = json.loads(function_args)
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# logger.info(f"成功解析参数字符串为 JSON: {parsed_args}")
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# return parsed_args
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# except json.JSONDecodeError as e:
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# error_msg = f"函数参数不是有效的 JSON 格式: {str(e)}"
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# logger.error(error_msg)
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# raise ValueError(error_msg)
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#
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# # 其他类型不支持，抛出异常
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# error_msg = f"不支持的函数参数类型: {type(function_args)}，参数必须是有效的 JSON 格式"
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# logger.error(error_msg)
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# raise ValueError(error_msg)
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###========================== 暂时使用旧版
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# !/usr/bin/env python
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# -*- coding: utf-8 -*-
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|
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"""
|
||
脚本处理器模块
|
||
提供脚本执行和变量设置的处理器
|
||
"""
|
||
|
||
import logging
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from typing import Dict, Any
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from services.execution.task_context import TaskContext
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from utils.logger import get_logger
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from .model.block_name import ScriptBlockName
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from .base import BlockHandler, register_handler
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|
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# 获取日志记录器
|
||
logger = get_logger("services.execution.handlers.script")
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||
|
||
|
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# 脚本块处理器
|
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@register_handler(ScriptBlockName.SET_TASK_VARIABLES)
|
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class SetTaskVariablesBlockHandler(BlockHandler):
|
||
"""设置任务变量块处理器"""
|
||
|
||
async def execute(
|
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self,
|
||
block: Dict[str, Any],
|
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input_params: Dict[str, Any],
|
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context: TaskContext
|
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) -> Dict[str, Any]:
|
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"""执行设置任务变量块"""
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try:
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# 获取函数名和参数
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function_name = input_params.get("functionName")
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function_args = input_params.get("functionArgs", {})
|
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|
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if not function_name:
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result = {
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"success": False,
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"message": "缺少函数名"
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}
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# 记录执行结果
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await self._record_task_log(block, result, context)
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return result
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|
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# 调用脚本执行方法
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logger.info("进入执行脚本功能块")
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exec_result = await self._execute_script(function_name, function_args, context)
|
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# print(exec_result, "=------------------=-")
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exec_result_output = exec_result.get("output")
|
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if exec_result_output:
|
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save_result = exec_result_output.get("result")
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context.set_variable(function_name, save_result)
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# 如果执行成功，将变量保存到任务记录
|
||
# if exec_result.get("success", False):
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# save_result = {function_name: exec_result}
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|
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await self._save_variables_to_database(context)
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# 记录执行结果
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||
await self._record_task_log(block, exec_result, context)
|
||
return exec_result
|
||
except Exception as e:
|
||
result = {
|
||
"success": False,
|
||
"message": f"设置任务变量失败: {str(e)}"
|
||
}
|
||
# 记录异常
|
||
await self._record_task_log(block, result, context)
|
||
return result
|
||
|
||
async def _execute_script(
|
||
self,
|
||
function_name: str,
|
||
function_args: Any,
|
||
context: TaskContext
|
||
) -> Dict[str, Any]:
|
||
"""
|
||
执行指定的脚本函数
|
||
|
||
Args:
|
||
function_name: 要执行的函数名
|
||
function_args: 函数参数
|
||
context: 任务上下文
|
||
|
||
Returns:
|
||
Dict[str, Any]: 执行结果
|
||
"""
|
||
# 固定加载scripts/user_save/test1.py文件
|
||
script_file = "scripts/user_save/test1.py"
|
||
|
||
try:
|
||
# 动态加载脚本模块
|
||
import importlib.util
|
||
import sys
|
||
import os
|
||
|
||
# 处理打包后的路径
|
||
if getattr(sys, 'frozen', False):
|
||
# 在打包后的环境中
|
||
base_path = sys._MEIPASS if hasattr(sys, '_MEIPASS') else os.path.dirname(sys.executable)
|
||
script_path = os.path.join(base_path, script_file)
|
||
else:
|
||
# 在开发环境中
|
||
script_path = script_file
|
||
|
||
logger.info(f"正在加载脚本文件: {script_path}")
|
||
|
||
# 检查文件是否存在
|
||
if not os.path.exists(script_path):
|
||
return {
|
||
"success": False,
|
||
"message": f"脚本文件不存在: {script_path}"
|
||
}
|
||
|
||
# 加载模块
|
||
spec = importlib.util.spec_from_file_location("user_script", script_path)
|
||
if not spec:
|
||
return {
|
||
"success": False,
|
||
"message": f"无法加载脚本规范: {script_path}"
|
||
}
|
||
module = importlib.util.module_from_spec(spec)
|
||
sys.modules["user_script"] = module
|
||
spec.loader.exec_module(module)
|
||
|
||
# 检查函数是否存在
|
||
if not hasattr(module, function_name):
|
||
return {
|
||
"success": False,
|
||
"message": f"函数 {function_name} 在脚本 {script_path} 中不存在"
|
||
}
|
||
# 获取函数对象
|
||
func = getattr(module, function_name)
|
||
|
||
# 准备函数参数（处理不同类型的参数传递方式）
|
||
args = []
|
||
kwargs = {}
|
||
# 如果function_args是字典，将其作为关键字参数传递
|
||
if isinstance(function_args, dict):
|
||
kwargs = function_args
|
||
# 如果function_args是列表，将其作为位置参数传递
|
||
elif isinstance(function_args, list):
|
||
args = function_args
|
||
|
||
# 如果function_args是其他类型，将其作为单个位置参数传递
|
||
# elif function_args is not None:
|
||
# args = [function_args]
|
||
elif isinstance(function_args, str):
|
||
function_args = eval(function_args)
|
||
|
||
# 调用函数
|
||
logger.info(f"调用函数 {function_name} 参数: args={args}, kwargs={kwargs}")
|
||
|
||
# 特殊处理：如果函数只接受一个参数且传入的是字典，直接传递字典
|
||
# print(function_args, "--------", type(function_args))
|
||
# result_value = func(function_args)
|
||
import inspect
|
||
sig = inspect.signature(func)
|
||
params = list(sig.parameters.keys())
|
||
if len(params) == 1 and isinstance(function_args, dict) and not args:
|
||
# 函数只有一个参数且传入的是字典，直接传递
|
||
result_value = func(function_args)
|
||
else:
|
||
result_value = func(**function_args)
|
||
|
||
# 检查是否是异步函数并等待结果
|
||
if inspect.iscoroutine(result_value):
|
||
import asyncio
|
||
result_value = await result_value
|
||
|
||
logger.info(f"函数 {function_name} 执行结果: {result_value}")
|
||
|
||
# 设置返回值到上下文 - 与ScriptBp不同，这里会更新所有变量
|
||
if isinstance(result_value, dict):
|
||
# 如果返回值是字典，将字典中的每个键值对设置为任务变量
|
||
for key, value in result_value.items():
|
||
context.set_variable(key, value)
|
||
|
||
result_message = f"脚本函数 {function_name} 执行成功，已更新 {len(result_value)} 个变量"
|
||
else:
|
||
# 如果返回值不是字典，将整个返回值设置为scriptResult变量
|
||
context.set_variable("scriptResult", result_value)
|
||
result_message = f"脚本函数 {function_name} 执行成功，结果已保存为scriptResult变量"
|
||
|
||
# 构建成功结果
|
||
return {
|
||
"success": True,
|
||
"message": result_message,
|
||
"output": {
|
||
"result": result_value,
|
||
"functionName": function_name
|
||
}
|
||
}
|
||
|
||
except Exception as e:
|
||
logger.error(f"执行脚本函数时发生异常: {str(e)}", exc_info=True)
|
||
return {
|
||
"success": False,
|
||
"message": f"执行脚本函数 {function_name} 失败: {str(e)}"
|
||
}
|
||
|
||
async def _save_variables_to_database(self, context: TaskContext) -> None:
|
||
"""
|
||
将任务变量保存到数据库的任务记录中
|
||
|
||
Args:
|
||
context: 任务上下文
|
||
"""
|
||
try:
|
||
from sqlalchemy import update
|
||
from data.models.taskrecord import VWEDTaskRecord
|
||
from data.session import get_async_session
|
||
import json
|
||
|
||
# 获取任务记录ID
|
||
task_record_id = context.task_record_id
|
||
|
||
if not task_record_id:
|
||
logger.error("无法保存变量，任务记录ID为空")
|
||
return
|
||
|
||
# 将任务变量转换为JSON字符串
|
||
variables_json = json.dumps(context.variables, ensure_ascii=False)
|
||
# 更新数据库记录
|
||
async with get_async_session() as session:
|
||
stmt = update(VWEDTaskRecord).where(VWEDTaskRecord.id == task_record_id).values(
|
||
variables=variables_json
|
||
)
|
||
await session.execute(stmt)
|
||
await session.commit()
|
||
|
||
logger.info(f"已将任务变量保存到数据库记录 {task_record_id}")
|
||
|
||
except Exception as e:
|
||
logger.error(f"保存任务变量到数据库失败: {str(e)}")
|
||
|
||
|
||
# 脚本块处理器
|
||
@register_handler(ScriptBlockName.SCRIPT)
|
||
class ScriptBlockHandler(BlockHandler):
|
||
"""脚本块处理器"""
|
||
|
||
async def execute(
|
||
self,
|
||
block: Dict[str, Any],
|
||
input_params: Dict[str, Any],
|
||
context: TaskContext
|
||
) -> Dict[str, Any]:
|
||
"""执行脚本块"""
|
||
try:
|
||
# 获取函数名和参数
|
||
function_name = input_params.get("functionName")
|
||
function_args = input_params.get("functionArgs", {})
|
||
|
||
if not function_name:
|
||
result = {
|
||
"success": False,
|
||
"message": "缺少函数名"
|
||
}
|
||
# 记录执行结果
|
||
await self._record_task_log(block, result, context)
|
||
return result
|
||
|
||
# 调用脚本执行方法
|
||
exec_result = await self._execute_script(function_name, function_args, context)
|
||
|
||
# 记录执行结果
|
||
await self._record_task_log(block, exec_result, context)
|
||
return exec_result
|
||
except Exception as e:
|
||
result = {
|
||
"success": False,
|
||
"message": f"脚本执行失败: {str(e)}"
|
||
}
|
||
# 记录异常
|
||
await self._record_task_log(block, result, context)
|
||
return result
|
||
|
||
async def _execute_script(
|
||
self,
|
||
function_name: str,
|
||
function_args: Any,
|
||
context: TaskContext
|
||
) -> Dict[str, Any]:
|
||
"""
|
||
执行指定的脚本函数
|
||
|
||
Args:
|
||
function_name: 要执行的函数名
|
||
function_args: 函数参数
|
||
context: 任务上下文
|
||
|
||
Returns:
|
||
Dict[str, Any]: 执行结果
|
||
"""
|
||
# 固定加载scripts/user_save/test1.py文件
|
||
script_file = "scripts/user_save/test1.py"
|
||
|
||
try:
|
||
# 动态加载脚本模块
|
||
import importlib.util
|
||
import sys
|
||
import os
|
||
|
||
# 处理打包后的路径
|
||
if getattr(sys, 'frozen', False):
|
||
# 在打包后的环境中
|
||
base_path = sys._MEIPASS if hasattr(sys, '_MEIPASS') else os.path.dirname(sys.executable)
|
||
script_path = os.path.join(base_path, script_file)
|
||
else:
|
||
# 在开发环境中
|
||
script_path = script_file
|
||
|
||
logger.info(f"正在加载脚本文件: {script_path}")
|
||
|
||
# 检查文件是否存在
|
||
if not os.path.exists(script_path):
|
||
return {
|
||
"success": False,
|
||
"message": f"脚本文件不存在: {script_path}"
|
||
}
|
||
|
||
# 加载模块
|
||
spec = importlib.util.spec_from_file_location("user_script", script_path)
|
||
if not spec:
|
||
return {
|
||
"success": False,
|
||
"message": f"无法加载脚本规范: {script_path}"
|
||
}
|
||
module = importlib.util.module_from_spec(spec)
|
||
sys.modules["user_script"] = module
|
||
spec.loader.exec_module(module)
|
||
# 检查函数是否存在
|
||
if not hasattr(module, function_name):
|
||
return {
|
||
"success": False,
|
||
"message": f"函数 {function_name} 在脚本 {script_path} 中不存在"
|
||
}
|
||
# 获取函数对象
|
||
func = getattr(module, function_name)
|
||
|
||
# 准备函数参数（处理不同类型的参数传递方式）
|
||
args = []
|
||
kwargs = {}
|
||
|
||
# 如果function_args是字典，将其作为关键字参数传递
|
||
if isinstance(function_args, dict):
|
||
kwargs = function_args
|
||
# 如果function_args是列表，将其作为位置参数传递
|
||
elif isinstance(function_args, list):
|
||
args = function_args
|
||
# 如果function_args是其他类型，将其作为单个位置参数传递
|
||
elif isinstance(function_args, str):
|
||
eval_result = eval(function_args)
|
||
if isinstance(eval_result, dict):
|
||
kwargs = eval_result
|
||
elif isinstance(eval_result, list):
|
||
args = eval_result
|
||
else:
|
||
args = [eval_result]
|
||
elif function_args is not None:
|
||
args = [function_args]
|
||
|
||
# 调用函数
|
||
logger.info(f"调用函数 {function_name} 参数: args={args}, kwargs={kwargs}")
|
||
|
||
# 特殊处理：如果函数只接受一个参数且传入的是字典，直接传递字典
|
||
import inspect
|
||
sig = inspect.signature(func)
|
||
params = list(sig.parameters.keys())
|
||
|
||
if len(params) == 1 and isinstance(function_args, dict) and not args:
|
||
# 函数只有一个参数且传入的是字典，直接传递
|
||
result_value = func(function_args)
|
||
else:
|
||
# 正常的参数传递
|
||
result_value = func(*args, **kwargs)
|
||
|
||
# 检查是否是异步函数并等待结果
|
||
if inspect.iscoroutine(result_value):
|
||
import asyncio
|
||
result_value = await result_value
|
||
|
||
logger.info(f"函数 {function_name} 执行结果: {result_value}")
|
||
|
||
# 设置返回值到上下文
|
||
context.set_variable("scriptResult", result_value)
|
||
|
||
# 构建成功结果
|
||
return {
|
||
"success": True,
|
||
"message": f"脚本函数 {function_name} 执行成功",
|
||
"output": {
|
||
"result": result_value,
|
||
"functionName": function_name
|
||
}
|
||
}
|
||
|
||
except Exception as e:
|
||
logger.error(f"执行脚本函数时发生异常: {str(e)}", exc_info=True)
|
||
return {
|
||
"success": False,
|
||
"message": f"执行脚本函数 {function_name} 失败: {str(e)}"
|
||
}
|