调用python,rpc返回,值得研究
本帖最后由 善小而为_ 于 2024-2-6 11:56 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
import win.ui;
/*DSG{{*/
var winform = win.form(text="aardio form";right=759;bottom=469)
winform.add(
edit={cls="edit";text="Edit";left=123;top=68;right=598;bottom=360;edge=1;multiline=1;z=1}
)
/*}}*/
import process.python;
process.python.path = "python.exe";
var pyJsonRpcCode = /***
import sys;
import json
from jsonrpyc import RPC;
#定义允许客户端调用的类
class MyTarget(object):
def greet(self, name):
jls_extract_var = "Hi, %s!" % name +"" + " is very good."+"\n" +sys.version
return jls_extract_var
def add(self, a,b):
return a + b
#启动 JSON-RPC 服务端
RPC( MyTarget() )
***/
var python = process.python.jsonRpc(pyJsonRpcCode);
var rep,err = python.greet("Jacen")
if( rep[["result"]] ){
winform.edit.print( `调用 py.greet("Jacen") 成功,返回值:`, rep.result )
}
else{
winform.edit.print(err )
}
winform.show();
win.loopMessage();
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