善小而为_ 发表于 2024-2-6 11:46:13

aardio调用python,返回json,有点意思

本帖最后由 善小而为_ 于 2024-2-6 11:58 编辑

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


import console;

import process.python;
process.python.path = "python.exe";

var pyJsonCode = /***
?>
import sys;
import json
str = json.dumps(['foo', "<?= time() ?>",{'bar': ('baz', None, 1.0, 2)},sys.argv])
# print 写到进程标准输出,在 aardio 中可以读取
print( str)
***/

var prcs = process.python.exec(pyJsonCode);
var info = prcs.json();
console.dump(info)

console.getText("");


旧事阑珊 发表于 2024-2-22 16:36:52

很好的网站,希望越来越好

飞飞 发表于 2024-2-29 15:55:57

:)学习学习
页: [1]
查看完整版本: aardio调用python,返回json,有点意思