在Jupyter上启动python脚本作为后台作业

本文介绍了在Jupyter上启动python脚本作为后台作业的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我正在尝试在木星笔记本中将*.py文件作为后台服务运行.

I am trying to run a *.py file as a background service in Jupiter notebook.

from IPython.lib import backgroundjobs as bg jobs = bg.BackgroundJobManager() jobs.new(%run -i "script.py") # Not working jobs.new("script.py") # Not working

推荐答案

Ipython/Jupyter后台作业旨在将任一纯代码运行到 eval (字符串)或函数.不支持文件和ipython magic命令.

Ipython/Jupyter background jobs is designed to run either plain code to eval (string), or function. Files and ipython magic commands is not supported.

您可以做的一件事就是简单地读取文件内容并将其传递给eval:

One thing you can do is to simply read file content and pass it to eval:

from IPython.lib.backgroundjobs import BackgroundJobFunc with open('script.py') as code: job = BackgroundJobFunc(exec, code.read()) result = job.run()

BackgroundJobManager 几乎相同，但是有点更智能".

BackgroundJobManager is pretty much the same, but a little bit "smarter".

侧面说明:该接口背后的所有后台机械都在同一进程的线程中运行，并共享解释器状态和输出.因此，请紧记:

Side note: all background machinery behind this interfaces runs in threads of the same process and share interpreter state and output. So, just keep in mind:

• 这不适用于需要大量计算的脚本
• 永远不要以这种方式运行不受信任的代码-总体上适用于eval，但是在这种情况下，您可能会遇到永远无法使GIL返回前端"线程的情况.
• 避免使用stdout的脚本，很可能这些脚本会紧紧抓住您的主线程

• this is not suited for computational-heavy scripts
• never run untrusted code this way — this applies to eval overall, but in this case you can into situation when you'll never get GIL back to your "frontend" thread
• avoid scripts that use stdout, most probably those will clutch with your main thread