Uploaded November 2022 | Updated September 2026, 2 weeks ago
Why is Systemd coming to Windows Subsystem for Linux a big deal? Because you can start doing generic scheduled events as if doing web development but without a webserver. Just plain old generic Linux allows you to easily write services that run 24 hours a day 7 days a week, triggering off events written in the programming language of your choice.
In my case it's Python and now that JupyterLab is running on my local laptop as a Linux program, the Notebooks are very convertible into scheduled .py-files. In this case I had to contain an async block of code that ran without being inside a function when in Jupyter into being inside an async function when turned into a .py-file.
So this video covers going all the way from mocked-up code in a Jupyter Notebook to active code running on a Linux server. It builds upon prior work and shows how close the Jupyter "Lost" mode of operation where you have to sit there and press a button all the time can be become hands-free automation of a "remote" Linux server.
Many people would use the cloud, but I see no reason. Just slap it onto your NAS or a Raspberry Pi and save yourself the hosting costs and vendor dependency. Oh yeah, did I mention this was also the testing of Microsoft Playwright in headless mode used to do a Google SERP screenshot? Very useful stuff.
Why is Systemd coming to Windows Subsystem for Linux a big deal? Because you can start doing generic scheduled events as if doing web development but without a webserver. Just plain old generic Linux allows you to easily write services that run 24 hours a day 7 days a week, triggering off events written in the programming language of your choice.
In my case it's Python and now that JupyterLab is running on my local laptop as a Linux program, the Notebooks are very convertible into scheduled .py-files. In this case I had to contain an async block of code that ran without being inside a function when in Jupyter into being inside an async function when turned into a .py-file.
So this video covers going all the way from mocked-up code in a Jupyter Notebook to active code running on a Linux server. It builds upon prior work and shows how close the Jupyter "Lost" mode of operation where you have to sit there and press a button all the time can be become hands-free automation of a "remote" Linux server.
Many people would use the cloud, but I see no reason. Just slap it onto your NAS or a Raspberry Pi and save yourself the hosting costs and vendor dependency. Oh yeah, did I mention this was also the testing of Microsoft Playwright in headless mode used to do a Google SERP screenshot? Very useful stuff.
