Let’s run Jupyter notebooks in a Visual Studio Code development container, so we keep our host system clean and our development setup replicable. We’re building a scraper, so let’s add support for Puppeteer (pyppeteer) as well!
I imagine your first thought is: why? Well, at Wehkamp we do a lot of cross platform development, but sometimes we end up with shell scripts that do stuff with Docker and Python. Usually that’s not a problem for Mac, but for Windows it’s a different thing. I have a MacBook Pro, but I’m a .NET developer, that’s why I prefer Windows, so I run Bootcamp. This article will show how to do Python development in the Windows Subsystem for Linux (WSL) using Visual Studio Code and Docker.
My Synology disk crashed and so did my Docker set up. Basically, the CI/CD pipeline for my programs no longer existed. The wonderful thing of an awful crash like this, is that I could rethink my setup. The result is what I would call “a poor man’s CI/CD”. It’s just Git, Docker, Docker Compose and Cron. It is easy to set up and it might be all you need.
The main problem of a CI/CD pipeline – in my opinion – is logging. When it logs too little you don’t know what’s going on, when it logs to much you can’t see the trees to the forest. Having too much logging can seriously impact the effectiveness of your CI/CD pipeline. This script will improve Xunit unit test output.