It was summer and because of the remaining days off which I got granted during my internship at CERN, it was time for vacations. 2 weeks. Time, which I definitely did not want to spend at one single place. So, a road trip? Mmh, without a proper car, properly not the best idea. Bus traveling? I had this one in South America and it takes too much time for only 2 weeks. So train? If so, how far? Good that there are global passes offered by Interrail (non-EU citizens may refer to Eurail). You get the freedom to use your pass multiple times. We (my travel mate Sabrina and I) chose the 5 times in 10 days pass which is enough for 2 weeks.

It is time for another Random Output post, this time featuring an evidence of unicorns, my flat’s garden and money problems.

Splitting software into packages and defining dependencies between them is a good thing. It simplifies security updates and enables code reusability. However, it comes with a big pack of problems, collected under the term dependency hell. All package managers have to deal with it and some of them get it right (e.g., Meteor, libsolv used by Zypper and DNF) and many of them do not (e.g., pip). In this post I want to explore an optimal way to install a desired package and its requirements.

This time there I do not have to tell much about the graphics. The reason for this is that my experiment turned out to be less enlightening than I hoped it would be. Anyway, it is quite a good amount of data and some people might need a new data-driven wallpaper. What you see here is a the transaction split over a day.

This is the first Random Output post. This post series will contain random material I want to share without long and complicated descriptions.