As a software developer, there are few things more frustrating than trying to work with poor legacy code. Whether it's poorly written code or a lack of documentation, dealing with legacy code can be a time-consuming and often painful process. As you try to make updates or improvements, you may find yourself constantly battling bugs and errors, struggling to understand how the code works, and feeling like you're fighting an uphill battle. Clean Code for the rescue! But what is it?

In neuroscience and epileptology research, one of the most persistent hurdles is the precise localization of intracranial electrodes. When working with post-implantation MRI or CT scans, we need a way to bridge the gap between raw medical imaging and actionable data. To address this, I developed PyLocator, an open-source Python tool designed to make the mapping of electrodes within MRI volumes more intuitive and reproducible.

Python is great. I've been using it for 15 years now, and since then it has evolved from a niche-solution to the most popular programming language of the planet. It is being used massively in Data Science, Machine Learning, Web Development and automation. 

The main advantages are .... 

But still, some aspects of Python are just annoying. I collected my personal list of shortcomings - but beyond just complaining, I also complement them with benefits, alternatives and songs of praise.