Good Scientific Coding

Workshop description
Scientific code is notorious for being hard to read and navigate, difficult to reproduce, and badly documented. One reason leading to this situation is that curricula that traditionally train scientists do not explicitly treat writing good code, and during the scientific life there is little time for the individual to practice this on their own. In this intensive three-session online workshop, we will change that and teach you all you need to know to write code that is Clear, Easy to understand, Well-documented, Reproducible, Testable, Reliable, Reusable, Extendable, and Generic.

Timetable
May 6th 1:00-4:00 pm
Session 1 focuses on writing clear and understandable code that is quick to parse.
May 13th 1:00-4:00 pm
Session 2 focuses on teaching you software development paradigms so that you can design codebases that are modular, extendable, accessible, and reusable.
May 20th 1:00-4:00 pm
Session 3 focuses on how to easily achieve open and reproducible computational research.

Bring your own code!
The exercise sessions have two components. On the first, illustrative but simple exercises are given to the participants to practice each topic. Participants are expected to solve the exercises live during the workshop! The second component requires the participants to apply this new knowledge to their very own code base. Therefore, please bring along all code you have used in your latest published paper. If you haven't published yet, no worries, bring along all the code you have at the moment for your science project. Decide in advance on 2-3 figures of your paper/project, which will be the central focus of the exercises. The exercise plan will transform your code from random scripts to a self-contained code base that is understandable, extendable, continuously tested, documented, and hosted on open and accessible platforms.
Note: for this plan to have meaningful impact, you should bring a code base where you had to write a substantial amount of source code.