Yesterday we talked about function writing and how to write them in R. But there is (unfortunately) a chance that your function won't work at the first try - and that's where debugging comes in 🕵️♀️
Ways to approach this problem are, for instance, to google the error message (if there is one), take separate parts of your code and let them run, or to use the more formal debugging tools that #rstats offers.
One major thing that I learned throughout the years is the power of #debugging. Irrespective of the programming language I use, debugging is for me key when it comes to understanding the functionality of code (also for code written by someone else).
One of the very first steps when digging into a new coding basis is always turning the debugging mode on - it guides you so nicely through the functions that were written (and show you how they are connected) 😊
As a fun fact, when I wrote the initial version of my first R package, I wasn’t aware of how debugging works in R and I used a lot of "print()" statements to understand my own functions.
This works perfectly fine for smaller functions but once your code universe gets larger, unleashing the power of debugging is a game changer! ✨
How often do you use the debugging tools in R? (and all answers are great!) 👇
https://twitter.com/cosima_meyer/status/1569565278861774849
• • •
Missing some Tweet in this thread? You can try to
force a refresh
