Some people despise developing with unit tests, but I prefer to use them and leverage them to the allow me to quickly push new code and be more confident that it works! I love doing TDD (test-driven development) which inherently involves continuously re-running the tests, and regardless of what language you are coding in, being able to run your tests in "watch mode" makes TDD faster and easier than without it!

Although Java is one of my favorite languages to dump on, I have been using Java for Exercism.io problems. Not only have I been trying to get some in with Java itself, but other languages like Clojure and CFML depend on have some version of Java installed on your system, either just the runtime environment (JRE) or the whole development kit (JDK). In this post I'll talk about Jabba, my new favorite cli tool for installing and switching Java versions!

There have been many times since my friends Lasha told me about this service that I forgot its name and ending up kicking myself for hours or days until I finally remember the name, Buffer. Yep, this post of going to be short and sweet and really just serve the purpose of reminding me what the heck the name of this thing is when I search "schedule post" on my site. hehe

This guide demonstrates one way to setup your locally computer for solving exercises on Exercism.io. When working on your solutions to exercism, why not version you code and save it to git just as you would any "real" project you plan to deploy? With Github, you can make a public repo for free that can contain all of your solutions, plus you'll be associating this nice code with your Github profile and be getting those green squares on Github! Excercism projects make excellent code to have on your Github account because every exercise itself is it's own little self-contained, fully unit tested and peer-reviewed bit of clean code that does something correctly! You can take a look at my Exercism-Solutions repo to see how awesome it is to have all of your Exercism solutions there in a Github repo. ?

Notebooks are an excellent way to store little python projects because they cleanly mix markdown and runnable code snippet in one file. If you are using python or doing data science work, building your project inside of a notebook can make it easily transferable to other colleagues in a presentable form right out of the box.