Is there a reason to use Python 2 over Python 3, or vice versa?
In the software industry, some things take years to become the standard. Although Python 3 was released back in 2008, everyone’s code was already in production in Python 2. Given the amount of work it takes to update systems to a different version of a language, and the amount of testing it requires to ensure that a new language update offers more pros than cons, it’s no wonder that many features, programs, and libraries continue to run on Python 2. Even though Python 2 is the older version, many tasks or companies may still require that you use Python 2.
Today, Python 3 is widespread, and the differences between 2 and 3 are very easy to catch up on. Learning Python 3 will be a matter of learning a handful of differences in syntax and functionality - the fundamentals are all the same, and adapting your learning from one to the other is relatively simple. If you want to learn Python 2 and then add or switch to Python 3, don’t worry, you will be in good company! With reading and practice, particularly with developer documentation, you can pick up Python 3 quickly.
As of October 2019, Codecademy Pro on Python teaches Python 3 – this includes the Pro Computer Science and Data Science Paths and multiple skill paths. Paths and include content from the core Python 3 course as well as deeper and broader material on Python to help with the Path outcome (e.g. different instruction with applying Python for data science vs. computer science). Codecademy’s older free course, Learn Python 2, teaches Python 2.x. Early access to new courses is one of the benefits of being a Pro member, and Codecademy Pro has a free 7 day trial if you want to try before you buy.
If you’re curious to learn more, here’s Python’s very own documentation on the differences and what’s new in version 3!