The biggest issue when dealing with multiple projects is how to keep track of the various Python and other packages’ versions you are using in each project. It is not uncommon to update something and get something else broken…
The solution is virtual environments. And for these there are few options such as virtualenv and conda (among others). So far I have postponed (and not with good results) the use of environments. But finally, I took the necessary time to investigate pros and cons and make a decision. I found the following guides from WhiteBox exceptional well written and useful:
- The definitive guide to Python virtual environments with conda
- The Definitive Data Scientist Environment Setup
along with this great meme …
