Managing Your Reusable Python Code as a Data Scientist - KDnuggets

There are lots of different approaches to managing your own code, which will differ depending on your requirements, personality, technical know-how, role, and numerous other factors. While a highly-experienced developer may have an incredibly regimented method of organizing their code across multiple languages, projects, and use cases, a data analyst that rarely writes their own code may be much more ad hoc and lackadaisical out of lack of necessity. There really is no right or wrong, it's simply a matter of what works -- and is appropriate -- for you. To be specific, what I'm referring to by "managing code" is how you organize, store, and recall different pieces of code you, yourself, have written and found useful as long-term additions to your programming toolbox. Programming is all about automating, and so if, as someone who writes code, you find that you are performing similar tasks repetitively, it's only makes sense that you somehow automated the recalling of the code associated with that task.