Take your Python functions to the next level with functools

Introduction

Last month, I wrote an article about some modules in the Python standard library that I have found to be incredibly useful in my programming and Data Science career. The article had such a great reception with quality feedback that I decided to double down on the idea and write another article discussing the same topic with a lot more standard library tools that everyone should be familiar with. It turns out that the Python programming language’s base is actually quite inclusive, and includes a lot of great tools for various programming challenges. If you would like to read either one of those articles, you can check them out here:

When going over a lot of these tools, it seemed like some should have an entire article dedicated to them, rather than just a little overview that is required for most of the other modules that were presented with it. The tool that I think most reciprocated this idea to me is the functools module. This is an incredibly powerful module that can be used to improve nearly any function in Python by utilizing simple and classic methods, such as utilizing stack over processor speed. While in some circumstances I could see that being a big negative, there are certainly exceptions to that case.

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