I ran into a situation when writing some code recently where I had to add caching to an existing function in order to speed up the execution of my function when it was called multiple times with the same arguments. I know from experience that this involves a technique called memoization in which you basically cache the previous result and when the same arguments are passed to your function you pull from the cache instead of re-executed the same code that takes a while and would render the exact same result.
Adding the memoization/caching feature to your function isn’t hard but immediately I found it made the whole function look ugly and cluttered, and I was not satisfied with that. Luckily I was using python which has a feature called decorators which allow you to easily add more “functionality” to an existing function without cluttering its “code space”.
As any good engineer the first thing to do was to look around and see if someone had already created a memoize decorator for python and I quickly found there was a decent example in the python documentation but it lacked quite a few features including the ability to handle functions with lists or other objects as arguments. So I set out to create my own memoize module that could be easily used in other projects without having to clutter my code with “memoization” code.
I built the memoize module that is now available here and the README included has enough information on how to use this in your own project.