In this chapter, we'll look at a few optimizations that we can make to create high performance functional programs. We'll expand on the @lru_cache decorator from Chapter 10, The Functools Module. We have a number of ways to implement the memoization algorithm. We'll also discuss how to write our own decorators. More importantly, we'll see how we use a Callable object to cache memoized results.

We'll also look at some optimization techniques that were presented in Chapter 6, Recursions and Reductions. We'll review the general approach to tail recursion optimization. For some algorithms, we can combine memoization with a recursive implementation and achieve good performance. For other algorithms, memoization isn't really very helpful and we have to look elsewhere for performance improvements.

In most cases, small changes to a program will lead to small improvements in performance. Replacing a function with a lambda object will have a tiny impact on...