The Functools Module

Functional programming emphasizes functions as first class objects. We have many
high-order functions that accept functions as arguments or return functions as
results. In this chapter, we'll look at the functools library with some functions to
help us create and modify functions.

We'll look at some higher-order functions in this chapter. Earlier, we looked at
higher-order functions in Chapter 5, Higher-order Functions. We'll continue to look at
higher-order function techniques in Chapter 11, Decorator Design Techniques, as well.

We'll look at the following functions in this module:

• @lru_cache: This decorator can be a huge performance boost for certain
  types of applications.


• @total_ordering: This decorator can help create rich comparison operators.
  However, it lets us look at the more general question of object-oriented
  design mixed with functional programming.


• partial(): It creates a new function with some arguments applied to
  a given function.


• reduce(): It is a higher-order function which generalizes reductions
  like sum().

We'll defer two additional members of this library to Chapter 11, Decorator Design
Techniques: the update_wrapper() and wraps() functions. We'll look more closely
at writing our own decorators in the next chapter also.

We'll ignore the cmp_to_key() function entirely. Its purpose is to help with
converting Python 2 code—which uses a comparison—to run under Python 3
which uses key extraction. We're only interested in Python 3; we'll write proper
key functions.