Book Image

Functional Python Programming - Second Edition

By : Steven F. Lott
Book Image

Functional Python Programming - Second Edition

By: Steven F. Lott

Overview of this book

If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective.
Table of Contents (22 chapters)
Title Page
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Chapter 10. The Functools Module

Functional programming emphasizes functions as first-class objects. We've seen several higher-order functions that accept functions as arguments or return functions as results. In this chapter, we'll look at the functools library with some tools to help us implement some common functional design patterns.

We'll look at some higher-order functions. This extends the material from Chapter 5, Higher-Order Functions. We'll continue looking 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. Additionally, it lets us look at the more general question of object-oriented design mixed with functional programming.
  • partial(): This function creates a new function from a function and some parameter value bindings.
  • reduce...