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
Packt Upsell
Contributors
Preface
Index

Summary


In this chapter, we looked closely at writing pure functions free of side effects. The bar is low here, since Python forces us to use the global statement to write impure functions. We looked at generator functions and how we can use these as the backbone of functional programming. We also examined the built-in collection classes to show how they're used in the functional paradigm. While the general idea behind functional programming is to limit the use of stateful variables, the collection objects are generally stateful and, for many algorithms, also essential. Our goal is to be judicious in our use of Python's non-functional features.

In the next two chapters, we'll look at higher-order functions: functions that accept functions as arguments as well as returning functions. We'll start with an exploration of the built-in higher-order functions. In later chapters, we'll look at techniques for defining our own higher-order functions. We'll also look at the itertools and functools modules...