Book Image

Functional Python Programming. - Second Edition

Book Image

Functional Python Programming. - Second Edition

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

Chapter 13. Conditional Expressions and the Operator Module

Functional programming emphasizes lazy or non-strict ordering of operations. The idea is to allow the compiler or runtime to do as little work as possible to compute the answer. Python tends to impose strict ordering on evaluations, which could be inefficient.

The Python if, elif, and else statements enforce a strict ordering on the evaluation of the conditions. In this chapter, we'll look at ways we can, to an extent, free ourselves from the strict ordering, and develop a limited kind of non-strict conditional statement. It's not clear whether this is helpful, but it will show some alternative ways to express an algorithm in a somewhat more functional style.

In the previous chapters, we looked at a number of higher-order functions. In some cases, we used these higher-order functions to apply fairly sophisticated functions to collections of data. In other cases, we applied simple functions to collections of data.

Indeed, in many cases...