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 (18 chapters)

Summary

In this chapter, we looked at alternatives to the if, elif, and else statement sequence. Ideally, using a conditional expression allows some optimization to be done. Pragmatically, Python doesn't optimize, so there's little tangible benefit to the more exotic ways to handle conditions.

We also looked at how we can use the operator module with higher-order functions such as max(), min(), sorted(), and reduce(). Using operators can save us from having to create a number of small lambdas.

In the next chapter, we'll look at the PyMonad library to express a functional programming concept directly in Python. We don't require monads generally because Python is an imperative programming language under the hood.

Some algorithms might be expressed more clearly with monads than with stateful variable assignments. We'll look at an example where monads lead...