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 at how we can use the PyMonad library to express some functional programming concepts directly in Python. The module contains many important functional programming techniques.

We looked at the idea of currying, a function that allows combinations of arguments to be applied to create new functions. Currying a function also allows us to use functional composition to create more complex functions from simpler pieces. We looked at functors that wrap simple data objects to make them into functions which can also be used with functional composition.

Monads are a way to impose a strict evaluation order when working with an optimizing compiler and lazy evaluation rules. In Python, we don't have a good use case for monads, because Python is an imperative programming language under the hood. In some cases, imperative Python may be more expressive and succinct than a monad construction.

In the next chapter, we'll look at how we can apply functional programming techniques...