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

Functional composition and the PyMonad * operator

One of the significant values of curried functions is the ability to combine them through functional composition. We looked at functional composition in Chapter 5, Higher-Order Functions, and Chapter 11, Decorator Design Techniques.

When we've created a curried function, we can more easily perform function composition to create a new, more complex curried function. In this case, the PyMonad package defines the * operator for composing two functions. To explain how this works, we'll define two curried functions that we can compose. First, we'll define a function that computes the product, and then we'll define a function that computes a specialized range of values.

Here's our first function, which computes the product:

import  operator
prod = myreduce(operator.mul) 

This is based on our curried myreduce() function that was defined previously. It uses the operator.mul() function to compute a times-reduction of an iterable: we can call a product...