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

Chapter 4. Working with Collections

Python offers a number of functions that process whole collections. They can be applied to sequences (lists or tuples), sets, mappings, and iterable results of generator expressions. We'll look at Python's collection-processing features from a functional programming viewpoint.

We'll start out by looking at iterables and some simple functions that work with iterables. We'll look at some design patterns to handle iterables and sequences with recursive functions as well as explicit for loops. We'll look at how we can apply a scalar function to a collection of data with a generator expression.

In this chapter, we'll show you examples of how to use the following functions with collections:

  • any() and all()
  • len(), sum(), and some higher-order statistical processing related to these functions
  • zip() and some related techniques to structure and flatten lists of data
  • reversed()
  • enumerate()

The first four functions can be called reductions: they reduce a collection to a single...