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


The itertools chapter of the Python library documentation is outstanding. The basic definitions are followed by a series of recipes that are extremely clear and helpful. Since there's no reason to reproduce these, we'll reference them here. They are the required reading materials on functional programming in Python.

Section 10.1.2, Itertools Recipes, in the Python Standard Library is a wonderful resource. Visit for more details.

These function definitions aren't importable functions in the itertools modules. These are ideas that need to be read and understood and then, perhaps, copied or modified before inclusion in an application.

The following table summarizes some recipes that show functional programming algorithms built from the itertools basics:

Function name





This generates all the subsets of the iterable. Each subset is actually a tuple object, not a set instance.