#### 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.
Title Page
Packt Upsell
Contributors
Preface
Free Chapter
Understanding Functional Programming
Introducing Essential Functional Concepts
Functions, Iterators, and Generators
Working with Collections
Recursions and Reductions
The Itertools Module
More Itertools Techniques
The Functools Module
Decorator Design Techniques
Conditional Expressions and the Operator Module
A Functional Approach to Web Services
Optimizations and Improvements
Other Books You May Enjoy
Index

## Recursion instead of an explicit loop state

Functional programs don't rely on loops and the associated overhead of tracking the state of loops. Instead, functional programs try to rely on the much simpler approach of recursive functions. In some languages, the programs are written as recursions, but Tail-CallOptimization (TCO) in the compiler changes them to loops. We'll introduce some recursion here and examine it closely in Chapter 6, Recursions and Reductions.

We'll look at a simple iteration to test a number for being prime. A prime number is a natural number, evenly divisible by only 1 and itself. We can create a naïve and poorly-performing algorithm to determine whether a number has any factors between 2 and the number. This algorithm has the advantage of simplicity; it works acceptably for solving Project Euler problems. Read up on Miller-Rabin primality tests for a much better algorithm.

We'll use the term `coprime` to mean that two numbers have only one as their common factor. The numbers...