#### 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

One of the other features of PyMonad is the confusingly named monoid. This comes directly from mathematics and it refers to a group of data elements that have an operator and an identity element, and the group is closed with respect to that operator. When we think of natural numbers, the `add` operator, and an identity element `0`, this is a proper monoid. For positive integers, with an operator `*`, and an identity value of `1`, we also have a monoid; strings using `|` as an operator and an empty string as an identity element also qualify.
PyMonad includes a number of predefined monoid classes. We can extend this to add our own `monoid` class. The intent is to limit a compiler to certain kinds of optimization. We can also use the monoid class to create data structures which accumulate a complex value, perhaps including a history of previous operations.