Implement common functional programming design patterns and techniques in Python
Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance
Apply functional Python to common Exploratory Data Analysis (EDA) programming problems
Who This Book Is For
This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.
What You Will Learn
Use Python's generator functions and generator expressions to work with collections in a non-strict (or lazy) manner
Utilize Python library modules including itertools, functools, multiprocessing, and concurrent.futures for efficient functional programs
Use Python strings using object-oriented suffix notation and prefix notation
Avoid stateful classes with families of tuples
Design and implement decorators to create composite functions
Use functions like max(), min(), map(), filter(), and sorted()
Write higher-order functions
In Detail
Python is an easy-to-learn and extensible programming language that offers a number of functional programming features. It's ideally suited to a number of applications in the broad space of data science.
This practical guide demonstrates the Python implementation of a number of functional programming techniques and design patterns. Starting with a general overview of functional programming concepts, you will explore common functional features such as first-class and higher-order functions, pure functions and more, and how these are accomplished in Python. Additionally, you will cover how common functional optimizations can be handled in Python. You'll also explore data preparation techniques and data exploration in depth. Moving on, you will learn how the Python standard library fits the functional programming model. The book concludes with a look at the PyMonad project and some larger examples.
By the end of this book, you will be able to understand what functional programming is all about, its impact on the programming workflow, why it's important, and how to implement it in Python.
About the Author
Steven Lott has been programming since the 1970s, when computers were large, expensive, and rare. As a contract software developer and architect, he has worked on hundreds of projects, from very small to very large. He's been using Python to solve business problems for over 10 years. He's particularly adept struggling with gnarly data representation problems. His other titles include Mastering Object-Oriented Python and Python for Secret Agents, both by Packt Publishing. After spending years as a technomad living in various places on the east coast of the US he has dropped the hook in the Chesapeake Bay. He blogs at http://slott-softwarearchitect.blogspot.com.
