Functional Python Programming

Create succinct and expressive implementations with functional programming in Python

About This Book

• 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.

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.

Table of Contents

Chapter 1: Introducing Functional Programming
Chapter 2: Introducing Some Functional Features
Chapter 3: Functions, Iterators, and Generators
Chapter 4: Working with Collections
Chapter 5: Higher-Order Functions
Chapter 6: Recursions and Reductions
Chapter 7: Additional Tuple Techniques
Chapter 8: The Itertools Module
Chapter 9: More Itertools Techniques
Chapter 10: The Functools Module
Chapter 11: Decorator Design Techniques
Chapter 12: The Multiprocessing and Threading Modules
Chapter 13: Conditional Expressions and the Operator Module
Chapter 14: The PyMonad Library
Chapter 15: A Functional Approach to Web Services
Chapter 16: Optimizations and Improvements