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.