Book Image

Functional Python Programming. - Second Edition

Book Image

Functional Python Programming. - Second Edition

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.
Table of Contents (22 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Functional programming design patterns


There are a number of common design patterns for functional programming. These are typical approaches to functional programming that are used in a variety of contexts. 

Note the important distinction from object-oriented design patterns. Many OO design patterns are designed to make management of state more explicit, or aid in composition of complex, emergent behavior. For functional design patterns, the focus is almost always on creating complex behavior from simpler pieces.

There are many common functional design approaches shown throughout this book. Most have not been presented with a particular name or story. In this section, we'll review a number of these patterns.

  • Currying: This can be called a partial function application and is implemented with the partial() function in the functools module. The idea is to create a new function based on an existing function plus some (but not all) of the function's arguments.
  • Closures: In Python, it's very easy...