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Functional Python Programming

You're reading from   Functional Python Programming Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788627061
Length 408 pages
Edition 2nd Edition
Languages
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Toc

Table of Contents (18) Chapters Close

Preface 1. Understanding Functional Programming FREE CHAPTER 2. Introducing Essential Functional Concepts 3. Functions, Iterators, and Generators 4. Working with Collections 5. Higher-Order Functions 6. Recursions and Reductions 7. Additional Tuple Techniques 8. The Itertools Module 9. More Itertools Techniques 10. The Functools Module 11. Decorator Design Techniques 12. The Multiprocessing and Threading Modules 13. Conditional Expressions and the Operator Module 14. The PyMonad Library 15. A Functional Approach to Web Services 16. Optimizations and Improvements 17. Other Books You May Enjoy

Preface

Functional programming offers a variety of techniques for creating succinct and expressive software. While Python is not a purely functional programming language, we can do a great deal of functional programming in Python.

Python has a core set of functional programming features. This lets us borrow many design patterns and techniques from other functional languages. These borrowed concepts can lead us to create succinct and elegant programs. Python's generator expressions, in particular, negate the need to create large in-memory data structures, leading to programs that may execute more quickly because they use fewer resources.

We can’t easily create purely functional programs in Python. Python lacks a number of features that would be required for this. We don’t have unlimited recursion, for example, we don’t have lazy evaluation of all expressions, and we don’t have an optimizing compiler.

There are several key features of functional programming languages that are available in Python. One of the most important ones is the idea of functions being first-class objects. Python also offers a number of higher-order functions. The built-in map(), filter(), and functools.reduce() functions are widely used in this role, and less-obvious are functions such as sorted(), min(), and max().

We’ll look at the core features of functional programming from a Python point of view. Our objective is to borrow good ideas from functional programming languages and use those ideas to create expressive and succinct applications in Python.

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