Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Functional Python Programming, 3rd edition

You're reading from   Functional Python Programming, 3rd edition Use a functional approach to write succinct, expressive, and efficient Python code

Arrow left icon
Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781803232577
Length 576 pages
Edition 3rd Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface
1. Chapter 1: Understanding Functional Programming FREE CHAPTER 2. Chapter 2: Introducing Essential Functional Concepts 3. Chapter 3: Functions, Iterators, and Generators 4. Chapter 4: Working with Collections 5. Chapter 5: Higher-Order Functions 6. Chapter 6: Recursions and Reductions 7. Chapter 7: Complex Stateless Objects 8. Chapter 8: The Itertools Module 9. Chapter 9: Itertools for Combinatorics – Permutations and Combinations 10. Chapter 10: The Functools Module 11. Chapter 11: The Toolz Package 12. Chapter 12: Decorator Design Techniques 13. Chapter 13: The PyMonad Library 14. Chapter 14: The Multiprocessing, Threading, and Concurrent.Futures Modules 15. Chapter 15: A Functional Approach to Web Services 16. Other Books You Might Enjoy
17. Index

2.3 Strict and non-strict evaluation

Functional programming’s efficiency stems, in part, from being able to defer a computation until it’s required. There are two similar concepts for avoiding computation. These are:

  • Strictness: Python operators are generally strict and evaluate all sub-expressions from left to right. This means an expression like f(a)+f(b)+f(c) is evaluated as if it was (f(a)+f(b))+f(c). An optimizing compiler might avoid strict ordering to improve performance. Python doesn’t optimize and code is mostly strict. We’ll look at cases where Python is not strict below.

  • Eagerness and laziness: Python operators are generally eager and evaluate all sub-expressions to compute the final answer. This means (3-3) * f(d) is fully evaluated even though the first part of the multiplication—the (3-3) sub-expression—is always zero, meaning the result is always zero, no matter what value is computed by the expression f(d). Generator...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image