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

7.8 Summary

In this chapter, we looked at different ways to use NamedTuple subclasses to implement more complex data structures. The essential features of a NamedTuple are a good fit with functional design. They can be created with a creation function and accessed by position as well as name.

Similarly, we looked at frozen dataclasses as an alternative to NamedTuple objects. The use of a dataclass seems slightly superior to a NamedTuple subclass because a dataclass doesn’t also behave like a sequence of attribute values.

We looked at how immutable objects can be used instead of stateful object definitions. The core technique for replacing state changes is to wrap objects in larger objects that contain derived values.

We also looked at ways to handle multiple data types in Python. For most arithmetic operations, Python’s internal method dispatch locates proper implementations. To work with collections, however, we might want to handle iterators and sequences slightly differently...

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