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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

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781803232577
Length 576 pages
Edition 3rd Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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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

11.3 Using the toolz package

The toolz package comprises functions that are similar to some of the functions in the built-in itertools and functools modules. The toolz package adds some functions to perform sophisticated processing on dictionary objects. This package has a narrow focus on iterables, dictionaries, and functions. This overlaps nicely with the data structures available in JSON and CSV documents. The idea of processing iterables that come from files or databases allows a Python program to deal with vast amounts of data without the complication of filling memory with the entire collection of objects.

We’ll look at a few example functions from the various subsections of the toolz package. There are over sixty individual functions in the current release. Additionally, there is a cytoolz implementation written in Cython that provides higher performance than the pure Python toolz package.

11.3.1 Some itertoolz functions

We’ll look at a common data analysis problem...

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