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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 2. Introducing Essential Functional Concepts FREE CHAPTER 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

Defining classes with total ordering


The total_ordering decorator is helpful for creating new class definitions that implement a rich set of comparison operators. This might apply to numeric classes that subclass numbers.Number. It may also apply to semi-numeric classes.

As an example of a semi-numeric class, consider a playing card. It has a numeric rank and a symbolic suit. The rank matters only when doing simulations of some games. This is particularly important when simulating casino blackjack. Like numbers, cards have an ordering. We often sum the point values of each card, making them number-like. However, multiplication of card × card doesn't really make any sense; a card isn't quite like a number.

We can almost emulate a playing card with a NamedTuple base class as follows:

from typing import NamedTuple
class Card1(NamedTuple):
    rank: int
    suit: str

This is almost a good emulation. It suffers from a profound limitation: all comparisons include both the rank and the suit by default...

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