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Functional Python Programming

You're reading from   Functional Python Programming Create succinct and expressive implementations with functional programming in Python

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784396992
Length 360 pages
Edition 1st 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. Introducing Functional Programming FREE CHAPTER 2. Introducing Some Functional Features 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 Index

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.

We can almost emulate a playing card with a namedtuple() function as follows:

Card1 = namedtuple("Card1", ("rank", "suit"))

This suffers from a profound limitation: all comparisons include both a rank and a suit by default. This leads to the following awkward behavior:

>>> c2s= Card1(2, '\u2660')
>>> c2h...
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