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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

Reducing with operators

We'll look at one more way that we might try to use the operator definitions. We can use them with the built-in functools.reduce() function. The sum() function, for example, can be defined as follows:

sum= functools.partial(functools.reduce, operator.add)

We created a partially evaluated version of the reduce() function with the first argument supplied. In this case, it's the + operator, implemented via the operator.add() function.

If we have a requirement for a similar function that computes a product, we can define it like this:

prod= functools.partial(functools.reduce, operator.mul)

This follows the pattern shown in the preceding example. We have a partially evaluated reduce() function with the first argument of * operator, as implemented by the operator.mul() function.

It's not clear whether we can do similar things with too many of the other operators. We might be able to find a use for the operator.concat() function as well as the operator.and(...

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