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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 FREE CHAPTER 2. Introducing Essential Functional Concepts 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

Using map() with multiple sequences


Sometimes, we'll have two collections of data that need to be parallel to each other. In Chapter 4, Working with Collections, we saw how the zip() function can interleave two sequences to create a sequence of pairs. In many cases, we're really trying to do something like the following:

map(function, zip(one_iterable, another_iterable))  

We're creating argument tuples from two (or more) parallel iterables and applying a function to the argument tuple. We can also look at it as follows:

(function(x,y) 
    for x,y in zip(one_iterable, another_iterable)
)

Here, we've replaced the map() function with an equivalent generator expression.

We might have the idea of generalizing the whole thing to the following:

def star_map(function, *iterables)
    return (function(*args) for args in zip(*iterables))

There is a better approach that is already available to us. We don't actually need these techniques. Let's look at a concrete example of the alternate approach.

In Chapter...

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