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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 the map() function to apply a function to a collection

A scalar function maps values from a domain to a range. When we look at the math.sqrt() function, as an example, we're looking at a mapping from the float value, x, to another float value, y = sqrt(x), such that . The domain is limited to positive values. The mapping can be done via a calculation or table interpolation.

The map() function expresses a similar concept; it maps values from one collection to create another collection. It assures that the given function is used to map each individual item from the domain collection to the range collection-the ideal way to apply a built-in function to a collection of data.

Our first example involves parsing a block of text to get the sequence of numbers. Let's say we have the following chunk of text:

>>> text= """\
...   2   3    5    7  ...
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