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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

Functors and applicative functors

The idea of a functor is a functional representation of a piece of simple data. A functor version of the number 3.14 is a function of zero arguments that returns this value. Consider the following example:

>>> pi = lambda: 3.14
>>> pi()
3.14

We created a zero-argument lambda object that returns a simple value.

When we apply a curried function to a functor, we're creating a new curried functor. This generalizes the idea of applying a function to an argument to get a value by using functions to represent the arguments, the values, and the functions themselves.

Once everything in our program is a function, then all processing is simply a variation of the theme of functional composition. The arguments and results of curried functions can be functors. At some point, we'll apply a getValue() method to a functor object to get...

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