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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

Monad bind() function and the >> operator


The name of the PyMonad library comes from the functional programming concept of a monad, a function that has a strict order. The underlying assumption behind much functional programming is that functional evaluation is liberal: it can be optimized or rearranged as necessary. A monad provides an exception that imposes a strict left-to-right order.

Python, as we have seen, is strict. It doesn't require monads. We can, however, still apply the concept in places where it can help clarify a complex algorithm.

The technology for imposing strict evaluation is a binding between a monad and a function that will return a monad. A flat expression will become nested bindings that can't be reordered by an optimizing compiler. The bind() function is mapped to the >> operator, allowing us to write expressions like this:

Just(some file) >> read header >> read next >> read next

The preceding expression would be converted to the following...

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