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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 lists, dicts, and sets

A Python sequence object, such as a list, is iterable. However, it has some additional features. We'll think of it as a materialized iterable. We've used the tuple() function in several examples to collect the output of a generator expression or generator function into a single tuple object. We can also materialize a sequence to create a list object.

In Python, a list display, or list comprehension, offers simple syntax to materialize a generator: we just add the [] brackets. This is ubiquitous to the point where the distinction between generator expression and list comprehension is lost. We need to disentangle the idea of generator expression from a list display that uses a generator expression.

The following is an example to enumerate the cases:

>>> range(10)
range(0, 10)
>>> [range(10)]
[range(0, 10)]
>>&gt...
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