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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

Working with the infinite iterators


The itertools module provides a number of functions that we can use to enhance or enrich an iterable source of data. We'll look at the following three functions:

  • count(): This is an unlimited version of the range() function
  • cycle(): This will reiterate a cycle of values
  • repeat(): This can repeat a single value an indefinite number of times

Our goal is to understand how these various iterator functions can be used in generator expressions and with generator functions.

Counting with count()

The built-in range() function is defined by an upper limit: the lower limit and step values are optional. The count() function, on the other hand, has a start and optional step, but no upper limit.

This function can be thought of as the primitive basis for a function such as enumerate(). We can define the enumerate() function in terms of zip() and count() functions, as follows:

enumerate = lambda x, start=0: zip(count(start), x)

The enumerate() function behaves as if it's a zip...

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