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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

Cloning iterators with tee()


The tee() function gives us a way to circumvent one of the important Python rules for working with iterables. The rule is so important, we'll repeat it here:

Note

Iterators can be used only once.

The tee() function allows us to clone an iterator. This seems to free us from having to materialize a sequence so that we can make multiple passes over the data. For example, a simple average for an immense dataset could be written in the following way:

def mean(iterator: Iterator[float]) -> float:
    it0, it1 = tee(iterator,2)
    N = sum(1 for x in it0)
    s1 = sum(x for x in it1)
    return s1/N

This would compute an average without appearing to materialize the entire dataset in memory in any form. Note that the type hint of float doesn't preclude integers. The mypy program is aware of the type coercion rules, and this definition provides a flexible way to specify that either int or float will work.

While interesting in principle, the tee() function's implementation...

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