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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 the operator module instead of lambdas

When using the max(), min(), and sorted() functions, we have an optional key= parameter. The function provided as an argument value modifies the behavior of the higher-order function. In many cases, we used simple lambda forms to pick items from a tuple. Here are two examples we heavily relied on:

from typing import Callable, Sequence, TypeVar
T_ = TypeVar("T_")
fst: Callable[[Sequence[T_]], T_] = lambda x: x[0]
snd: Callable[[Sequence[T_]], T_] = lambda x: x[1]

These match built-in functions in some other functional programming languages that are used to pick the first or second item from a tuple. This includes type hints to assure that there's no other transformation going on—the type of items in the sequence is bound to the type variable, T_, which reflects the type of the result of the function.

We don't...

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