Book Image

Functional Python Programming. - Second Edition

Book Image

Functional Python Programming. - Second Edition

Overview of this book

If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective.
Table of Contents (22 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Permuting a collection of values


When we permute a collection of values, we'll elaborate all the possible orders for the items. There are 

ways to permute

items. We can use a sequence of permutations as a kind of brute-force solution to a variety of optimization problems.

By visiting http://en.wikipedia.org/wiki/Combinatorial_optimization, we can see that the exhaustive enumeration of all permutations isn't appropriate for larger problems. The use of the itertools.permutations() function is only handy for exploring very small problems.

One popular example of these combinatorial optimization problems is the assignment problem. We have n agents and n tasks, but the cost of each agent performing a given task is not equal. Imagine that some agents have trouble with some details, while other agents excel at these details. If we can properly assign tasks to agents, we can minimize the costs.

We can create a simple grid that shows how well a given agent is able to perform a given task. For a small...