Book Image

Getting Started with Python

By : Fabrizio Romano, Benjamin Baka, Dusty Phillips
Book Image

Getting Started with Python

By: Fabrizio Romano, Benjamin Baka, Dusty Phillips

Overview of this book

This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: • Learn Python Programming - Second Edition by Fabrizio Romano • Python Data Structures and Algorithms by Benjamin Baka • Python 3 Object-Oriented Programming by Dusty Phillips
Table of Contents (31 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
8
Stacks and Queues
10
Hashing and Symbol Tables
Index

Quick sort


The quick sort algorithm falls under the divide and conquer class of algorithms, where we break (divide) a problem into smaller chunks that are much simpler to solve (conquer). In this case, an unsorted array is broken into sub-arrays that are partially sorted, until all elements in the list are in the right position, by which time our unsorted list will have become sorted.

List partitioning

Before we divide the list into smaller chunks, we have to partition it. This is the heart of the quick sort algorithm. To partition the array, we must first select a pivot. All the elements in the array will be compared with this pivot. At the end of the partitioning process, all elements that are less than the pivot will be to the left of the pivot, while all elements greater than the pivot will lie to the right of the pivot in the array.

Pivot selection

For the sake of simplicity, we'll take the first element in any array as the pivot. This kind of pivot selection degrades in performance, especially...