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Python Data Structures and Algorithms

Python Data Structures and Algorithms

By : Benjamin Baka
2.7 (11)
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Python Data Structures and Algorithms

Python Data Structures and Algorithms

2.7 (11)
By: Benjamin Baka

Overview of this book

Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications.
Table of Contents (14 chapters)
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5
Stacks and Queues
7
Hashing and Symbol Tables

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...

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