Book Image

Python Data Structures and Algorithms

By : Benjamin Baka
Book Image

Python Data Structures and Algorithms

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 (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
5
Stacks and Queues
7
Hashing and Symbol Tables

Graph traversal


Since graphs don't necessarily have an ordered structure, traversing a graph can be more involving. Traversal normally involves keeping track of which nodes or vertices have already been visited and which ones have not. A common strategy is to follow a path until a dead end is reached, then walking back up until there is a point where there is an alternative path. We can also iteratively move from one node to another in order to traverse the full graph or part of it. In the next section, we will discuss breadth and depth-first search algorithms for graph traversal.

Breadth-first search

The breadth-first search algorithm starts at a node, chooses that node or vertex as its root node, and visits the neighboring nodes, after which it explores neighbors on the next level of the graph.

Consider the following diagram as a graph:

The diagram is an example of an undirected graph. We continue to use this type of graph to help make explanation easy without being too verbose.

The adjacency...