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

Technical implementation


Let's dig into the implementation of some of the theoretical programming techniques that we discussed previously in this chapter. We will start with dynamic programming.

Dynamic programming

As we have already described, in this approach, we divide a problem into smaller subproblems. In finding the solutions to the subprograms, care is taken not to recompute any of the previously encountered subproblems.

This sounds a bit like recursion, but things are a little broader here. A problem may lend itself to being solved by using dynamic programming but will not necessarily take the form of making recursive calls.

A property of a problem that will make it an ideal candidate for being solved with dynamic programming is that it should have an overlapping set of subproblems.

Once we realize that the form of subproblems has repeated itself during computation, we need not compute it again. Instead, we return the result of a pre-computed value of that subproblem previously encountered...