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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

Priority queues and heaps


A priority queue is basically a type of queue that will always return items in order of priority. This priority could be, for example, that the lowest item is always popped off first. Although it is called a queue, priority queues are often implemented using a heap, since it is very efficient for this purpose.

Consider that, in a store, customers queue in a line where service is only rendered at the front of the queue. Each customer will spend some time in the queue to get served. If the waiting times for the customers in the queue are 4, 30, 2, and 1, then the average time spent in the queue becomes (4 + 34 + 36 + 37)/4, which is 27.75. However, if we change the order of service such that customers with the least amount of waiting time are served first, then we obtain a different average waiting time. In doing so, we calculate our new average waiting time by (1 + 3 + 7 + 37)/4, which now equals 12, a better average waiting time. Clearly, there is merit to serving...

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