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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

A faster append operation


There is a big problem with the append method in the previous section: it has to traverse the entire list to find the insertion point. This may not be a problem when there are just a few items in the list, but wait until you need to add thousands of items. Each append will be slightly slower than the previous one. A O(n) goes to prove how slow our current implementation of the append method will actually be.

To fix this, we will store, not only a reference to the first node in the list, but also a reference to the last node. That way, we can quickly append a new node at the end of the list. The worst case running time of the append operation is now reduced from O(n) to O(1). All we have to do is make sure the previous last node points to the new node, that is about to be appended to the list. Here is our updated code:

    class SinglyLinkedList:
         def __init__(self): 
             # ...
             self.tail = None

         def append(self, data):
      ...

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