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Hands-On Data Structures and Algorithms with Python – Third Edition

You're reading from   Hands-On Data Structures and Algorithms with Python – Third Edition Store, manipulate, and access data effectively and boost the performance of your applications

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781801073448
Length 496 pages
Edition 3rd Edition
Languages
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Author (1):
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Dr. Basant Agarwal Dr. Basant Agarwal
Author Profile Icon Dr. Basant Agarwal
Dr. Basant Agarwal
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Toc

Table of Contents (17) Chapters Close

Preface 1. Python Data Types and Structures FREE CHAPTER 2. Introduction to Algorithm Design 3. Algorithm Design Techniques and Strategies 4. Linked Lists 5. Stacks and Queues 6. Trees 7. Heaps and Priority Queues 8. Hash Tables 9. Graphs and Algorithms 10. Searching 11. Sorting 12. Selection Algorithms 13. String Matching Algorithms 14. Other Books You May Enjoy
15. Index
Appendix: Answers to the Questions

Implementing hash tables

To implement the hash table, we start by creating a class to hold hash table items. These need to have a key and a value since the hash table is a {key-value} store:

class HashItem: 
    def __init__(self, key, value): 
        self.key = key 
        self.value = value 

Next, we start working on the hash table class itself. As usual, we start with a constructor:

class HashTable: 
     def __init__(self): 
         self.size = 256 
         self.slots = [None for i in range(self.size)] 
         self.count = 0 

Standard Python lists can be used to store data elements in a hash table. Let’s set the size of the hash table to 256 elements to start with. Later, we will look at strategies for how to grow the hash table as we begin filling it up. We will now initialize a list containing 256 elements in the code. These are the positions where the elements are to be stored—the slots or buckets. So, we have 256 slots to store elements...

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