#### Overview of this book

Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You’ll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you’ll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.
Preface
Free Chapter
Python Data Types and Structures
Introduction to Algorithm Design
Algorithm Design Techniques and Strategies
Stacks and Queues
Trees
Heaps and Priority Queues
Hash Tables
Graphs and Algorithms
Searching
Sorting
Selection Algorithms
String Matching Algorithms
Other Books You May Enjoy
Index

# 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...