#### 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
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Index

# Introducing hash tables

As we know, arrays and lists store the data elements in sequence. As in an array, the data items are accessed by an index number. Accessing array elements using index numbers is fast. However, they are very inconvenient to use when it is required to access any element when we can’t remember the index number. For example, if we wish to extract the phone number for a person from the address book at index 56, there is nothing to link a particular contact with number 56. It is difficult to retrieve an entry from the list using the index value.

Hash tables are a data structure better suited to this kind of problem. A hash table is a data structure where elements are accessed by a keyword rather than an index number, unlike in lists and arrays. In this data structure, the data items are stored in key-value pairs similar to dictionaries. A hash table uses a hashing function in order to find an index position where an element should be stored and retrieved...