#### 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

# Recursion

A recursive algorithm calls itself repeatedly in order to solve the problem until a certain condition is fulfilled. Each recursive call itself spins off other recursive calls. A recursive function can be in an infinite loop; therefore, it is required that each recursive function adheres to certain properties. At the core of a recursive function are two types of cases:

1. Base cases: These tell the recursion when to terminate, meaning the recursion will be stopped once the base condition is met
2. Recursive cases: The function calls itself recursively, and we progress toward achieving the base criteria

A simple problem that naturally lends itself to a recursive solution is calculating factorials. The recursive factorial algorithm defines two cases: the base case when n is zero (the terminating condition) and the recursive case when n is greater than zero (the call of the function itself). A typical implementation is as follows:

``````def factorial(n):
...``````