Book Image

Getting Started with Python

By : Fabrizio Romano, Benjamin Baka, Dusty Phillips
Book Image

Getting Started with Python

By: Fabrizio Romano, Benjamin Baka, Dusty Phillips

Overview of this book

This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: • Learn Python Programming - Second Edition by Fabrizio Romano • Python Data Structures and Algorithms by Benjamin Baka • Python 3 Object-Oriented Programming by Dusty Phillips
Table of Contents (31 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
8
Stacks and Queues
10
Hashing and Symbol Tables
Index

Recursive functions


When a function calls itself to produce a result, it is said to be recursive. Sometimes recursive functions are very useful in that they make it easier to write code. Some algorithms are very easy to write using the recursive paradigm, while others are not. There is no recursive function that cannot be rewritten in an iterative fashion, so it's usually up to the programmer to choose the best approach for the case at hand.

The body of a recursive function usually has two sections: one where the return value depends on a subsequent call to itself, and one where it doesn't (called a base case).

As an example, we can consider the (hopefully familiar by now) factorial function, N!. The base case is when N is either 0 or 1. The function returns 1 with no need for further calculation. On the other hand, in the general case, N! returns the product 1 * 2 * ... * (N-1) * N. If you think about it, N! can be rewritten like this: N! = (N-1)! * N. As a practical example, consider 5!...