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

Testing with pytest


The Python unittest module requires a lot of boilerplate code to set up and initialize tests. It is based on the very popular JUnit testing framework for Java. It even uses the same method names (you may have noticed they don't conform to the PEP-8 naming standard, which suggests snake_case rather than CamelCase to indicate a method name) and test layout. While this is effective for testing in Java, it's not necessarily the best design for Python testing. I actually find the unittest framework to be an excellent example of overusing object-oriented principles.

Because Python programmers like their code to be elegant and simple, other test frameworks have been developed, outside the standard library. Two of the more popular ones are pytest and nose. The former is more robust and has had Python 3 support for much longer, so we'll discuss it here.

Since pytest is not part of the standard library, you'll need to download and install it yourself. You can get it from the pytest...