Book Image

Python Automation Cookbook - Second Edition

By : Jaime Buelta
Book Image

Python Automation Cookbook - Second Edition

By: Jaime Buelta

Overview of this book

In this updated and extended version of Python Automation Cookbook, each chapter now comprises the newest recipes and is revised to align with Python 3.8 and higher. The book includes three new chapters that focus on using Python for test automation, machine learning projects, and for working with messy data. This edition will enable you to develop a sharp understanding of the fundamentals required to automate business processes through real-world tasks, such as developing your first web scraping application, analyzing information to generate spreadsheet reports with graphs, and communicating with automatically generated emails. Once you grasp the basics, you will acquire the practical knowledge to create stunning graphs and charts using Matplotlib, generate rich graphics with relevant information, automate marketing campaigns, build machine learning projects, and execute debugging techniques. By the end of this book, you will be proficient in identifying monotonous tasks and resolving process inefficiencies to produce superior and reliable systems.
Table of Contents (16 chapters)
14
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15
Index

Introduction

When the code and the complexity of your software grows, generating tests to ensure your program does what it is supposed to do is the best tool to provide you with a firm footing over rocky terrain.

Tests are, in essence, double-checking the code is valid and doing what it is supposed to do. This is a deceptively simple statement, but in practice, it can be very difficult.

Mastering the ability to test is a difficult task and is worth a book or two. The tasks introduced in this chapter move from business-oriented tasks to software engineering tasks, which is a different approach. The objective of this chapter is to present some practical aspects of testing to introduce the subject.

The most important thing about a test is that it tries to check the code that is being tested independently. This involves a mindset of looking at the code and the inputs and outputs and approaching the task with a fresh look, and to not be influenced by the internal...