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
Other Books You May Enjoy
15
Index

Debugging through logging

Debugging is, after all, detecting what's going on inside our program and finding out what unexpected or incorrect effects may be happening. A simple, yet very effective, approach is to output variables and other information at strategic parts of your code to allow the programmer to follow the flow of the program.

The simplest form of this approach is called print debugging. This technique consists of inserting print statements at certain points to print the value of variables or points while debugging.

But taking this technique a little further and combining it with the logging techniques presented in Chapter 2, Automating Tasks Made Easy, allows us to create a trace of the execution of the program. This tracing information can be really useful when detecting issues in a running program. Logs are also typically displayed when running tests using a test framework.

pytest, introduced in Chapter 12, Automatic Testing Routines, automatically...