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  • Book Overview & Buying Python Automation Cookbook
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Python Automation Cookbook

Python Automation Cookbook - Second Edition

By : Jaime Buelta
3.8 (16)
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Python Automation Cookbook

Python Automation Cookbook

3.8 (16)
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)
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14
Other Books You May Enjoy
15
Index

Introduction

Writing code is not easy. Actually, it is very hard. Even the best programmer in the world can't foresee every possible alternative and flow of the code.

This means that executing our code will always produce surprises and unexpected behaviors. Some will be very evident, while others will be very subtle, but the ability to identify and remove these defects in the code is critical to building solid software.

These defects in software are known as bugs, and therefore removing them is called debugging.

Inspecting the code just by reading it and reasoning about its execution image will never be enough to cover all the possible outcomes on non-trivial code. There are always surprises, and complex code is difficult to follow. That's why the ability to debug by stopping execution and taking a look at the current state of things is important.

Everyone, and I mean EVERYONE, introduces bugs in the code, only to be surprised by them later. Some people...

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Python Automation Cookbook
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