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Python Automation Cookbook

Python Automation Cookbook - Third Edition

By : Jaime Buelta
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Python Automation Cookbook

Python Automation Cookbook

By: Jaime Buelta

Overview of this book

Automating repetitive tasks and integrating systems efficiently becomes increasingly complex as workflows scale. This book helps you solve that problem with practical Python recipes that guide you from foundational automation to advanced, AI-powered workflows. You start by building a strong base in Python automation, exploring tested solutions for file handling, web scraping, APIs, testing, and system operations, and learning how to design reliable automation workflows. The cookbook approach enables you to quickly apply solutions to real problems while building a deeper understanding through hands-on practice. This third edition expands the scope of automation by introducing AI-powered capabilities. You learn how to call AI models within your scripts, use and implement the Model Context Protocol (MCP) for system integration, and design intelligent agents that automate decision-making processes. New chapters provide real-world examples of AI agents in business automation, helping you move beyond scripts to adaptive systems. This book combines practical knowledge with modern techniques to ensure you stay current with evolving automation practices. By the end of this book, you will be able to design, build, and extend Python automation workflows, including AI-driven solutions, to handle complex real-world tasks with confidence.
Table of Contents (20 chapters)
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18
Other Books You May Enjoy
19
Index

Preparing testing scenarios

Tests are typically prepared in batches. Similar tests require a similar setup and cleanup, and they only differ on small details. Repeating the same preparation over and over generates boilerplate code and is less readable.

The term boilerplate comes from 19th-century local newspapers printing already-prepared news stamped onto metal plates by distribution companies. This meant the same news, in the same format, was repeated all across different newspapers. Boilerplate code is reused code that presents little or no variation and, in most cases, mainly adds clutter. When creating tests, it is easy to fall into this pattern, which makes the code cumbersome.

At the moment, a common trap is to repeat the code quickly through the usage of GenAI tools, which will produce boilerplate and won't get tired of adding it over and over. While this is good from the point of view of generation, it makes the tests more difficult to read and to understand. Easily understandable...

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Python Automation Cookbook
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