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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

Understanding GenAI elements

The key element in Artificial Intelligence is the AI Model. In general, there's some confusion between AI models and GenAI tools.

For example, ChatGPT is a tool by OpenAI, and it can call several different models that can be chosen, based on the requirements. For example, GPT-5.4 is a specific model by OpenAI.

GenAI tools call AI models internally, but they perform coordination on which model to use, when to call it, and what information to send back and forth.

Figure 11.4: Schema of a GenAI tool calling the AI model

Figure 11.4: Schema of a GenAI tool calling the AI model

For example, ChatGPT itself is a GenAI tool. It keeps a conversation, is able to call the AI model multiple times, and calls the right tools.

AI libraries also have capabilities that allow more actions than purely calling the model. In that regard, they act as GenAI tools. We won't be using them in this chapter but will do so later in the book. See Chapter 15 for more information.

In this chapter we will focus on working directly...

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Python Automation Cookbook
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