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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

Standardizing the date format

The date time format in the logs differs depending on the location. In the Canadian logs, the format is the standard ISO 8601 in the format YYYY‑MM‑DD. The logs coming from the USA use the format MM‑DD‑YYYY.

The format YYYY‑MM‑DD is the programmer's notion of a perfect date, as sorting them alphabetically also sort them as dates.

In this recipe, we will append a new column with a standard format to unify both dates.

Getting ready

We will use the CSV file resulting from the previous recipe that receives and transforms logs in the following format:

[<Timestamp>] - SALE - PRODUCT: <product id> - PRICE: <price>

Each line will represent a sale log.

We will use the parse and pendulum modules, installing them by adding them to our requirements.txt file as follows:

$ echo "parse==1.20.2" >> requirements.txt
$ echo "pendulum==3.2.0" >> requirements.txt
$ uv pip install...
CONTINUE READING
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Python Automation Cookbook
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