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

Preparing a CSV spreadsheet

As we saw in the previous chapter, CSV files are files containing tabular data defined as a collection of rows with defined columns, separated by commas. They are a very common format for all kinds of data. We will see in this recipe how to extract data from log files and store the information in a CSV file.

Getting ready

We will use a similar log format as the one introduced in the Extracting data from structured strings recipe in Chapter 1, Let's Begin Our Automation Journey:

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

Each line will represent a sale log.

We will use the parse module. We should install the module, adding it to our requirements.txt file as follows:

$ echo "parse==1.14.0" >> requirements.txt
$ pip install -r requirements.txt

In the GitHub repository, there are some log files to process with the following structure:

sale_logs/
  OH
    logs.txt
  ON...