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

Appending currency based on location

The resulting CSV file from the previous recipe doesn't contain currency information, even though the location can indicate different places with different currencies. In this recipe, we will process a CSV file to add extra information: the currency the prices are in, and a conversion into US dollars.

Getting ready

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

[<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
    logs.txt

The code can be found...