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

Standardizing the date format

The date time format in the logs is different 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. In this recipe, we will append a new column with a standard format to unify both dates.

Getting ready

We will use the resulting CSV file 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 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 in the...