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

Reading CSV files

Some text files contain tabular data separated by commas. This is a convenient way of creating structured data, instead of using proprietary, more complex binary formats such as Excel or others. These files are called Comma Separated Values or CSV files, and most spreadsheet packages allow us to work directly with them.

Getting ready

We've prepared a CSV file using the data for the top 10 movies by theatre attendance, as described by this page: http://www.mrob.com/pub/film-video/topadj.html.

We copied the first 10 elements of the table into a spreadsheet program (Numbers) and exported the file as a CSV. The file is available in the GitHub repository in the Chapter04/documents directory as top_films.csv:

Figure 4.1: Content of the CSV file

How to do it...

  1. Import the csv module:
    >>> import csv
    
  2. Open the file, create a reader, and iterate through it to show the tabular data of all rows (only...