Book Image

Python Automation Cookbook

By : Jaime Buelta
Book Image

Python Automation Cookbook

By: Jaime Buelta

Overview of this book

Have you been doing the same old monotonous office work over and over again? Or have you been trying to find an easy way to make your life better by automating some of your repetitive tasks? Through a tried and tested approach, understand how to automate all the boring stuff using Python. The Python Automation Cookbook helps you develop a clear understanding of how to automate your business processes using Python, including detecting opportunities by scraping the web, analyzing information to generate automatic spreadsheets reports with graphs, and communicating with automatically generated emails. You’ll learn how to get notifications via text messages and run tasks while your mind is focused on other important activities, followed by understanding how to scan documents such as résumés. Once you’ve gotten familiar with the fundamentals, you’ll be introduced to the world of graphs, along with studying how to produce organized charts using Matplotlib. In addition to this, you’ll gain in-depth knowledge of how to generate rich graphics showing relevant information. By the end of this book, you’ll have refined your skills by attaining a sound understanding of how to identify and correct problems to produce superior and reliable systems.
Table of Contents (12 chapters)

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 formats such as Excel or others. These files are called Comma Separated Values, or CSV, files and most spreadsheet packages also export to it.

Getting ready

We've prepared a CSV file using the data for the 10 top movies by theatre attendance, as described by this page:

We copied the first ten 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: