Python Automation Cookbook Second Edition

Get a firm grip on the core processes including browser automation, web scraping, Word, Excel, and GUI automation with Python 3.8 and higher

▶Book Description
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.

▶What You Will Learn
⦁Learn data wrangling with Python and Pandas for your data science and AI projects
⦁Automate tasks such as text classification, email filtering, and web scraping with Python
⦁Use Matplotlib to generate a variety of stunning graphs, charts, and maps
⦁Automate a range of report generation tasks, from sending SMS and email campaigns to creating templates, adding images in Word, and even encrypting PDFs
⦁Master web scraping and web crawling of popular file formats and directories with tools like Beautiful Soup
⦁Build cool projects such as a Telegram bot for your marketing campaign, a reader from a news RSS feed, and a machine learning model to classify emails to the correct department based on their content
⦁Create fire-and-forget automation tasks by writing cron jobs, log files, and regexes with Python scripting

▶Key Features
⦁Automate integral business processes such as report generation, email marketing, and lead generation
⦁Explore automated code testing and Python's growth in data science and AI automation in three new chapters
⦁Understand techniques to extract information and generate appealing graphs, and reports with Matplotlib

▶Who This Book Is For
Python Automation Cookbook - Second Edition is for developers, data enthusiasts or anyone who wants to automate monotonous manual tasks related to business processes such as finance, sales, and HR, among others. Working knowledge of Python is all you need to get started with this book.

▶What this book covers
⦁ Chapter 1, Let's Begin Our Automation Journey, presents some basic content that will be used all through the book. It describes how to install and manage third-party tools through virtual environments, how to do effective string manipulation, how to use command-line arguments, and introduces you to regular expressions and other methods of text processing.

⦁ Chapter 2, Automating Tasks Made Easy, shows how to prepare and automatically run tasks. It covers how to program tasks to be executed when they should, instead of running them manually; how to be notified of the result of a task that's run automatically; and how to be notified if there has been an error in an automated process.

⦁ Chapter 3, Building Your First Web Scraping Application, explores sending web requests to communicate with external websites in different formats, such as raw HTML content; structured feeds; RESTful APIs; and even automating a browser to execute steps without manual intervention. It also covers how to process results to extract relevant information.

⦁ Chapter 4, Searching and Reading Local Files, explains how to search through local files and directories and analyze the information stored there. You will learn how to filter through relevant files in different encodings and read files in several common formats, such as CSVs, PDFs, Word documents, and even images.

⦁ Chapter 5, Generating Fantastic Reports, looks at how to display information given in text format in multiple formats. This includes creating templates to produce text files, as well as creating richly formatted and properly styled Word and PDF documents.

⦁ Chapter 6, Fun with Spreadsheets, explores how to read and write spreadsheets in the CSV format; in rich Microsoft Excel, including with formatting and charts; and in LibreOffice, a free alternative to Microsoft Excel.

⦁ Chapter 7, Cleaning and Processing Data, presents techniques to deal with multiple sources of information and cleanup of data before processing it. You will learn how to batch process to speed up working with big amounts of data, including using specific data analysis libraries like Pandas.

⦁ Chapter 8, Developing Stunning Graphs, explains how to produce beautiful charts, including common examples such as pie, line, and bar charts, as well as other advanced cases, such as stacked bars and even maps. It also explains how multiple graphs can be combined and styled to generate rich graphics and show relevant information in an understandable format.

⦁ Chapter 9, Dealing with Communication Channels, explains how to send messages in multiple channels, using external tools to do the most of the heavy lifting. This chapter goes into sending and receiving emails individually as well as en masse, communicating through SMS messages, and creating a bot in Telegram.

⦁ Chapter 10, Why Not Automate Your Marketing Campaign?, combines the different recipes included in the book to generate a full marketing campaign, including steps such as detection of opportunity, generation of promotion, communication to potential customers, and analyzing and reporting sales produced by promotion. This chapter shows how to combine different elements to create powerful systems.

⦁ Chapter 11, Machine Learning for Automation, explains how to use the Machine Learning APIs from Google for text analysis, detecting a location of an image landmark, and extracting text from images. The chapter includes the creation and training of a model for detecting, based on text, which department an email should be assigned.

⦁ Chapter 12, Automatic Testing Routines, explores the write and execute tests to verify that code is behaving as expected. To do so, the test framework pytest is presented with common situations to effectively work with tests.

⦁ Chapter 13, Debugging Techniques, features different methods and tips to help in the debugging process and ensure the quality of your software. It leverages the great introspection capabilities of Python and its out-of-the-box debugging tools for fixing problems and producing solid automated software.