Buelta Python Automation Cookbook

75 Python automation recipes for web scraping; data wrangling; and Excel, report, and email processing
2. Auflage 2024
ISBN: 978-1-80020-259-7
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 526 Seiten

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.

Autoren/Hrsg.

Buelta, Jaime

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsvisualisierung
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen

Inhaltsverzeichnis

Table of Contents - Let's Begin Our Automation Journey
- Automating Tasks Made Easy
- Building Your First Web Scraping Application
- Searching and Reading Local Files
- Generating Fantastic Reports
- Fun with Spreadsheets
- Cleaning and Processing Data
- Developing Stunning Graphs
- Dealing with Communication Channels
- Why Not Automate Your Marketing Campaign?
- Machine Learning for Automation
- Automatic Testing Routines
- Debugging Techniques

Leseproben

Preface

We are all probably spending time doing small manual tasks that don't add much value. It may be scanning through information sources in search of the small bits of relevant information, working with spreadsheets to generate the same graph over and over, or searching files one by one until we find the data we're looking for. Some—probably most—of those tasks are, in fact, automatable. There's an investment upfront, but for the tasks that get repeated over and over, we can use computers to do these kinds of menial tasks and focus our own efforts instead on what humans are good for—high-level analysis and decision making based on the result. This book will explain how to use the Python language to automate common business tasks that can be greatly sped up if a computer is doing them.

Given the expressiveness and ease of use of Python, it's surprisingly simple to start making small programs to perform these actions and combine them into more integrated systems. Throughout the book, we will show small, easy-to-follow recipes that can be adapted to your specific needs, and we will combine them to perform more complex actions. We will perform common actions, such as detecting opportunities by scraping the web, analyzing information to generate automatic spreadsheet reports with graphs, communicating with automatically generated emails, getting notifications via text messages, and learning how to run tasks while your mind is focused on other more important stuff.

Though some Python knowledge is required, the book is written with non-programmers in mind, giving clear and instructive recipes that will further the reader's proficiency while being oriented to specific day-to-day goals.

Who this book is for

This book is for Python beginners, not necessarily developers, that want to use and expand their knowledge to automate tasks. Most of the examples in the book are aimed at marketing, sales, and other non-tech areas. The reader needs to know a little of the Python language, including its basic concepts.

What this book covers

, , 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.

, , 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.

, , 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.

, , 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.

, , 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.

, , 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.

, , 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.

, , 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.

, , 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 , communicating through SMS messages, and creating a bot in Telegram.

, , 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.

, , 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.

, , explores the write and execute tests to verify that code is behaving as expected. To do so, the test framework is presented with common situations to effectively work with tests.

, , 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.

To get the most out of this book

• Before reading this book, readers need to know the basics of the Python language. We do not assume that the reader is an expert in the language.
• The reader needs to know how to input commands in the command line (Terminal, Bash, or equivalent).
• To understand the code in this book, you need a text editor, which will enable you to read and edit the code. You can use an IDE that supports the Python language, such as PyCharm and PyDev—which you choose is up to you. Check out this link for ideas about IDEs: https://realpython.com/python-ides-code-editors-guide/.

Download the example code files

You can download the example code files for this book from your account at http://www.packtpub.com. If you purchased this book elsewhere, you can visit http://www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at http://www.packtpub.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the on-screen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR / 7-Zip for Windows
• Zipeg / iZip / UnRarX for Mac
• 7-Zip / PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Python-Automation-Cookbook-Second-Edition. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://static.packt-cdn.com/downloads/9781800207080_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

: Indicates code words in text, object names, module names, folder names, filenames, file extensions, pathnames, dummy URLs and user input. Here is an example: "For this recipe, we need to import the module."

A block of code is set as follows:

Note that code may be edited for concision and clarity. Refer to the full code when necessary, which is available at GitHub.

Any command-line input or output is written as follows (notice the symbol):

Über Autor(innen)

Buelta Jaime :

Jaime Buelta is a Software Architect who has been a professional programmer since 2002 and a Python enthusiast since 2010. He has developed software for a variety of fields, focusing, in the last 10 years, on developing web services in Python in the gaming, finance and education industries. He is a strong proponent of automating everything to make computers do most of the heavy lifting, so humans can focus on the important stuff. He published his first book, "Python Automation Cookbook", in 2018 (recently with an extended second edition), followed a year later by "Hands-On Docker for Microservices with Python" describing how to migrate to a microservice architecture. He is currently living in Dublin, Ireland, and is a regular speaker at PyCon Ireland.