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Key benefits

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

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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Total € 142.97

siebo Jun 11, 2020

This book shows how Python can be applied to many common workflows. It covers tasks like file manipulation, text processing, structured data, graphing and reporting, and marketing automation. The code examples are written in modern, well-structured Python code. Reading the book sequentially gives you a tour of some of the things can do with Python. It helps you recognize opportunities to automate your work, using the language, and helps build up your abilities to confidently use Python this way. It can also be used as a Cookbook, where you refer to specific chapters when working with particular use cases. I think this book is approachable even for people who are new to Python. I'd also recommend it to developers who already work with Python, for example with a web framework, and want to expand their knowledge into using the language to automate their daily workflows.

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Steven Klassen Jun 12, 2020

Disclaimer: I was offered a review copy by the publisher to write an honest review.I skimmed through this book over the course of a week paying close attention to the code samples. The writing is really very good and didn't set off any of my grammar alarms that are constantly waiting in the background when I'm reading anything. That made the technical bits a lot more enjoyable.There were a lot of examples that were light and that you could go through from start to finish without getting mired in complicated logic. I didn't find any issues with the code itself which was also nice.If I had to offer a critique for a 2nd edition (if it remains a cookbook style offering) it would be to maybe explain less and show more. While the information in this one was really well written it could have almost dropped cookbook from the title and still been worth its salt.

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Viktor Kis Jun 11, 2020

Really appreciate any book that starts off driving home the importance of setting virtual environments properly. Yes, a lot of information now days can be searched online, but if you are here, you are willing to chip in a little for a fresh set of neatly laid out concepts – and this book is just that. It is a great compilation of relatable example driven concepts. Regular expression, argument parsing, logging, directory manipulation, reading txt/pdf/image/csv/word/excel files are all bread and butter now days and if any of these topics daunted you, this book gives you a nice high-level intro into them. The web sections were great for me who has really only scrapped the web, I was exposed to other ideas such as automated emails and text messages. Although you don’t have to read the book chapter by chapter, I would have preferred to put the testing section up front to drive test driven development home a bit more. Overall it was a great read – thanks for collecting these ideas/examples and contributing back to the python community!

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Stephan Miller Jun 22, 2020

This book has a lot of information. First it shows you how to set up a Python environment for automation, including installing Python, setting up cron jobs to run your tasks on schedule, and adding notifications so you can get details on your jobs delivered to your email.And then it gets interesting. This book differs slightly from other cookbooks I have read that just list a bunch of small coding examples to do specific things. These recipes build on each other and can be mixed and matched to automate a process you are doing manually.The topics covered are web scraping, file processing, report generation, spreadsheet manipulation, data processing and cleaning, graph and chart generation, communication, marketing automation, machine learning, code testing and debugging. You will definitely find enough examples here to automate any process you may have and free up time.

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Matthew Emerick Jun 08, 2020

Disclaimer: The publisher asked me to review this book and gave me a review copy. I promise to be 100% honest in how I feel about this book, both the good and the less so.OverviewThis book is intended for someone who wants to automate some tasks, but may not be an overly technical person. They may have a Python background, but not necessarily so. They may be developers, but don't have to be. They just need to get something done, and don't want to keep doing it by hand.What I Like:This is a wide ranging book that gives the reader an opportunity to learn about libraries and techniques that they probably haven't seen before. Each section, or recipe, is set up the same. It starts with Getting Ready, which lists the required libraries, their version, and the command to set it up. Next is How To Do It, which gives the code. The code is, of course, available through the Packt website, as it is for any book with code. Then we have How It Works, which changes back to a more conversational tone and talks through the code example. The fourth section is There's More, which gives you a few tips to extend what was just taught. Each recipe finishes up with See Also, where you see what other recipes are related to the current one. This standard structure makes it easy to read through a recipe and focus on what you need.What I Don't Like:The title of this section is probably a little too strong. It would be better to say, What I Don't Prefer. However, this is how I've been organizing these reviews, and that's what I'l stick with for now.So what I don't prefer are the last few sections. Chapter 11 is about using machine learning. Anyone who has been following my book reviews knows that I love machine learning and other forms of artificial intelligence. This chapter, though, uses Google Cloud, which is an entirely different beast than what has been discussed. Machine learning itself is a skill to be learned, as is Google Cloud. It also sticks out as the only section in the book that uses anything from Google. I personally would have preferred to learn about using Python with Google Drive products, such as Docs, Sheets, Slides, and Sites. Many people use these technologies, and would probably welcome automating using them. Thankfully, the author finishes up with testing and debugging, which a less technical person will probably need.What I Would Like to See:Given how useful I tend to find cookbooks, I would like to see more recipes. As you would expect from having personal expectations, there are plenty of recipes that I don't think I'll need. But do I still gain value from them? Yes. It gives me an idea of what is possible that I haven't thought about yet. Maybe I'll need them one day. Or maybe I can use this book to guide someone else who has a question. It's a good reference book for a library all around.I can easily give this book a 5 out of 5. It is very useful with both the specific recipes as well as how they are organized. I would be very happy to see more books like this from Packt and would like to thank the author for this one.

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Python Automation Cookbook: 75 Python automation recipes for web scraping; data wrangling; and Excel, report, and email processing , Second Edition

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