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Python Automation Cookbook

You're reading from   Python Automation Cookbook 75 Python automation recipes for web scraping; data wrangling; and Excel, report, and email processing

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Product type Paperback
Published in May 2020
Publisher Packt
ISBN-13 9781800207080
Length 526 pages
Edition 2nd Edition
Languages
Tools
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Author (1):
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Jaime Buelta Jaime Buelta
Author Profile Icon Jaime Buelta
Jaime Buelta
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Toc

Table of Contents (16) Chapters Close

Preface 1. Let's Begin Our Automation Journey 2. Automating Tasks Made Easy FREE CHAPTER 3. Building Your First Web Scraping Application 4. Searching and Reading Local Files 5. Generating Fantastic Reports 6. Fun with Spreadsheets 7. Cleaning and Processing Data 8. Developing Stunning Graphs 9. Dealing with Communication Channels 10. Why Not Automate Your Marketing Campaign? 11. Machine Learning for Automation 12. Automatic Testing Routines 13. Debugging Techniques 14. Other Books You May Enjoy
15. Index

Parsing HTML

Downloading raw text or a binary file is a good starting point, but the main language of the web is HTML.

HTML is a structured language, defining different parts of a document such as headings and paragraphs. HTML is also hierarchical, defining sub-elements. The ability to parse raw text into a structured document is basically the ability to extract information automatically from a web page. For example, some text can be relevant if enclosed in certain HTML elements, such as a class div or after a heading h3 tag.

Getting ready

We'll use the excellent Beautiful Soup module to parse HTML text into a memory object that can be analyzed. We need to use the latest version of the beautifulsoup4 package to be compatible with Python 3. Add the package to your requirements.txt and install the dependencies in the virtual environment:

$ echo "beautifulsoup4==4.8.2" >> requirements.txt
$ pip install -r requirements.txt

How to do it...

...
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