Book Image

Hands-On Web Scraping with Python - Second Edition

By : Anish Chapagain
Book Image

Hands-On Web Scraping with Python - Second Edition

By: Anish Chapagain

Overview of this book

Web scraping is a powerful tool for extracting data from the web, but it can be daunting for those without a technical background. Designed for novices, this book will help you grasp the fundamentals of web scraping and Python programming, even if you have no prior experience. Adopting a practical, hands-on approach, this updated edition of Hands-On Web Scraping with Python uses real-world examples and exercises to explain key concepts. Starting with an introduction to web scraping fundamentals and Python programming, you’ll cover a range of scraping techniques, including requests, lxml, pyquery, Scrapy, and Beautiful Soup. You’ll also get to grips with advanced topics such as secure web handling, web APIs, Selenium for web scraping, PDF extraction, regex, data analysis, EDA reports, visualization, and machine learning. This book emphasizes the importance of learning by doing. Each chapter integrates examples that demonstrate practical techniques and related skills. By the end of this book, you’ll be equipped with the skills to extract data from websites, a solid understanding of web scraping and Python programming, and the confidence to use these skills in your projects for analysis, visualization, and information discovery.
Table of Contents (20 chapters)
1
Part 1:Python and Web Scraping
4
Part 2:Beginning Web Scraping
8
Part 3:Advanced Scraping Concepts
13
Part 4:Advanced Data-Related Concepts
16
Part 5:Conclusion

Data extraction from a PDF

PDF is a rich (in terms of containing document features and formatting) document format that can be created, shared, and accessed on any supporting device. It is not an understatement to state that PDF files are everywhere, supported by all kinds of electronic devices and systems. It is also quite useful to know that Word documents, PowerPoint presentations, HTML, Jupyter notebooks, analysis reports from various applications, and many more content types support exporting and saving files as PDF.

We often find various types of data (such as textual, tabular, and images) in a PDF file. In Chapters 3 and 4, we saw how to extract web-based content using Python. Here, we will be using the PyPDF2 Python library to extract data from PDF files.

In the next sections, we will install and explore PyPDF2 from a data extraction perspective.

The PyPDF2 library

PyPDF2 (https://pypdf2.readthedocs.io/en/3.0.0/index.html) is a free, open source (https://github...