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 formats and patterns in APIs

Data available through APIs might be different from what you expected or might not fit the plan exactly – in the Benefits of web APIs section, we covered a few of the ways the data might be different (limitation, irrelevance, and more).

Acquiring data from APIs is a straightforward process with or without API authorization. Content received via an API may appear in many formats, such as key names, nested lists and dictionaries, named or numerical indexing blocks, and many more. We generally find API content in JSON format, comprising Python lists and dictionaries.

Before moving on to the data formats, patterns, and results of APIs or API content, it is important to demonstrate how APIs are called or used. Most of the time, API service providers keep an updated version of their APIs in their documentation. Listed here are a few examples that web users normally use to access data from an API (example URL: exampledomain.com):

  • http...