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Hands-On Web Scraping with Python - Second Edition

You're reading from Hands-On Web Scraping with Python - Second Edition

Product type Book

Published in Oct 2023

Publisher Packt

ISBN-13 9781837636211

Pages 324 pages

Edition 2nd Edition

Languages

Concepts

Web Programming

Author (1):

Anish Chapagain

Table of Contents (20) Chapters

Preface

1. Part 1:Python and Web Scraping

2. Chapter 1: Web Scraping Fundamentals

3. Chapter 2: Python Programming for Data and Web

4. Part 2:Beginning Web Scraping

5. Chapter 3: Searching and Processing Web Documents

6. Chapter 4: Scraping Using PyQuery, a jQuery-Like Library for Python

7. Chapter 5: Scraping the Web with Scrapy and Beautiful Soup

8. Part 3:Advanced Scraping Concepts

9. Chapter 6: Working with the Secure Web

10. Chapter 7: Data Extraction Using Web APIs

11. Chapter 8: Using Selenium to Scrape the Web

12. Chapter 9: Using Regular Expressions and PDFs

13. Part 4:Advanced Data-Related Concepts

14. Chapter 10: Data Mining, Analysis, and Visualization

15. Chapter 11: Machine Learning and Web Scraping

16. Part 5:Conclusion

17. Chapter 12: After Scraping – Next Steps and Data Analysis

18. Index

Why subscribe?

19. Other Books You May Enjoy

Data processing

Data processing, in the context of web scraping, refers to storing, handling, managing, and analyzing the data that is generated from scraping. In previous chapters of the book, we focused on the concept of effective and efficient scraping with code examples.

As the demand for data is growing, technologies are also evolving and adapting to new changes. Currently, as there has been a boom in AI/ML-based systems, there is competition to provide easy and quick solutions to problems without compromising on quality.

In the coming sections, we will introduce some technologies that help with data processing.

PySpark

The Python library for Apache Spark, pyspark (https://spark.apache.org/), is used to process and analyze data, especially of a large volume. Spark is a framework that is used to handle big data (data with variety, volume, and velocity) and is more effective than Hadoop (https://hadoop.apache.org/), a framework for parallel processing, scheduling, and...

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Authors (1)

Anish Chapagain

Anish Chapagain is a software engineer with a passion for data science, its processes, and Python programming, which began around 2007. He has been working with web scraping and analysis-related tasks for more than 5 years, and is currently pursuing freelance projects in the web scraping domain. Anish previously worked as a trainer, web/software developer, and as a banker, where he was exposed to data and gained further insights into topics including data analysis, visualization, data mining, information processing, and knowledge discovery. He has an MSc in computer systems from Bangor University (University of Wales), United Kingdom, and an Executive MBA from Himalayan Whitehouse International College, Kathmandu, Nepal.

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