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Website Scraping with Python

How to use BeautifulSoup and Scrapy in practice

Gábor László Hajba

A book about website scraping and data processing in Python. Which tool to use? How fast the tools are? I try to answer these questions in this book and help to gain a better understanding of website scraping with BeautifulSoup4 and Scrapy. I highlight some problems I encountered and perhaps you can encounter too -- with solutions.

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About

About

About the Book

New version by Apress

In 2018 I teamed-up with Apress and we released an updated version of this book. You can find it on Amazon: https://amzn.to/2Dkl4gI

This book is the follow-up of my previous one: "XML processing and website scraping in Java". There I looked at ways and tools to process XML and HTML in Java, did some performace comparisons and introduced some new programming concepts to make things even better.

In this book I take a closer look at website scraping with the two tools used nowadays: BeautifulSoup and Scrapy.

I create the sample application from the Java book -- now in Python, use the two tools for parsing, show examples how to export CSV files in Python.

As a bonus I will compare the two tools for their runtime, try to tweak where possible and I will give a quick introduction on plotting the runtimes as charts.

Until it is finished, you can buy the book for a discounted price. The final book will be around $35.

I will write about the following topics in this book:

  • BeautifulSoup
  • Scrapy
  • Performance comparison
  • Plotting in Python
  • Functional programming with Python
  • Parallel code execution with Python
  • Sample application to gather Amazon data
  • Other real-life projects (source code coming soon into the package)
  • Update for Scrapy's release and Python 3 (coming soon)

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SoftwareComputers and ProgrammingPythonData Science

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About the Author

Gábor László Hajba

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