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Python Web Scraping

You're reading from   Python Web Scraping Successfully scrape data from any website with the power of Python

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Product type Hardcover
Published in May 2017
Last Updated in Feb 2025
Publisher Packt
ISBN-13 9781786462589
Length 220 pages
Edition 1st Edition
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Author (1):
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Richard Penman Richard Penman
Author Profile Icon Richard Penman
Richard Penman
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Summary

This chapter covered two approaches to scraping data from dynamic web pages. It started with reverse engineering a dynamic web page using browser tools, and then moved on to using a browser renderer to trigger JavaScript events for us. We first used WebKit to build our own custom browser, and then reimplemented this scraper with the high-level Selenium framework.

A browser renderer can save the time needed to understand how the backend of a website works; however, there are some disadvantages. Rendering a web page adds overhead and is much slower than just downloading the HTML or using API calls. Additionally, solutions using a browser renderer often require polling the web page to check whether the resulting HTML has loaded, which is brittle and can fail when the network is slow.

I typically use a browser renderer for short-term solutions where the long-term performance and reliability is less important...

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Python Web Scraping
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