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Python Web Scraping Cookbook

You're reading from   Python Web Scraping Cookbook Over 90 proven recipes to get you scraping with Python, microservices, Docker, and AWS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787285217
Length 364 pages
Edition 1st Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Scraping 2. Data Acquisition and Extraction FREE CHAPTER 3. Processing Data 4. Working with Images, Audio, and other Assets 5. Scraping - Code of Conduct 6. Scraping Challenges and Solutions 7. Text Wrangling and Analysis 8. Searching, Mining and Visualizing Data 9. Creating a Simple Data API 10. Creating Scraper Microservices with Docker 11. Making the Scraper as a Service Real 12. Other Books You May Enjoy

Crawling with delays

Fast scraping is considered a bad practice. Continuously pounding a website for pages can burn up CPU and bandwidth, and a robust site will identify you doing this and block your IP. And if you are unlucky, you might get a nasty letter for violating terms of service!

The technique of delaying requests in your crawler depends upon how your crawler is implemented. If you are using Scrapy, then you can set a parameter that informs the crawler how long to wait between requests. In a simple crawler just sequentially processing URLs in a list, you can insert a thread.sleep statement.

Things can get more complicated if you have implemented a distributed cluster of crawlers that spread the load of page requests, such as using a message queue with competing consumers. That can have a number of different solutions, which are beyond the scope provided in this context...

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