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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 Paperback
Published in Oct 2015
Publisher Packt
ISBN-13 9781782164364
Length 174 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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Toc

One million web pages

To test the performance of concurrent downloading, it would be preferable to have a larger target website. For this reason, we will use the Alexa list in this chapter, which tracks the top 1 million most popular websites according to users who have installed the Alexa Toolbar. Only a small percentage of people use this browser plugin, so the data is not authoritative, but is fine for our purposes.

These top 1 million web pages can be browsed on the Alexa website at http://www.alexa.com/topsites. Additionally, a compressed spreadsheet of this list is available at http://s3.amazonaws.com/alexa-static/top-1m.csv.zip, so scraping Alexa is not necessary.

Parsing the Alexa list

The Alexa list is provided in a spreadsheet with columns for the rank and domain:

Parsing the Alexa list

Extracting this data requires a number of steps, as follows:

  1. Download the .zip file.
  2. Extract the CSV file from this .zip file.
  3. Parse the CSV file.
  4. Iterate each row of the CSV file to extract the domain.

Here is an implementation...

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