Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python Web Scraping

You're reading from   Python Web Scraping Hands-on data scraping and crawling using PyQT, Selnium, HTML and Python

Arrow left icon
Product type Paperback
Published in May 2017
Publisher
ISBN-13 9781786462589
Length 220 pages
Edition 2nd Edition
Languages
Tools
Concepts
Arrow right icon
Author (1):
Arrow left icon
Katharine Jarmul Katharine Jarmul
Author Profile Icon Katharine Jarmul
Katharine Jarmul
Arrow right icon
View More author details
Toc

Comparing performance

To help evaluate the trade-offs between the three scraping approaches described in the section, Three approaches to scrape a web page, it would be helpful to compare their relative efficiency. Typically, a scraper would extract multiple fields from a web page. So, for a more realistic comparison, we will implement extended versions of each scraper which extract all the available data from a country's web page. To get started, we need to return to our browser to check the format of the other country features, as shown here:

By using our browser's inspect capabilities, we can see each table row has an ID starting with places_ and ending with __row. The country data is contained within these rows in the same format as the area example. Here are implementations that use this information to extract all of the available country data:

FIELDS = ('area', 'population',...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime