Book Image

Python Web Scraping Cookbook

By : Michael Heydt
Book Image

Python Web Scraping Cookbook

By: Michael Heydt

Overview of this book

Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, caches, and more. You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills needed to design and develop reliable performance data flows, but also deploy your codebase to AWS. If you are involved in software engineering, product development, or data mining (or are interested in building data-driven products), you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with Ajax websites, paginated items, and more. You will also learn to tackle problems such as 403 errors, working with proxy, scraping images, and LXML. By the end of this book, you will be able to scrape websites more efficiently and able to deploy and operate your scraper in the cloud.
Table of Contents (13 chapters)

Identifying and removing rare words

We can remove words with low occurences by leveraging the ability to find words with low frequency counts, that fall outside of a certain deviation of the norm, or just from a list of words considered to be rare within the given domain. But the technique we will use works the same for either.

How to do it

Rare words can be removed by building a list of those rare words and then removing them from the set of tokens being processed. The list of rare words can be determined by using the frequency distribution provided by NTLK. Then you decide what threshold should be used as a rare word threshold:

  1. The script in the 07/07_rare_words.py file extends that of the frequency distribution recipe...