A few years ago I developed the sitescraper library for automatically scraping website data based on example cases:
See this paper for more info.
>>> from sitescraper import sitescraper>>> ss = sitescraper() >>> url = 'http://www.amazon.com/s/ref=nb_ss_gw?url=search-alias%3Daps&field-keywords=python&x=0&y=0' >>> data = ["Amazon.com: python", ["Learning Python, 3rd Edition", "Programming in Python 3: A Complete Introduction to the Python Language (Developer's Library)", "Python in a Nutshell, Second Edition (In a Nutshell (O'Reilly))"]] >>> ss.add(url, data) >>> # we can add multiple example cases, but this is a simple example so 1 will do (I generally use 3) >>> # ss.add(url2, data2) >>> ss.scrape('http://www.amazon.com/s/ref=nb_ss_gw?url=search-alias%3Daps&field-keywords=linux&x=0&y=0') ["Amazon.com: linux", ["A Practical Guide to Linux(R) Commands, Editors, and Shell Programming", "Linux Pocket Guide", "Linux in a Nutshell (In a Nutshell (O'Reilly))", 'Practical Guide to Ubuntu Linux (Versions 8.10 and 8.04), A (2nd Edition)', 'Linux Bible, 2008 Edition: Boot up to Ubuntu, Fedora, KNOPPIX, Debian, openSUSE, and 11 Other Distributions']]
See this paper for more info.
It was designed for scraping websites overtime where their layout may change. Unfortunately I don't use it much these days because most of my projects are one-off scrapes.