Automated scraping with Scrapely

For scraping the annotated fields Portia uses a library called Scrapely (https://github.com/scrapy/scrapely), which is a useful open-source tool developed independently from Portia. Scrapely uses training data to build a model of what to scrape from a web page. The trained model can then be applied to scrape other web pages with the same structure.

You can install it using pip:

pip install scrapely

Here is an example to show how it works:

  
>>> from scrapely import Scraper
>>> s = Scraper()
>>> train_url = 'http://example.webscraping.com/view/Afghanistan-1'
>>> s.train(train_url, {'name': 'Afghanistan', 'population': '29,121,286'})
>>> test_url = 'http://example.webscraping.com/view/United-Kingdom-239'
>>> s.scrape(test_url)
[{u'name': [u'United Kingdom&apos...