Pypi Example ----------------------------------- Lets make a scraper that extract data from the pypi's front page http://pypi.python.org/pypi Supose that we want extract data from the packages table and store it in a database. First at all we need to start a new crawley's project. In this case it will be called pypi_packages. .. code-block:: bash crawley startproject pypi_packages cd pypi_packages Then, inside the pypi_packages there will a settings.py file and another directory containing a crawlers.py file and a models.py file. Lets start defining the models.py wich is very simple in this case. Models =========== .. code-block:: python from crawley.persistance import Entity, UrlEntity, Field, Unicode class Package(Entity): #add your table fields here updated = Field(Unicode(255)) package = Field(Unicode(255)) description = Field(Unicode(255)) As you can see, we just need a simple Package table that matches the data we want to extract. Ok, now is time to code. Lets make the scraper. It must be located inside the crawlers.py file Crawlers =========== .. code-block:: python from crawley.crawlers import BaseCrawler from crawley.scrapers import BaseScraper from crawley.extractors import XPathExtractor from models import * class pypiScraper(BaseScraper): #specify the urls that can be scraped by this class matching_urls = ["%"] def scrape(self, response): #getting the html table table = response.html.xpath("/html/body/div[5]/div/div/div[3]/table")[0] #for rows 1 to n-1 for tr in table[1:-1]: #obtaining the searched html inside the rows td_updated = tr[0] td_package = tr[1] package_link = td_package[0] td_description = tr[2] #storing data in Packages table Package(updated=td_updated.text, package=package_link.text, description=td_description.text) class pypiCrawler(BaseCrawler): #add your starting urls here start_urls = ["http://pypi.python.org/pypi"] #add your scraper classes here scrapers = [pypiScraper] #specify you maximum crawling depth level max_depth = 0 #select your favourite HTML parsing tool extractor = XPathExtractor The interesting part of this is the scrape method defined inside the pypiScraper class. It uses Xpath in order to obtain the parsed html and then stores the extracted data in the Packages table. At this time we have finished our work. Very simple. Isn't it? Run crawley =========== Finally, just run the crawler (Ensure you are in the same directory where the settings.py file is, in other case you can specify your settings directory with --settings=path/to/your/settings.py) .. code-block:: bash ~$ crawley run And we are done. Check the results in your database! Downloading the Code ==================== The entire code is located in the crawley's official repository at: https://github.com/jmg/crawley/tree/master/examples/pypi_packages