and efficient, such as: • Built-in support for selecting and extracting data from HTML and XML sources • Built-in support for cleaning and sanitizing the scraped data using a collection of reusable filters commands' 3.2 Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy provides the Item class for this purpose. Item objects are simple def parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.contrib.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls

easy and efficient, such as: Built-in support for selecting and extracting data from HTML and XML sources Built-in support for cleaning and sanitizing the scraped data using a collection of reusable filters documentation » Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy provides the Item class for this purpose. Item objects are simple parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.contrib.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls

easy and efficient, such as: • Built-in support for selecting and extracting data from HTML/XML sources using extended CSS selectors and XPath expressions, with helper methods to extract using regular def parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls = very rare though. Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy spiders can return the extracted data as Python dicts. While convenient

easy and efficient, such as: • Built-in support for selecting and extracting data from HTML/XML sources using extended CSS selectors and XPath expressions, with helper methods to extract using regular def parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls = very rare though. Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy spiders can return the extracted data as Python dicts. While convenient

scraping easy and efficient, such as: Built-in support for selecting and extracting data from HTML/XML sources using extended CSS selectors and XPath expressions, with helper methods to extract using regular parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls very rare though. Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy spiders can return the extracted data as Python dicts. While convenient

scraping easy and efficient, such as: Built-in support for selecting and extracting data from HTML/XML sources using extended CSS selectors and XPath expressions, with helper methods to extract using regular parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls very rare though. Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy spiders can return the extracted data as Python dicts. While convenient

scraping easy and efficient, such as: Built-in support for selecting and extracting data from HTML/XML sources using extended CSS selectors and XPath expressions, with helper methods to extract using regular parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls very rare though. Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy spiders can return the extracted data as Python dicts. While convenient

scraping easy and efficient, such as: Built-in support for selecting and extracting data from HTML/XML sources using extended CSS selectors and XPath expressions, with helper methods to extract using regular parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls very rare though. Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy spiders can return the extracted data as Python dicts. While convenient

easy and efficient, such as: Built-in support for selecting and extracting data from HTML and XML sources Built-in support for cleaning and sanitizing the scraped data using a collection of reusable filters documentation » Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy provides the Item class for this purpose. Item objects are simple parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.contrib.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls

and efficient, such as: • Built-in support for selecting and extracting data from HTML and XML sources • Built-in support for cleaning and sanitizing the scraped data using a collection of reusable filters commands' 3.2 Items The main goal in scraping is to extract structured data from unstructured sources, typically, web pages. Scrapy provides the Item class for this purpose. Item objects are simple def parse_shop(self, response): pass # ... scrape shop here ... Combine SitemapSpider with other sources of urls: from scrapy.contrib.spiders import SitemapSpider class MySpider(SitemapSpider): sitemap_urls