![]() ![]() Links = response.css('.css-8atqhb a::attr(href)').extract() descriptions = response.css('.css-1pfq5u').extract() Similarly, we try and find the class names of the description element and the link element (note that the class names might change by the time you run this code. Titles = response.css('.css-1m5bs2v').extract() You can see that the CSS class name of the title element is CSS-1m5bs2v, so we are going to ask scrapy to get us the contents of this class like this. This will open the Google Chrome Inspector like below. Go to the URL and right-click on the title of one of the editorial stories and click on inspecting. We now need to find the CSS selector of the elements we need to extract the data. Here is where we can write our code to extract the data we want. The def parse(self, response): Scrapy calls a function after every successful URL crawl. For us, in this example, we only need one URL. ![]() The allowed_domains array restricts all further crawling to the domain paths specified here. Let's examine this code before we proceed. Now open the file ourfirstbot.py in the spider's folder. This should return successfully like this.Ĭreated spider 'ourfirstbot' using template 'basic' in module: We call the spider ourfirstbot and pass it the URL of the New York Times page. So we use the genspider to tell scrapy to create one for us. Now we need a spider to crawl through the NYT page. Applications/MAMP/htdocs/scrapy_examples/scrapingproject New Scrapy project 'scrapingproject', using template directory '/Library/Python/2.7/site-packages/scrapy/templates/project', created in: Once installed, go ahead and create a project by invoking the startproject command. Today lets see how we can scrape The New York Times to get their Editorial section.įirst, we need to install Scrapy if you haven't already. ![]() Scrapy is one of the most accessible tools that you can use to scrape and also spider a website with effortless ease. ![]()
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