response object: >>> response.css('title') [] The result of running response.css('title') is a list-like object called SelectorList fine-grain the selection or extract the data. To extract the text from the title above, you can do: >>> response.css('title::text').extract() ['Quotes to Scrape'] There are two things to note here: one directly inside <title> element. If we don’t specify ::text, we’d get the full title element, including its tags: >>> response.css('title').extract() ['<title>Quotes to Scrapetitle>'] The other thing

response object: >>> response.css('title') [] The result of running response.css('title') is a list-like object called SelectorList fine-grain the selection or extract the data. To extract the text from the title above, you can do: >>> response.css('title::text').extract() ['Quotes to Scrape'] There are two things to note here: one directly inside <title> element. If we don’t specify ::text, we’d get the full title element, including its tags: >>> response.css('title').extract() ['<title>Quotes to Scrapetitle>'] The other thing

scrapy.Request(full_url, callback=self.parse_question) def parse_question(self, response): yield { 'title': response.css('h1 a::text').extract()[0], 'votes': response.css('.question .vote-count-post::text') s.json file a list of the most upvoted questions in StackOverflow in JSON format, containing the title, link, number of upvotes, a list of the tags and the question content in HTML, looking like this (reformatted ˓→array-faster-than-an-unsorted-array", "tags": ["java", "c++", "performance", "optimization"], "title": "Why is processing a sorted array faster than an unsorted array?", "votes": "9924" }, { "body":

response object: >>> response.css('title') [] The result of running response.css('title') is a list-like object called SelectorList fine-grain the selection or extract the data. To extract the text from the title above, you can do: >>> response.css('title::text').getall() ['Quotes to Scrape'] There are two things to note here: one directly inside <title> element. If we don’t specify ::text, we’d get the full title element, including its tags: >>> response.css('title').getall() ['<title>Quotes to Scrapetitle>'] The other thing

response object: >>> response.css('title') [] The result of running response.css('title') is a list-like object called SelectorList fine-grain the selection or extract the data. To extract the text from the title above, you can do: >>> response.css('title::text').extract() ['Quotes to Scrape'] There are two things to note here: one directly inside <title> element. If we don’t specify ::text, we’d get the full title element, including its tags: >>> response.css('title').extract() ['<title>Quotes to Scrapetitle>'] The other thing

response object: >>> response.css('title') [] The result of running response.css('title') is a list-like object called SelectorList fine-grain the selection or extract the data. To extract the text from the title above, you can do: >>> response.css('title::text').extract() ['Quotes to Scrape'] There are two things to note here: one directly inside <title> element. If we don’t specify ::text, we’d get the full title element, including its tags: >>> response.css('title').extract() ['<title>Quotes to Scrapetitle>'] The other thing

response object: >>> response.css('title') [] The result of running response.css('title') is a list-like object called SelectorList fine-grain the selection or extract the data. To extract the text from the title above, you can do: >>> response.css('title::text').extract() ['Quotes to Scrape'] There are two things to note here: one directly inside <title> element. If we don’t specify ::text, we’d get the full title element, including its tags: >>> response.css('title').extract() ['<title>Quotes to Scrapetitle>'] The other thing

callback=self.parse_question) def parse_question(self, response): yield { 'title': response.css('h1 a::text').extract()[0], 'votes': response.css('.question .vote-count- s.json file a list of the most upvoted questions in StackOverflow in JSON format, containing the title, link, number of upvotes, a list of the tags and the question content in HTML, looking like this (reformatted -faster-than-an-unsorted-array", "tags": ["java", "c++", "performance", "optimization"], "title": "Why is processing a sorted array faster than an unsorted array?", "votes": "9924" }, {

response object: >>> response.css('title') [] The result of running response.css('title') is a list-like object called SelectorList extract the data. To extract the text from the title above, you can do: 14 Chapter 2. First steps Scrapy Documentation, Release 1.2.3 >>> response.css('title::text').extract() ['Quotes to Scrape'] There directly inside <title> element. If we don’t specify ::text, we’d get the full title element, including its tags: >>> response.css('title').extract() ['<title>Quotes to Scrapetitle>'] The other thing

response object: >>> response.css('title') [] The result of running response.css('title') is a list-like object called SelectorList fine-grain the selection or extract the data. To extract the text from the title above, you can do: >>> response.css('title::text').extract() ['Quotes to Scrape'] 2.3. Scrapy Tutorial 13 Scrapy Documentation directly inside <title> element. If we don’t specify ::text, we’d get the full title element, including its tags: >>> response.css('title').extract() ['<title>Quotes to Scrapetitle>'] The other thing