Crawl a website with Scrapy in Python

Crawl web pages appearing in the home page of start url indicated below. There are many categories of news in the home page, but only editorials and international sections should be crawled. Scraped data should be stored into MongoDb database in the pipeline and download the web pages as .html and save it to the disk. Only three fields are required as indicated below. Since the website is protected by CloudFlare, use cfscrape to open the request session in Scrapy. For, this task, follow only page 1 and 2 of the paginator of editorials and international section. Not required to crawl entire website or other sections. Replace [login to view URL] with actual domain indicated in the start url. Thanks. Fields: article = [login to view URL]() title = [login to view URL]() date = [login to view URL]() start url: [login to view URL] follow link patterns: [login to view URL] [login to view URL] Format of target data: Article content <div class="content node-article"> <p>Some text in para 1</p> <p>Some text in para 2</p> <p>Some text in para 3</p> </div> 2. Title <span property="dc:title" content="Quick brown fox….." class="rdf-meta element-hidden"></span> 3. Date <span property="dc:date dc:created" content="2015-11-20T17:08:53+06:30" datatype="xsd:dateTime">Fri, 11/20/2015 - 17:08</span>