How Scrapy and Selenium are used in Analyzing and Scraping News Articles?

				
					import scrapy
    from selenium import webdriver
    from selenium.webdriver.chrome.options import Options
    from scrapy.selector import Selector
    import time
    

    

    class CnnSpider(scrapy.Spider):
        name = 'cnn'
        allowed_domains = ['www.cnn.com']
        start_urls = ['https://www.cnn.com']
        
        # initiating selenium
        def __init__(self):
            
            # set up the driver
            chrome_options = Options()
            # chrome_options.add_argument("--headless") # uncomment if don't want to appreciate the sight of a possessed browser
            driver = webdriver.Chrome(executable_path=str('./chromedriver'), options=chrome_options)
            driver.get("https://www.cnn.com")
            
            # begin search
            search_input = driver.find_element_by_id("footer-search-bar") # find the search bar
            search_input.send_keys("immigration") # type in the search term
            search_btn = driver.find_element_by_xpath("(//button[contains(@class, 'Flex-sc-1')])[2]") # find the search button
            search_btn.click()
            
            # record the first page
            self.html = [driver.page_source]
            
            # start turning pages
            i = 0
            while i < 100: # 100 is just right to get us back to July
                i += 1
                time.sleep(5) # just in case the next button hasn't finished loading
                next_btn = driver.find_element_by_xpath("(//div[contains(@class, 'pagination-arrow')])[2]") # click next button
                next_btn.click()
                self.html.append(driver.page_source) # not the best way but will do
                
        # using scrapy's native parse to first scrape links on result pages
        def parse(self, response):
            for page in self.html:
                resp = Selector(text=page)
                results = resp.xpath("//div[@class='cnn-search__result cnn-search__result--article']/div/h3/a") # result iterator
                for result in results:
                    title = result.xpath(".//text()").get()
                    if ("Video" in title) | ("coronavirus news" in title) | ("http" in title):
                        continue # ignore videos and search-independent news or ads
                    else:
                        link = result.xpath(".//@href").get()[13:] # cut off the domain; had better just use request in fact
                        yield response.follow(url=link, callback=self.parse_article, meta={"title": title})
    

        # pass on the links to open and process actual news articles
        def parse_article(self, response):
            title = response.request.meta['title']
            
            # several variations of author's locator
            authors = response.xpath("//span[@class='metadata__byline__author']//text()").getall()
            if len(authors) == 0:
                authors = response.xpath("//p[@data-type='byline-area']//text()").getall()
                if len(authors) == 0:
                    authors = response.xpath("//div[@class='Article__subtitle']//text()").getall()
            
            # two variations of article body's locator
            content = ' '.join(response.xpath("//section[@id='body-text']/div[@class='l-container']//text()").getall())
            if content is None:
                content = ' '.join(response.xpath("//div[@class='Article__content']//text()").getall())
            yield {
                "title": title,
                "byline": ' '.join(authors), # could be multiple authors
                "time": response.xpath("//p[@class='update-time']/text()").get(),
                "content": content
            }