python之Scrapy，从第二组链接中抓取页面

我今天一直在浏览 Scrapy 文档并试图获得一个工作版本 - https://docs.scrapy.org/en/latest/intro/tutorial.html#our-first-spider - 一个真实世界的例子。我的示例略有不同，因为它有 2 个下一页，即

start_url > city page > unit page

就是我要抓取数据的单位页面。

我的代码:

import scrapy 
 
 
class QuotesSpider(scrapy.Spider): 
    name = "quotes" 
    start_urls = [ 
        'http://www.unitestudents.com/', 
            ] 
 
    def parse(self, response): 
        for quote in response.css('div.property-body'): 
            yield { 
                'name': quote.xpath('//span/a/text()').extract(), 
                'type': quote.xpath('//div/h4/text()').extract(), 
                'price_amens': quote.xpath('//div/p/text()').extract(), 
                'distance_beds': quote.xpath('//li/p/text()').extract() 
            } 
 
            # Purpose is to crawl links of cities 
            next_page = response.css('a.listing-item__link::attr(href)').extract_first() 
            if next_page is not None: 
                next_page = response.urljoin(next_page) 
                yield scrapy.Request(next_page, callback=self.parse) 
 
            # Purpose is to crawl links of units 
            next_unit_page = response.css(response.css('a.text-highlight__inner::attr(href)').extract_first()) 
            if next_unit_page is not None: 
                                          next_unit_page = response.urljoin(next_unit_page) 
                                          yield scrapy.Request(next_unit_page, callback=self.parse) 

但是当我运行它时我得到:

INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min) 

所以我认为我的代码未设置为检索上述流程中的链接，但我不确定如何最好地做到这一点？

更新流程:

Main page > City page > Building page > Unit page

它仍然是我要从中获取数据的单元页面。

更新代码:

import scrapy 
 
 
class QuotesSpider(scrapy.Spider): 
    name = "quotes" 
    start_urls = [ 
        'http://www.unitestudents.com/', 
            ] 
 
    def parse(self, response): 
        for quote in response.css('div.site-wrapper'): 
            yield { 
                'area_name': quote.xpath('//div/ul/li/a/span/text()').extract(), 
                'type': quote.xpath('//div/div/div/h1/span/text()').extract(), 
                'period': quote.xpath('/html/body/div/div/section/div/form/h4/span/text()').extract(), 
                'duration_weekly': quote.xpath('//html/body/div/div/section/div/form/div/div/em/text()').extract(), 
                'guide_total': quote.xpath('//html/body/div/div/section/div/form/div/div/p/text()').extract(),               
                'amenities': quote.xpath('//div/div/div/ul/li/p/text()').extract(),               
            } 
 
            # Purpose is to crawl links of cities 
            next_page = response.xpath('//html/body/div/footer/div/div/div/ul/li/a[@class="listing-item__link"]/@href').extract() 
            if next_page is not None: 
                next_page = response.urljoin(next_page) 
                yield scrapy.Request(next_page, callback=self.parse) 
 
            # Purpose is to crawl links of units 
            next_unit_page = response.xpath('//li/div/h3/span/a/@href').extract() 
            if next_unit_page is not None: 
                                          next_unit_page = response.urljoin(next_unit_page) 
                                          yield scrapy.Request(next_unit_page, callback=self.parse) 
 
            # Purpose to crawl crawl pages on full unit info 
 
            last_unit_page = response.xpath('//div/div/div[@class="content__btn"]/a/@href').extract() 
            if last_unit_page is not None: 
                last_unit_page = response.urljoin(last_unit_page) 
                yield scrapy.Request(last_unit_page, callback=self.parse) 

请您参考如下方法:

让我们从逻辑开始:

1. 抓取主页 - 获取所有城市
2. 抓取城市页面 - 获取所有单元 url
3. 抓取单元页面 - 获取所有需要的数据

我在下面的 scrapy 蜘蛛中做了一个例子来说明如何实现它。我无法找到您在示例代码中提到的所有信息，但我希望代码足够清晰，让您能够理解它的作用以及如何添加所需的信息。

import scrapy 
 
 
class QuotesSpider(scrapy.Spider): 
    name = "quotes" 
    start_urls = [ 
        'http://www.unitestudents.com/', 
            ] 
 
    # Step 1 
    def parse(self, response): 
        for city in response.xpath('//select[@id="frm_homeSelect_city"]/option[not(contains(text(),"Select your city"))]/text()').extract(): # Select all cities listed in the select (exclude the "Select your city" option) 
            yield scrapy.Request(response.urljoin("/"+city), callback=self.parse_citypage) 
 
    # Step 2 
    def parse_citypage(self, response): 
        for url in response.xpath('//div[@class="property-header"]/h3/span/a/@href').extract(): #Select for each property the url 
            yield scrapy.Request(response.urljoin(url), callback=self.parse_unitpage) 
 
        # I could not find any pagination. Otherwise it would go here. 
 
    # Step 3 
    def parse_unitpage(self, response): 
        unitTypes = response.xpath('//div[@class="room-type-block"]/h5/text()').extract() + response.xpath('//h4[@class="content__header"]/text()').extract() 
        for unitType in unitTypes: # There can be multiple unit types so we yield an item for each unit type we can find. 
            yield { 
                'name': response.xpath('//h1/span/text()').extract_first(), 
                'type': unitType, 
                # 'price': response.xpath('XPATH GOES HERE'), # Could not find a price on the page 
                # 'distance_beds': response.xpath('XPATH GOES HERE') # Could not find such info 
            } 

我认为代码非常简洁。评论应该阐明为什么我选择使用 for 循环。如果有什么不清楚的地方，请告诉我，我会尽力解释。