Question

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

start_url＆gt;城市页面＆gt;单位页面

这是我想要从中获取数据的单位页面。

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)

但是当我跑步时，我得到了：

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

所以我认为我的代码没有设置为检索上面提到的流程中的链接，但我不确定如何最好地做到这一点？

更新了流程：

主页＆gt;城市页面＆gt;构建页面＆gt;单位页面

它仍然是我想从中获取数据的单位页面。

更新的代码：

import scrapy


class QuotesSpider(scrapy.Spider):
    name = "quotes"
    start_urls = [
        'http://www.unitestudents.com/',
            ]

    def parse(self, response):
        for quote in response.css('div.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)

Answer 1

让我们从逻辑开始：

抓住主页 - 抓取所有城市
抓住城市页面 - 获取所有单位网址
抓单位页面 - 获取所有需要的数据

我已经举例说明了如何在下面的scrapy蜘蛛中实现这一点。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，以便您了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
            }

我认为代码非常干净简单。评论应该澄清为什么我选择使用for循环。如果事情不明确，请告诉我，我会尝试解释。

Scrapy，从第二组链接中抓取页面

1 个答案: