Question

我正在尝试抓取多个表，这些表的表名存储在h3标记下。有数据列我可以没有问题，当我提供下一个网址时，我可以将此数据附加到csv文件。我无法解决的问题是获取表头并将其相对于表的每一行存储。这样做的原因是当下一个表被输入时我需要知道它属于哪个表。是否可以使用len循环我们说'Round'来建立表长度然后将表头写入每一行？是否可以处理项目导出？

这是我的代码 spider.py

from bigcrawler.items import BigcrawlerItem
from scrapy import Spider, Request, Selector

from scrapy.selector import Selector

from bigcrawler.items import MatchStatItemLoader

class CrawlbotSpider(Spider):
   name = 'bigcrawler'
   allowed_domains = ['www.matchstat.com']
   start_urls =   [ 

      'https://matchstat.com/tennis/tournaments/w/Taipei/2015',        
      'https://matchstat.com/tennis/tournaments/w/Hong%20Kong/2017',
                ]
def parse_header(self , response):
    hxs = Selector(response)
    for tb in hxs.css('tr.match'):

      heading = tb.xpath('//*[@id="AWS"]/div/h3/text()').extract()[0]

        for td in tb.xpath(".//tr[contains(@class, 
                    'match')]/td[contains(@class, 'round')]/text()"):
            il = BigcrawlerItem(selector=td)

            il.add_value('event_title' , heading)
            yield il.load_item()


 def parse(self , response):
    for row in response.css('tr.match'):
        il = MatchStatItemLoader(selector=row)
        il.add_css('round' , '.round::text')
        il.add_css('event1' , '.event-name a::text')
        il.add_css('player_1' , '.player-name:nth-child(2) a::text')
        il.add_css('player_2' , '.player-name:nth-child(3) a::text')
        il.add_css('player_1_odds' , '.odds-td.odds-0 
       [payout]::text')
        il.add_css('player_2_odds' , '.odds-td.odds-1 
       [payout]::text')
        il.add_css('h_2_h' , 'a.h2h::text')
        yield il.load_item()

items.py

   import scrapy

   from scrapy.loader import ItemLoader
   from scrapy.loader.processors import TakeFirst, MapCompose
   from operator import methodcaller
   from scrapy import Spider, Request, Selector

   class BigcrawlerItem(scrapy.Item):
  # define the fields for your item here like:

       event_title = scrapy.Field()

       round = scrapy.Field()

       event1 = scrapy.Field()

      player_1 = scrapy.Field()

      player_2 = scrapy.Field()

      player_1_odds = scrapy.Field()

     player_2_odds = scrapy.Field()

     h_2_h = scrapy.Field()


  class MatchStatItemLoader(ItemLoader):
  default_item_class = BigcrawlerItem
  default_input_processor = MapCompose(methodcaller('strip'))
  default_output_processor = TakeFirst()

Answer 1

如果只有其中一个标题，您不需要相对于当前节点，请尝试以下操作：

il.add_xpath('event_title', '//*[@id="AWS"]//h3/text()')

但如果您需要它相对于当前节点，您也可以这样做：

il.add_xpath('event_title', './ancestor::*[@id="AWS"]//h3/text()')

Answer 2

我建议完全不要使用Items类并使用start_requests方法而不是start_urls，因为它们确实令人困惑。请在此处查看完整的代码。另请注意match_heading变量。

class CrawlbotSpider(Spider):
   name = 'bigcrawler'
   allowed_domains = ['www.matchstat.com']
   start_urls =   [ 

      'https://matchstat.com/tennis/tournaments/w/Taipei/2015',        
      'https://matchstat.com/tennis/tournaments/w/Hong%20Kong/2017',
                ]

    def start_requests(self):
       match_urls =   [ 

          'https://matchstat.com/tennis/tournaments/w/Taipei/2015',        
          'https://matchstat.com/tennis/tournaments/w/Hong%20Kong/2017',
                    ]

        for url in match_urls:

            yield Request(url=url, callback=self.parse_matches)



    def parse_matches(self , response):
        match_heading = response.xpath('//*[@id="AWS"]/div/h3/text()').extract_first()

        for row in response.css('tr.match'):

            match = {}
            match['heading'] = match_heading
            match['round'] = row.css(".round::text").extract_first()
            match['event1'] = row.css(".event-name a::text").extract_first()
            match['player_1'] = row.css(".player-name:nth-child(2) a::text").extract_first()
            match['player_2'] = row.css(".player-name:nth-child(3) a::text").extract_first()
            match['player_1_odds'] = row.css(".odds-td.odds-0 [payout]::text").extract_first()
            match['player_2_odds'] = row.css(".odds-td.odds-1 [payout]::text").extract_first()
            match['h_2_h'] = row.css("a.h2h::text::text").extract_first()

            yield match

刮取多个表并将每个表头存储为csv中的行

2 个答案: