我使用Scrapy Framework制作了一个网络刮刀,以获取this website的音乐会门票数据。我已经能够成功地从页面上每个票证内的元素中获取数据,除了只能通过单击"票证"按钮转到故障单页面并从页面上的故障单中刮取票价。
经过广泛的谷歌搜索后,我发现Scrapy.js(基于Splash)可以在Scrapy中用于与页面上的JavaScript交互(例如需要点击的按钮)。我已经看到了Splash用于与JavaScript交互的一些基本示例,但没有一个示例Splash与Scrapy的集成(甚至在文档中都没有)。
我一直在遵循使用项目加载器将格式化元素存储在parse方法中的格式,然后发出一个请求,该请求应该转到另一个链接并通过调用第二个解析方法解析该页面中的html
(e.g. yield scrapy.Request(next_link, callback=self.parse_price)
但是,由于我将使用Scrapy js,因此代码会有所改变。为了整合Scrapyjs,我考虑使用类似的功能:
function main(splash)
splash:go("http://example.com")
splash:wait(0.5)
local title = splash:evaljs("document.title")
return {title=title}
来自this site,但由于javascript无法直接在python程序中编写,我甚至可以在哪里/哪里将这种函数合并到程序中,以便能够导航到下一个页面单击按钮并解析HTML?我显然非常擅长网络抓取,所以任何帮助都会非常感激。蜘蛛的代码如下:
from scrapy.contrib.spiders import CrawlSpider , Rule
from scrapy.selector import HtmlXPathSelector
from scrapy.selector import Selector
from scrapy.contrib.loader import XPathItemLoader
from scrapy.contrib.loader.processor import Join, MapCompose
from concert_comparator.items import ComparatorItem
bandname = raw_input("Enter a bandname \n")
vs_url = "http://www.vividseats.com/concerts/" + bandname + "-tickets.html"
class MySpider(CrawlSpider):
handle_httpstatus_list = [416]
name = 'comparator'
allowed_domains = ["www.vividseats.com"]
start_urls = [vs_url]
#rules = (Rule(LinkExtractor(allow=('/' + bandname + '-.*', )), callback='parse_price'))
# item = ComparatorItem()
tickets_list_xpath = './/*[@itemtype="http://schema.org/Event"]'
item_fields = {
'eventName' : './/*[@class="productionsEvent"]/text()',
'eventLocation' : './/*[@class = "productionsVenue"]/span[@itemprop = "name"]/text()',
'ticketsLink' : './/a/@href',
'eventDate' : './/*[@class = "productionsDate"]/text()',
'eventCity' : './/*[@class = "productionsVenue"]/span[@itemprop = "address"]/span[@itemprop = "addressLocality"]/text()',
'eventState' : './/*[@class = "productionsVenue"]/span[@itemprop = "address"]/span[@itemprop = "addressRegion"]/text()',
'eventTime' : './/*[@class = "productionsTime"]/text()'
}
item_fields2 = {
'ticketPrice' : '//*[@class="eventTickets lastChild"]/div/div/@data-origin-price]',
}
def parse_price(self, response):
l.add_xpath('ticketPrice','.//*[@class = "price"]/text()' )
yield l.load_item()
def parse(self, response):
"""
"""
selector = HtmlXPathSelector(response)
# iterate over tickets
for ticket in selector.select(self.tickets_list_xpath):
loader = XPathItemLoader(ComparatorItem(), selector=ticket)
# define loader
loader.default_input_processor = MapCompose(unicode.strip)
loader.default_output_processor = Join()
# iterate over fields and add xpaths to the loader
for field, xpath in self.item_fields.iteritems():
loader.add_xpath(field, xpath)
yield Request(vs_url, self.parse_result, meta= {
'splash': {
'args':{
#set rendering arguments here
'html' :1
# 'url' is prefilled from request url
},
#optional parameters
function main(splash)
splash:autoload("https://ajax.googleapis.com/ajax/libs/jquery/2.1.3/jquery.min.js")
splash:go(vs_url)
splash:runjs("$('#some-button').click()")
return splash:html()
end
}
})
for field, xpath in self.item_fields2.iteritems():
loader.add_xpath(field, xpath)
yield loader.load_item()
答案 0 :(得分:1)
这里的关键点是 scrapyjs
提供了configure所需的scrapyjs.SplashMiddleware
中间件。然后,每个具有splash
meta key的请求都将由中间件处理。
仅供参考,我之前已成功将Scrapy
与scrapyjs
一起使用。