CrawlSpider

作用：用于进行全站数据爬取

CrawlSpider就是Spider的一个子类

如何新建一个基于CrawlSpider的爬虫文件

scrapy genspider -t crawl xxx www.xxx.com

例：choutiPro

LinkExtractor连接提取器：根据指定规则(正则)进行连接的提取

Rule规则解析器：将连接提取器提取到的连接进行请求发送，然后对获取的页面进行指定规则【callback】的解析

一个链接提取器对应唯一一个规则解析器

例：crawlspider深度(全栈)爬取【sunlinecrawl例】

分布式(通常用不到，爬取数据量级巨大、时间少时用分布式)

概念：可将一组程序执行在多态机器上(分布式机群)，使其进行数据的分布爬取

原生的scrapy框架是否可以实现分布式？

不能

抽屉

# spider文件

import scrapy

from scrapy.linkextractors import LinkExtractor

from scrapy.spiders import CrawlSpider, Rule

class ChoutiSpider(CrawlSpider):

name = 'chouti'

# allowed_domains = ['www.xxx.com']

start_urls = ['https://dig.chouti.com/1']

# 连接提取器：从起始url对应的页面中提取符合规则的所有连接；allow=正则表达式

# 正则为空的话，提取页面中所有连接

link = LinkExtractor(allow=r'\d+')

rules = (

# 规则解析器:将连接提取器提取到的连接对应的页面源码进行指定规则的解析

# Rule自动发送对应链接的请求

Rule(link, callback='parse_item', follow=True),

# follow：True 将连接提取器 继续 作用到 连接提取器提取出来的连接 对应的页面源码中

)

def parse_item(self, response):

item = {}

#item['domain_id'] = response.xpath('//input[@id="sid"]/@value').get()

#item['name'] = response.xpath('//div[@id="name"]').get()

#item['description'] = response.xpath('//div[@id="description"]').get()

return item

阳光热线网

# 1.spider文件

import scrapy

from scrapy.linkextractors import LinkExtractor

from scrapy.spiders import CrawlSpider, Rule

from sunLineCrawl.items import SunlinecrawlItem,ContentItem

class SunSpider(CrawlSpider):

name = 'sun'

# allowed_domains = ['www.xxx.com']

start_urls = ['http://wz.sun0769.com/index.php/question/questionType?type=4&page=']

link = LinkExtractor(allow=r'type=4&page=\d+') # 提取页码连接

link1 = LinkExtractor(allow=r'question/2019\d+/\d+\.shtml') # 提取详情页连接

rules = (

Rule(link, callback='parse_item', follow=False),

Rule(link1, callback='parse_detail'),

)

# 解析出标题和网友名称数据

def parse_item(self, response):

tr_list = response.xpath('//*[@id="morelist"]/div/table[2]//tr/td/table//tr')

for tr in tr_list:

title = tr.xpath('./td[2]/a[2]/text()').extract_first()

net_friend = tr.xpath('./td[4]/text()').extract_first()

item = SunlinecrawlItem()

item['title'] = title

item['net_friend'] = net_friend

yield item

# 解析出新闻的内容

def parse_detail(self,response):

content = response.xpath('/html/body/div[9]/table[2]//tr[1]/td/div[2]//text()').extract()

content = ''.join(content)

item = ContentItem()

item['content'] = content

yield item

--------------------------------------------------------------------------------

# 2.items文件

import scrapy

class SunlinecrawlItem(scrapy.Item):

title = scrapy.Field()

net_friend = scrapy.Field()

class ContentItem(scrapy.Item):

content = scrapy.Field()

--------------------------------------------------------------------------------

# 3.pipelines文件

class SunlinecrawlPipeline(object):

def process_item(self, item, spider):

# 确定接受到的item是什么类型(Content/Sunlinecrawl)

if item.__class__.__name__ == 'SunlinecrawlItem':

print(item['title'],item['net_friend'])

else:

print(item['content'])

return item

--------------------------------------------------------------------------------

# 4.setting文件

BOT_NAME = 'sunLineCrawl'

SPIDER_MODULES = ['sunLineCrawl.spiders']

NEWSPIDER_MODULE = 'sunLineCrawl.spiders'

LOG_LEVEL = 'ERROR'

USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.132 Safari/537.36'

ROBOTSTXT_OBEY = False

ITEM_PIPELINES = {

'sunLineCrawl.pipelines.SunlinecrawlPipeline': 300,

}

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。