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  • 增量式 爬虫

    增量式 爬虫

    概念: 监测网站的数据更新的情况,只爬取网站更新的数据.

    核心: 去重

    实现 Redis  set集合也行

    --  如何实现redis去重? -- 

    # 爬取电影站的更新数据   url去重  https://www.4567tv.tv/frim/index1.html
    # 下面代码以
    http://www.922dyy.com/dianying/dongzuopian/ 为例 作为起始页
    # spider.py 爬虫文件
    # -*- coding: utf-8 -*-
    import scrapy
    from scrapy.linkextractors import LinkExtractor
    from scrapy.spiders import CrawlSpider, Rule
    from redis import Redis
    from shipin.items import ShipinItem
    class DianyingSpider(CrawlSpider):
        conn = Redis(host='127.0.0.1',port=6379) # 连接对象
        name = 'dianying'
        # allowed_domains = ['www.xx.com']
        start_urls = ['http://www.922dyy.com/dianying/dongzuopian/']
    
        rules = (
            Rule(LinkExtractor(allow=r'/dongzuopian/indexd+.html'), callback='parse_item', follow=False), #这里需要所有页面时候改为True
        )  # 只提取页码url
    
    
        def parse_item(self, response):
            # 解析出当前页码对应页面中 电影详情页 的url
            li_list = response.xpath('/html/body/div[2]/div[2]/div[2]/ul/li')
            for li in li_list:
                # 解析详情页的url
                detail_url = 'http://www.922dyy.com' + li.xpath('./div/a/@href').extract_first()
                #
                ex = self.conn.sadd('mp4_detail_url',detail_url) # 有返回值
                # ex == 1 该url没有被请求过     ex==0在集合中,该url已经被请求过了
                if ex==1:
                    print('有新数据可爬.....')
                    yield scrapy.Request(url=detail_url,callback=self.parse_detail)
                else:
                    print('暂无新数据可以爬取')
    
        def parse_detail(self,response):
            name = response.xpath('//*[@id="film_name"]/text()').extract_first()
            m_type = response.xpath('//*[@id="left_info"]/p[1]/text()').extract_first()
            print(name,'--',m_type)
            item = ShipinItem() #实例化
            item['name'] = name
            item['m_type'] = m_type
    
            yield item
    # items.py
    # -*- coding: utf-8 -*-
    
    import scrapy
    
    class ShipinItem(scrapy.Item):
    
        name = scrapy.Field()
        m_type = scrapy.Field()
    # pipelines.py 管道
    # -*- coding: utf-8 -*-
    
    class ShipinPipeline(object):
        def process_item(self, item, spider):
            conn = spider.conn
            dic = {
                'name':item['name'],
                'm_type':item['m_type']
            }
            conn.lpush('movie_data',str(dic)) #一般这里不str的话会报错,数据类型dict的错误
            return item
    # settings.py  里面
    
    ITEM_PIPELINES = {
       'shipin.pipelines.ShipinPipeline': 300,
    }
    
    BOT_NAME = 'shipin'
    
    SPIDER_MODULES = ['shipin.spiders']
    NEWSPIDER_MODULE = 'shipin.spiders'
    
    USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36'
    
    ROBOTSTXT_OBEY = False
    
    LOG_LEVEL = 'ERROR'

    流程: scrapy startproject Name 

        cd Name 

        scrapy genspider -t crawl 爬虫文件名 www.example.com  

    注意点: 增量式爬虫,会判断url在不在集合里面,sadd (集合的方法) 返回值1就是没在里面,就是新数据.   

        lpush lrange llen  --key  都是redis里面列表类型的方法

    下面是糗事百科段子页面的数据 (作者/段子)   增量式爬取

    # 爬虫.py
    # -*- coding: utf-8 -*-
    import scrapy,hashlib
    from qbPro.items import QbproItem
    from redis import Redis
    
    # 只爬取当前页面
    class QiubaiSpider(scrapy.Spider):
        name = 'qiubai'
    
        conn = Redis(host='127.0.0.1',port=6379)
        start_urls = ['https://www.qiushibaike.com/text/']
    
        def parse(self, response):
            div_list = response.xpath('//*[@id="content-left"]/div')
            for div in div_list:
                # 数据指纹:爬取到一条数据的唯一标识
                author = div.xpath('./div/a[2]/h2/text() | ./div/span[2]/h2/text()').extract_first().strip()
                content = div.xpath('./a/div/span[1]//text()').extract()
                content = ''.join(content).replace('
    ','')
                item = QbproItem()  # 实例化
                item['author'] = author
                item['content'] = content
    
                # 给爬取到的数据生成一个数据指纹
                data = author+content
                hash_key = hashlib.sha256(data.encode()).hexdigest()
                ex = self.conn.sadd('hash_key',hash_key)  # 输指纹存进 集合里面
                if ex == 1:
                    print('有数据更新')
                    yield item
                else:
                    print('无数据更新')
    # items.py
    # -*- coding: utf-8 -*-
    import scrapy
    class QbproItem(scrapy.Item):
    
        author = scrapy.Field()
        content = scrapy.Field()
    # pipelines.py  管道
    # -*- coding: utf-8 -*-
    class QbproPipeline(object):
        def process_item(self, item, spider):
            conn = spider.conn
            dic = {
                'author': item['author'],
                'content': item['content']
            }
            conn.lpush('qiubai', str(dic))
            return item
    # settings.py  设置
    
    ITEM_PIPELINES
    = { 'qbPro.pipelines.QbproPipeline': 300, } USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.86 Safari/537.36' ROBOTSTXT_OBEY = False LOG_LEVEL = 'ERROR'

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  • 原文地址:https://www.cnblogs.com/zhangchen-sx/p/10849234.html
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