(实战项目三)新浪网分类资讯爬虫
爬取新浪网导航页所有下所有大类、小类、小类里的子链接,以及子链接页面的新闻内容。
效果演示图:
items.py
import scrapy
import sys
reload(sys)
sys.setdefaultencoding("utf-8")class SinaItem(scrapy.Item):# 大类的标题 和 urlparentTitle = scrapy.Field()parentUrls = scrapy.Field()# 小类的标题 和 子urlsubTitle = scrapy.Field()subUrls = scrapy.Field()# 小类目录存储路径subFilename = scrapy.Field()# 小类下的子链接sonUrls = scrapy.Field()# 文章标题和内容head = scrapy.Field()content = scrapy.Field()
spiders/sina.py
# -*- coding: utf-8 -*-
# -*- coding: utf-8 -*-from Sina.items import SinaItem
import scrapy
import osimport sys
reload(sys)
sys.setdefaultencoding("utf-8")class SinaSpider(scrapy.Spider):name= "sina"allowed_domains= ["sina.com.cn"]start_urls= ["http://news.sina.com.cn/guide/"]def parse(self, response):items= []# 所有大类的url 和 标题parentUrls = response.xpath('//div[@id=\"tab01\"]/div/h3/a/@href').extract()parentTitle = response.xpath("//div[@id=\"tab01\"]/div/h3/a/text()").extract()# 所有小类的ur 和 标题subUrls = response.xpath('//div[@id=\"tab01\"]/div/ul/li/a/@href').extract()subTitle = response.xpath('//div[@id=\"tab01\"]/div/ul/li/a/text()').extract()#爬取所有大类for i in range(0, len(parentTitle)):# 指定大类目录的路径和目录名parentFilename = "./Data/" + parentTitle[i]#如果目录不存在,则创建目录if(not os.path.exists(parentFilename)):os.makedirs(parentFilename)# 爬取所有小类for j in range(0, len(subUrls)):item = SinaItem()# 保存大类的title和urlsitem['parentTitle'] = parentTitle[i]item['parentUrls'] = parentUrls[i]# 检查小类的url是否以同类别大类url开头,如果是返回True (sports.sina.com.cn 和 sports.sina.com.cn/nba)if_belong = subUrls[j].startswith(item['parentUrls'])# 如果属于本大类,将存储目录放在本大类目录下if(if_belong):subFilename =parentFilename + '/'+ subTitle[j]# 如果目录不存在,则创建目录if(not os.path.exists(subFilename)):os.makedirs(subFilename)# 存储 小类url、title和filename字段数据item['subUrls'] = subUrls[j]item['subTitle'] =subTitle[j]item['subFilename'] = subFilenameitems.append(item)#发送每个小类url的Request请求,得到Response连同包含meta数据 一同交给回调函数 second_parse 方法处理for item in items:yield scrapy.Request( url = item['subUrls'], meta={'meta_1': item}, callback=self.second_parse)#对于返回的小类的url,再进行递归请求def second_parse(self, response):# 提取每次Response的meta数据meta_1= response.meta['meta_1']# 取出小类里所有子链接sonUrls = response.xpath('//a/@href').extract()items= []for i in range(0, len(sonUrls)):# 检查每个链接是否以大类url开头、以.shtml结尾,如果是返回Trueif_belong = sonUrls[i].endswith('.shtml') and sonUrls[i].startswith(meta_1['parentUrls'])# 如果属于本大类,获取字段值放在同一个item下便于传输if(if_belong):item = SinaItem()item['parentTitle'] =meta_1['parentTitle']item['parentUrls'] =meta_1['parentUrls']item['subUrls'] = meta_1['subUrls']item['subTitle'] = meta_1['subTitle']item['subFilename'] = meta_1['subFilename']item['sonUrls'] = sonUrls[i]items.append(item)#发送每个小类下子链接url的Request请求,得到Response后连同包含meta数据 一同交给回调函数 detail_parse 方法处理for item in items:yield scrapy.Request(url=item['sonUrls'], meta={'meta_2':item}, callback = self.detail_parse)# 数据解析方法,获取文章标题和内容def detail_parse(self, response):item = response.meta['meta_2']content = ""head = response.xpath('//h1[@id=\"main_title\"]/text()')content_list = response.xpath('//div[@id=\"artibody\"]/p/text()').extract()# 将p标签里的文本内容合并到一起for content_one in content_list:content += content_oneitem['head']= headitem['content']= contentyield item
pipelines.py
from scrapy import signals
import sys
reload(sys)
sys.setdefaultencoding("utf-8")class SinaPipeline(object):def process_item(self, item, spider):sonUrls = item['sonUrls']# 文件名为子链接url中间部分,并将 / 替换为 _,保存为 .txt格式filename = sonUrls[7:-6].replace('/','_')filename += ".txt"fp = open(item['subFilename']+'/'+filename, 'w')fp.write(item['content'])fp.close()return item
settings.py
BOT_NAME = 'Sina'SPIDER_MODULES = ['Sina.spiders']
NEWSPIDER_MODULE = 'Sina.spiders'ITEM_PIPELINES = {'Sina.pipelines.SinaPipeline': 300,
}LOG_LEVEL = 'DEBUG'
在项目根目录下新建main.py文件,用于调试
from scrapy import cmdline
cmdline.execute('scrapy crawl sina'.split())
执行程序
py2 main.py