新浪网分类资讯爬虫
从GitHub得到完整项目(https://github.com/daleyzou/sinainfo.git)
1、简介
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:
2、代码
items.py
1 import scrapy 2 3 4 class SinainfoItem(scrapy.Item): 5 # 大类的标题和url 6 parentTitle = scrapy.Field() 7 parentUrls = scrapy.Field() 8 9 # 小类的标题和子url 10 subTitle = scrapy.Field() 11 subUrls = scrapy.Field() 12 13 # 小类目录存储路径 14 subFilename = scrapy.Field() 15 16 # 小类下的子链接 17 sonUrls = scrapy.Field() 18 19 # 大文章标题和内容 20 head = scrapy.Field() 21 content = scrapy.Field()
spiders/sina.py(爬虫)
1 # -*- coding: utf-8 -*- 2 import scrapy 3 import sys 4 import os 5 6 # noinspection PyUnresolvedReferences 7 from sinainfo.items import SinainfoItem 8 9 reload(sys) 10 sys.setdefaultencoding('utf-8') 11 12 13 class SinaSpider(scrapy.Spider): 14 name = 'sina' 15 allowed_domains = ['sina.com.cn'] 16 start_urls = ['http://news.sina.com.cn/guide/'] 17 18 def parse(self, response): 19 items = [] 20 # 所有大类的标题和url 21 parentTitle = response.xpath("//div[@id='tab01']/div/h3/a/text()").extract() 22 parentUrls = response.xpath('//div[@id="tab01"]/div/h3/a/@href').extract() 23 24 # 所有小类的ur 和 标题 25 subUrls = response.xpath('//div[@id="tab01"]/div/ul/li/a/@href').extract() 26 subTitle = response.xpath('//div[@id="tab01"]/div/ul/li/a/text()').extract() 27 28 # 爬取所有大类 29 for i in range(0, len(parentTitle)): 30 # 指定大类目录的路径和目录名 31 parentFilename = "./Data/" + parentTitle[i] 32 # 如果目录不存在,则创建目录 33 if (not os.path.exists(parentFilename)): 34 os.makedirs(parentFilename) 35 36 # 爬取所有小类 37 for j in range(0, len(subUrls)): 38 item = SinainfoItem() 39 # 保存大类的title和urls 40 item['parentTitle'] = parentTitle[i] 41 item['parentUrls'] = parentUrls[i] 42 # 检查小类的url是否以同类别大类url开头,如果是返回Ture 43 if_belong = subUrls[j].startswith(item['parentUrls']) 44 # 如果属于本大类,将存储目录放在本大类下 45 if (if_belong): 46 subFilename = parentFilename + '/' + subTitle[j] 47 # 如果目录不存在,则创建目录 48 if (not os.path.exists(subFilename)): 49 os.makedirs(subFilename) 50 # 存储 小类url、title、和filename字段数据 51 item['subUrls'] = subUrls[j] 52 item['subTitle'] = subTitle[j] 53 item['subFilename'] = subFilename 54 items.append(item) 55 56 # 发送每个小类url的Request请求,得到Response连同包含meta数据 57 # 一同交给回调函数second_parse()处理 58 for item in items: 59 yield scrapy.Request(url = item['subUrls'],\ 60 meta={'meta_1':item}, callback=self.second_parse) 61 62 # 对于返回的小类url,在进行递归请求 63 def second_parse(self, response): 64 # 提取每次Response的meta数据 65 meta_1 = response.meta['meta_1'] 66 # 取出小类里所有字链接 67 sonUrls = response.xpath('//a/@href').extract() 68 69 items = [] 70 for i in range(0, len(sonUrls)): 71 # 检查每个链接是否以大类url开头、以.shtml结尾,如果是返回True 72 if_belong = sonUrls[i].endswith('.shtml') and sonUrls[i].startswith(\ 73 meta_1['parentUrls']) 74 # 如果属于本大类,获取字段值放在同一个item下便于传输 75 if (if_belong): 76 item = SinainfoItem() 77 item['parentTitle'] = meta_1['parentTitle'] 78 item['parentUrls'] = meta_1['parentUrls'] 79 item['subTitle'] = meta_1['subTitle'] 80 item['subUrls'] = meta_1['subUrls'] 81 item['subFilename'] = meta_1['subFilename'] 82 item['sonUrls'] = sonUrls[i] 83 items.append(item) 84 85 for item in items: 86 yield scrapy.Request(url = item['sonUrls'],\ 87 meta = {'meta_2':item}, callback=self.detail_parse) 88 89 # 数据解析方法,获取文章标题和内容 90 def detail_parse(self, response): 91 item = response.meta['meta_2'] 92 content = "" 93 head = response.xpath('//h1[@id="main_title"]/text()') 94 content_list = response.xpath('//div[@id="artibody"]/p/text()').extract() 95 # 将p标签里的文本内容合并到一起 96 for content_one in content_list: 97 content += content_one 98 item['head'] = head 99 item['content'] = content
pipelines.py
1 class SinainfoPipeline(object): 2 def process_item(self, item, spider): 3 sonUrls = item['sonUrls'] 4 5 # 文件名为子链接url中间部分,并将/替换为_,保存为.txt 6 filename = sonUrls[7:-6].replace('/', '_') 7 filename += ".txt" 8 9 fp = open(item['subFilename']+'/'+filename, 'w') 10 fp.write(item['content']) 11 fp.close() 12 return item
settings.py
1 2 BOT_NAME = 'sinainfo' 3 4 SPIDER_MODULES = ['sinainfo.spiders'] 5 NEWSPIDER_MODULE = 'sinainfo.spiders' 6 7 LOG_LEVEL = 'DEBUG' 8 # Crawl responsibly by identifying yourself (and your website) on the user-agent 9 USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/48.0.2564.116 Safari/537.36' 10 DOWNLOAD_DELAY = 3 11 COOKIES_ENABLED = False 12 13 ITEM_PIPELINES = { 14 'sinainfo.pipelines.SinainfoPipeline': 300, 15 }
3、运行
方法一:
(1)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())
(2)执行程序
py2 main.py
方法二:
在命令行下:
(1)切换到项目/sinainfo/sinainfo/spiders
(2)执行 scrapy crawl sina