python爬虫项目(scrapy-redis分布式爬取房天下租房信息)
python爬虫scrapy项目（二）
爬取目标：房天下全国租房信息网站（起始url：http://zu.fang.com/cities.aspx）
爬取内容：城市；名字；出租方式；价格；户型；面积；地址；交通
反反爬措施：设置随机user-agent、设置请求延时操作、
1、开始创建项目
1 scrapy startproject fang
2、进入fang文件夹，执行启动spider爬虫文件代码，编写爬虫文件。
1 scrapy genspider zufang "zu.fang.com"
命令执行完，用Python最好的IDE---pycharm打开该文件目录
3、编写该目录下的items.py文件，设置你需要爬取的字段。
1 import scrapy 2 3 4 class HomeproItem(scrapy.Item): 5 # define the fields for your item here like: 6 # name = scrapy.Field() 7 8 city = scrapy.Field() #城市 9 title = scrapy.Field() # 名字 10 rentway = scrapy.Field() # 出租方式 11 price = scrapy.Field() #价格 12 housetype = scrapy.Field() # 户型 13 area = scrapy.Field() # 面积 14 address = scrapy.Field() # 地址 15 traffic = scrapy.Field() # 交通
4、进入spiders文件夹，打开hr.py文件,开始编写爬虫文件
1 # -*- coding: utf-8 -*- 2 import scrapy 3 from homepro.items import HomeproItem 4 from scrapy_redis.spiders import RedisCrawlSpider 5 # scrapy.Spider 6 class HomeSpider(RedisCrawlSpider): 7 name = 'home' 8 allowed_domains = ['zu.fang.com'] 9 # start_urls = ['http://zu.fang.com/cities.aspx'] 10 11 redis_key = 'homespider:start_urls' 12 def parse(self, response): 13 hrefs = response.xpath('//div[@class="onCont"]/ul/li/a/@href').extract() 14 for href in hrefs: 15 href = 'http:'+ href 16 yield scrapy.Request(url=href,callback=self.parse_city,dont_filter=True) 17 18 19 def parse_city(self, response): 20 page_num = response.xpath('//div[@id="rentid_D10_01"]/span[@class="txt"]/text()').extract()[0].strip('共页') 21 # print('*' * 100) 22 # print(page_num) 23 # print(response.url) 24 25 for page in range(1, int(page_num)): 26 if page == 1: 27 url = response.url 28 else: 29 url = response.url + 'house/i%d' % (page + 30) 30 print('*' * 100) 31 print(url) 32 yield scrapy.Request(url=url, callback=self.parse_houseinfo, dont_filter=True) 33 34 def parse_houseinfo(self, response): 35 divs = response.xpath('//dd[@class="info rel"]') 36 for info in divs: 37 city = info.xpath('//div[@class="guide rel"]/a[2]/text()').extract()[0].rstrip("租房") 38 title = info.xpath('.//p[@class="title"]/a/text()').extract()[0] 39 rentway = info.xpath('.//p[@class="font15 mt12 bold"]/text()')[0].extract().replace(" ", '').lstrip('\r\n') 40 housetype = info.xpath('.//p[@class="font15 mt12 bold"]/text()')[1].extract().replace(" ", '') 41 area = info.xpath('.//p[@class="font15 mt12 bold"]/text()')[2].extract().replace(" ", '') 42 addresses = info.xpath('.//p[@class ="gray6 mt12"]//span/text()').extract() 43 address = '-'.join(i for i in addresses) 44 try: 45 des = info.xpath('.//p[@class ="mt12"]//span/text()').extract() 46 traffic = '-'.join(i for i in des) 47 except Exception as e: 48 traffic = "暂无详细信息" 49 50 p_name = info.xpath('.//div[@class ="moreInfo"]/p/text()').extract()[0] 51 p_price = info.xpath('.//div[@class ="moreInfo"]/p/span/text()').extract()[0] 52 price = p_price + p_name 53 54 item = HomeproItem() 55 item['city'] = city 56 item['title'] = title 57 item['rentway'] = rentway 58 item['price'] = price 59 item['housetype'] = housetype 60 item['area'] = area 61 item['address'] = address 62 item['traffic'] = traffic 63 yield item
5、设置setting.py文件，配置scrapy运行的相关内容
1 # 指定使用scrapy-redis的调度器 2 SCHEDULER = "scrapy_redis.scheduler.Scheduler" 3 4 # 指定使用scrapy-redis的去重 5 DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter' 6 7 # 指定排序爬取地址时使用的队列， 8 # 默认的 按优先级排序(Scrapy默认)，由sorted set实现的一种非FIFO、LIFO方式。 9 SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.SpiderPriorityQueue' 10 11 REDIS_HOST = '10.8.153.73' 12 REDIS_PORT = 6379 13 # 是否在关闭时候保留原来的调度器和去重记录，True=保留，False=清空 14 SCHEDULER_PERSIST = True
6、然后把代码发给其他附属机器,分别启动.子程序redis链接主服务器redis。
1 redis-cli -h 主服务器ip
7、主服务器先启动redis-server，再启动redis-cli
1 lpush homespider:start_urls 起始的url
