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responses.urljoin(不完整的链接)
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if isinstance(item,字典名)
保存
return item
判断网站ip类型,从而挂ip类型if request.url.startswitch(''http://"):
request.meta["proxy"]='http://+ip'
elif ...........('https://'):
......='https://+ip'
pipeline 管道class 管道名(object):
self.文件=open("文件名.后缀",'写入方式',encoding="utf_8")
self.文件=open("文件名.后缀",'写入方式',encoding="utf_8")
2. def process_item(self,spider):
# 管道中判断是否为某一个字典
if isinstance(item,字典名)
保存
return item
if isinstance(item, 字典名):
data = dict(item)
self.file.write(json.dumps(data, ensure_ascii=False) + ',\n')
#ensure_ascii=False:这是因为json.dumps 序列化时对中文默认使用的ascii编码.想输出真正的中文需要指定ensure_ascii=False
3. def close_spider(self,spider):
self.文件.close()#关闭文件
3. def __del__(self):
self.文件.close()#关闭文件
setting文件 代理及user_agentDOWNLOADER_MIDDLEWARES = {
# 'demo_58.middlewares.Demo58DownloaderMiddleware': 543,
#随机ua
'demo_58.middlewares.UserAgentDownloadMiddleware': 543,
#随机ip
'demo_58.middlewares.RandomProxy': 542,
}
DEFAULT_REQUEST_HEADERS = {
'accept-encoding': 'gzip, deflate, br',
'accept-language': 'zh-CN,zh;q=0.9',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Language': 'en',
'referer': 'https://cs.58.com/chuzu/?PGTID=0d100000-0019-e694-7c7e-9295d99e15c1&ClickID=2'
}
class RandomProxy: ip_list = [ '124.116.116.13:4228', '122.194.194.139:4212', '36.42.248.45:4215', '1.83.250.183:4228', '49.85.43.175:4223', '121.205.229.70:4231', ] # 方法名是scrapy规定的方法 (协商机制) def process_request(self, request, spider): proxy = random.choice(self.ip_list) # 修改请求的元数据字典 # 如果是将IP以列表随机形式构造 需要加上https://,否则报错 request.meta['proxy'] = 'https://' + proxy # 如果是将IP以字典形式构造 print('IP:', request.meta)随机user_agent
class UserAgentDownloadMiddleware: user_agent = [ 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.163 Safari/535.1', 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50', 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:77.0) Gecko/20190101 Firefox/77.0', 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36', 'Opera/9.80 (X11; Linux i686; Ubuntu/14.10) Presto/2.12.388 Version/12.16.2' ] # 方法名是scrapy规定的方法 (协商机制) # 每个交给下载器的request对象都会经过该方法,并期望返回response def process_request(self, request, spider): # 获取随机请求头 u_a = random.choice(self.user_agent) # 设置请求头 request.headers['User-Agent'] = u_aitem字典
# 租房 class Demo58Item_zufang(scrapy.Item): # define the fields for your item here like: title = scrapy.Field() # 租房标题 price = scrapy.Field() # 租房价格 # 二手房 class Demo58Item_ershou(scrapy.Item): # define the fields for your item here like: title = scrapy.Field() # 二手标题 price = scrapy.Field() # 二手价格spider文件
import scrapy
导入字典
from demo_58.items import Demo58Item_zufang,Demo58Item_ershou
class SpiderSpider(scrapy.Spider):
name = 'spider'
#限制域名
allowed_domains = ['58.com']
#限制网址
start_urls = ['http://58.com/']
def parse(self, response):
# 解析链接
links = response.xpath('//div[@]//span[@]/a/@href').extract()
for link in links:
# response.urljoin() 自动拼接链接
href = response.urljoin(link)
#指定爬取的子网页
if '58.com/chuzu/' in href:
yield scrapy.Request(url=href,callback=self.get_zufang_data)
if '58.com/ershoufang/' in href:
yield scrapy.Request(url=href, callback=self.get_ershoufang_data)
'''解析信息'''
def get_zufang_data(self,response):
title = response.xpath('//div[@]/h2/a/text()').extract() # 标题
preice = response.xpath('//div[@]//div[@]/b/text()').extract() # 价格
for titles,preices in zip(title,preice):
# 实例化租房的item类
zufang_item = Demo58Item_zufang()
zufang_item['title'] =titles
zufang_item['price'] =preices
# 返回给引擎
yield zufang_item
# 构造翻页
for i in range(2,12):
print('当前正在下载租房的第{}页'.format(i))
z_next_url = 'https://cs.58.com/chuzu/pn{}/'.format(i)
# 将翻页Url打包成请求对象给引擎
#callback=交给谁去执行
yield scrapy.Request(url=z_next_url,callback=self.get_zufang_data)
'''解析信息'''
def get_ershoufang_data(self,response):
title = response.xpath('//div[@]/div[@]/h3/text()').extract() # 标题
preice = response.xpath('//p[@]/span[@]/text()').extract() # 价格
for titles, preices in zip(title, preice):
# 实例化二手房的Item类
ershou_item = Demo58Item_ershou()
ershou_item['title'] = titles.strip()
ershou_item['price'] = preices
# 返回给引擎
yield ershou_item
# 开始二手房翻页
for i in range(2,12):
print('当前正在下载二手房的第{}页'.format(i))
next_url = 'https://cs.58.com/ershoufang/p{}/'.format(i)
# 将翻页Url打包成请求对象给引擎
yield scrapy.Request(url=next_url, callback=self.get_ershoufang_data)
if __name__ == '__main__':
#启动文件
from scrapy import cmdline
cmdline.execute(['scrapy', 'crawl', 'spider'])
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