Python培训之scrapy框架的日志等级和请求传参

　　一.Scrapy的培训日志等级

　　在使用scrapy crawl spiderFileName运行程序时，在终端里打印输出的日志就是scrapy的日志信息。

　　日志信息的等级种类：

　　ERROR ： 一般错误

　　WARNING : 警告

　　INFO : 一般的信息

　　DEBUG ： 调试信息

　　设置日志信息指定输出：

　　在settings.py配置文件中，加入

　　LOG_LEVEL = ‘指定日志信息种类’即可。和请

　　LOG_FILE = log.txt则表示将日志信息写入到指定文件中进行存储。求传

　　二.请求传参

　　在某些情况下，培训我们爬取的日志数据不在同一个页面中，例如，等级我们爬取一个电影网站，和请电影的求传名称，评分在一级页面，培训而要爬取的日志其他电影详情在其二级子页面中。网站模板这时我们就需要用到请求传参。等级

　　案例展示：爬取www.id97.com电影网，和请将一级页面中的求传电影名称，类型，评分一级二级页面中的上映时间，导演，片长进行爬取。

　　爬虫文件：

# -*- coding: utf-8 -*- import scrapy from moviePro.items import MovieproItem class MovieSpider(scrapy.Spider): name = movie allowed_domains = [www.id97.com] start_urls = [http://www.id97.com/] def parse(self, response): div_list = response.xpath(//div[@class="col-xs-1-5 movie-item"]) for div in div_list: item = MovieproItem() item[name] = div.xpath(.//h1/a/text()).extract_first() item[score] = div.xpath(.//h1/em/text()).extract_first() #xpath(string(.))表示提取当前节点下所有子节点中的数据值（.）表示当前节点 item[kind] = div.xpath(.//div[@class="otherinfo"]).xpath(string(.)).extract_first() item[detail_url] = div.xpath(./div/a/@href).extract_first() #请求二级详情页面，解析二级页面中的相应内容,通过meta参数进行Request的数据传递 yield scrapy.Request(url=item[detail_url],callback=self.parse_detail,meta={item:item}) def parse_detail(self,response): #通过response获取item item = response.meta[item] item[actor] = response.xpath(//div[@class="row"]//table/tr[1]/a/text()).extract_first() item[time] = response.xpath(//div[@class="row"]//table/tr[7]/td[2]/text()).extract_first() item[long] = response.xpath(//div[@class="row"]//table/tr[8]/td[2]/text()).extract_first() #提交item到管道 yield item

　　items文件：

# -*- coding: utf-8 -*- # Define here the models for your scraped items # # See documentation in: # https://doc.scrapy.org/en/latest/topics/items.html import scrapy class MovieproItem(scrapy.Item): # define the fields for your item here like: name = scrapy.Field() score = scrapy.Field() time = scrapy.Field() long = scrapy.Field() actor = scrapy.Field() kind = scrapy.Field() detail_url = scrapy.Field()

　　管道文件：

# -*- coding: utf-8 -*- # Define your item pipelines here # # Dont forget to add your pipeline to the ITEM_PIPELINES setting # See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html import json class MovieproPipeline(object): def __init__(self): self.fp = open(data.txt,w) def process_item(self, item, spider): dic = dict(item) print(dic) json.dump(dic,self.fp,ensure_ascii=False) return item def close_spider(self,spider): self.fp.close()

　　三.如何提高scrapy的爬取效率

　　增加并发：

　　默认scrapy开启的并发线程为32个，可以适当进行增加。在settings配置文件中修改CONCURRENT_REQUESTS = 100值为100,并发设置成了为100。

　　降低日志级别：

　　在运行scrapy时，会有大量日志信息的源码下载输出，为了减少CPU的使用率。可以设置log输出信息为INFO或者ERROR即可。在配置文件中编写：LOG_LEVEL = ‘INFO’

　　禁止cookie：

　　如果不是真的需要cookie，则在scrapy爬取数据时可以进制cookie从而减少CPU的使用率，提升爬取效率。在配置文件中编写：COOKIES_ENABLED = False

　　禁止重试：

　　对失败的HTTP进行重新请求(重试)会减慢爬取速度，因此可以禁止重试。在配置文件中编写：RETRY_ENABLED = False

　　减少下载超时：

　　如果对一个非常慢的链接进行爬取，减少下载超时可以能让卡住的链接快速被放弃，从而提升效率。在配置文件中进行编写：DOWNLOAD_TIMEOUT = 10 超时时间为10s

　　测试案例：爬取校花网校花图片 www.521609.com

# -*- coding: utf-8 -*- import scrapy from xiaohua.items import XiaohuaItem class XiahuaSpider(scrapy.Spider): name = xiaohua allowed_domains = [www.521609.com] start_urls = [http://www.521609.com/daxuemeinv/] pageNum = 1 url = http://www.521609.com/daxuemeinv/list8%d.html def parse(self, response): li_list = response.xpath(//div[@class="index_img list_center"]/ul/li) for li in li_list: school = li.xpath(./a/img/@alt).extract_first() img_url = li.xpath(./a/img/@src).extract_first() item = XiaohuaItem() item[school] = school item[img_url] = http://www.521609.com + img_url yield item if self.pageNum < 10: self.pageNum += 1 url = format(self.url % self.pageNum) #print(url) yield scrapy.Request(url=url,callback=self.parse) # -*- coding: utf-8 -*- # Define here the models for your scraped items # # See documentation in: # https://doc.scrapy.org/en/latest/topics/items.html import scrapy class XiaohuaItem(scrapy.Item): # define the fields for your item here like: # name = scrapy.Field() school=scrapy.Field() img_url=scrapy.Field() # -*- coding: utf-8 -*- # Define your item pipelines here # # Dont forget to add your pipeline to the ITEM_PIPELINES setting # See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html import json import os import urllib.request class XiaohuaPipeline(object): def __init__(self): self.fp = None def open_spider(self,spider): print(开始爬虫) self.fp = open(./xiaohua.txt,w) def download_img(self,item): url = item[img_url] fileName = item[school]+.jpg if not os.path.exists(./xiaohualib): os.mkdir(./xiaohualib) filepath = os.path.join(./xiaohualib,fileName) urllib.request.urlretrieve(url,filepath) print(fileName+"下载成功") def process_item(self, item, spider): obj = dict(item) json_str = json.dumps(obj,ensure_ascii=False) self.fp.write(json_str+\n) #下载图片 self.download_img(item) return item def close_spider(self,spider): print(结束爬虫) self.fp.close()

　　配置文件：

USER_AGENT = Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 Safari/537.36 # Obey robots.txt rules ROBOTSTXT_OBEY = False # Configure maximum concurrent requests performed by Scrapy (default: 16) CONCURRENT_REQUESTS = 100 COOKIES_ENABLED = False LOG_LEVEL = ERROR RETRY_ENABLED = False DOWNLOAD_TIMEOUT = 3 # Configure a delay for requests for the same website (default: 0) # See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs # The download delay setting will honor only one of: #CONCURRENT_REQUESTS_PER_DOMAIN = 16 #CONCURRENT_REQUESTS_PER_IP = 16 DOWNLOAD_DELAY = 3