Scrapy日志等级以及请求传参
日志等级
- 日志信息: 使用命令:scrapy crawl 爬虫文件 运行程序时,在终端输出的就是日志信息;
- 日志信息的种类:
- 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配置文件中添加:
- LOG_LEVEL = ‘指定日志信息种类’即可。
- LOG_FILE = 'log.txt'则表示将日志信息写入到指定文件中进行存储。
请求传参
- 在某些情况下,我们爬取的数据不在同一个页面中,例如,我们爬取一个电影网站,电影的名称,评分在一级页面,而要爬取的其他电影详情在其二级子页面中。这时我们就需要用到请求传参。
- 通过 在scrapy.Request()中添加 meta参数 进行传参;
scrapy.Request()
- 案例展示:爬取www.id97.com电影网,将一级页面中的电影名称,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 # # Don't 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()
提高scrapy的爬取效率
- 增加并发量:
- 默认最大的并发量为32,可以通过设置settings文件修改
CONCURRENT_REQUESTS = 100
- 将并发改为100
- 降低日志等级:
- 在运行scrapy时,会有大量日志信息的输出,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。修改settings.py
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。修改settings.py
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。修改settings.py
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。修改settings.py
DOWNLOAD_TIMEOUT = 10
- 测试案例:
# -*- coding: utf-8 -*- import scrapy from ..items import PicproItem # 提升spider的爬取效率测试 # 爬取4k高清壁纸网站的图片 class PicSpider(scrapy.Spider): name = 'pic' # allowed_domains = ['www.pic.com'] start_urls = ['http://pic.netbian.com/'] def parse(self, response): li_list = response.xpath('//div[@class="slist"]/ul/li') print(li_list) for li in li_list: img_url ="http://pic.netbian.com/"+li.xpath('./a/span/img/@src').extract_first() # print(66,img_url) title = li.xpath('./a/span/img/@alt').extract_first() print("title:", title) item = PicproItem() item["name"] = title yield scrapy.Request(url=img_url, callback =self.getImgData,meta={"item":item}) def getImgData(self, response): item = response.meta['item'] # 取二进制数据在body中 item['img_data'] = response.body yield item
import os class PicproPipeline(object): def open_spider(self,spider): if not os.path.exists('picLib'): os.mkdir('./picLib') def process_item(self, item, spider): imgPath = './picLib/'+item['name']+".jpg" with open(imgPath,'wb') as fp: fp.write(item['img_data']) print(imgPath+'下载成功!') return item
配置文件:
USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36' # Obey robots.txt rules ROBOTSTXT_OBEY = False ITEM_PIPELINES = { 'picPro.pipelines.PicproPipeline': 300, } # 打印具体错误信息 LOG_LEVEL ="ERROR" #提升爬取效率 CONCURRENT_REQUESTS = 10 COOKIES_ENABLED = False RETRY_ENABLED = False DOWNLOAD_TIMEOUT = 5