scrapy框架的日志等级和请求传参
一.scrapy的日志等级
- 在使用scrapy crawl spiderFileName程序运行时,在终端里打印输出的就是scrapy的日志信息.
- 日志种类:
* 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。 LOG_FILE = 'log.txt'则表示将日志信息写入到指定文件中进行存储。
二.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,而爬取其他电影详情在其二级子页面中,这是我们就西药用到请求传参.
- 案例展示: 爬取www.id97.com电影网,将一级子页面中的电影名称,影片描述进行爬取.
爬虫文件:
# -*- coding: utf-8 -*- import scrapy from qiubai.items import QiubaiItem class QiushiSpider(scrapy.Spider): name = 'qiushi' # allowed_domains = ['www.xxx.com'] start_urls = ['https://www.4567tv.tv/frim/index1.html'] def detail_parse(self, response): item = response.meta['item'] describe = response.xpath('//p[@class="desc detail hidden-xs"]/span[2]/text()|//span[@class="detail-sketch"]/text()').extract_first() item['describe'] = describe yield item def parse(self, response): li_list = response.xpath('//ul[@class="stui-vodlist clearfix"]/li') for li in li_list: item = QiubaiItem() title = li.xpath('./div/a/@title').extract_first() detail_url = "https://www.4567tv.tv/" + li.xpath('./div/a/@href').extract_first() item["name"] = title yield scrapy.Request(url=detail_url, callback=self.detail_parse, meta={'item':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 QiubaiItem(scrapy.Item): # define the fields for your item here like: name = scrapy.Field() describe = 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 class QiubaiPipeline(object): def process_item(self, item, spider): print(item) return item
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_TEQUESTS = 100 值为100,并发设置成了100.
- 降低日志级别:
在运行scrapy是,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,在配置文件中写: LOG_LEVEL = 'INFO'
- 禁止cookie:
如果不是征得需要cookie,则在scrapy爬取数据是可以禁止cookie从而减少CPU的使用率.在配置文件中编写: COOKIES_ENABLED = False
- 禁止重试:
对是被的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主的链接快速被放弃,从而提升效率.在配置文件中编写:DOWNLOAD_TIMEOUT = 10 超时时间为10秒.
测试案例:爬取校花网校花图片:
爬虫文件:
# -*- 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)
item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 XiaohuaItem(scrapy.Item): # define the fields for your item here like: # name = scrapy.Field() school=scrapy.Field() img_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 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
