scrapy框架的日志等级和请求传参

Scrapy的日志等级

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

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。

　　- 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：

import scrapy
from moviePro.items import MovieproItemclass 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itemitem = 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：

# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.htmlimport scrapyclass 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：

# 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.htmlimport 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 itemdef close_spider(self,spider):self.fp.close()

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

import scrapy
from xiaohua.items import XiaohuaItemclass XiahuaSpider(scrapy.Spider):name = 'xiaohua'allowed_domains = ['www.521609.com']start_urls = ['http://www.521609.com/daxuemeinv/']pageNum = 1url = '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'] = schoolitem['img_url'] = 'http://www.521609.com' + img_urlyield itemif self.pageNum < 10:self.pageNum += 1url = format(self.url % self.pageNum)#print(url)yield scrapy.Request(url=url,callback=self.parse)

# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.htmlimport scrapyclass XiaohuaItem(scrapy.Item):# define the fields for your item here like:# name = scrapy.Field()school=scrapy.Field()img_url=scrapy.Field()

# 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.htmlimport json
import os
import urllib.request
class XiaohuaPipeline(object):def __init__(self):self.fp = Nonedef 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 itemdef 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