12 Scrapy框架的日志等级和请求传参

朴灿烈づ我的快乐病毒、 2021-11-02 13:18 234阅读 0赞

**一.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。

**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:

1 import scrapy
     2 from moviePro.items import MovieproItem
     3 
     4 class MovieSpider(scrapy.Spider):
     5     name = 'movie'
     6     allowed_domains = ['www.id97.com']
     7     start_urls = ['http://www.id97.com/']
     8 
     9     def parse(self, response):
    10         div_list = response.xpath('//div[@class="col-xs-1-5 movie-item"]')
    11 
    12         for div in div_list:
    13             item = MovieproItem()
    14             item['name'] = div.xpath('.//h1/a/text()').extract_first()
    15             item['score'] = div.xpath('.//h1/em/text()').extract_first()
    16             #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
    17             item['kind'] = div.xpath('.//div[@class="otherinfo"]').xpath('string(.)').extract_first()
    18             item['detail_url'] = div.xpath('./div/a/@href').extract_first()
    19             #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
    20             yield scrapy.Request(url=item['detail_url'],callback=self.parse_detail,meta={
        'item':item})
    21 
    22     def parse_detail(self,response):
    23         #通过response获取item
    24         item = response.meta['item']
    25         item['actor'] = response.xpath('//div[@class="row"]//table/tr[1]/a/text()').extract_first()
    26         item['time'] = response.xpath('//div[@class="row"]//table/tr[7]/td[2]/text()').extract_first()
    27         item['long'] = response.xpath('//div[@class="row"]//table/tr[8]/td[2]/text()').extract_first()
    28         #提交item到管道
    29         yield item

items文件:

1 # -*- coding: utf-8 -*-
     2 
     3 # Define here the models for your scraped items
     4 #
     5 # See documentation in:
     6 # https://doc.scrapy.org/en/latest/topics/items.html
     7 
     8 import scrapy
     9 
    10 
    11 class MovieproItem(scrapy.Item):
    12     # define the fields for your item here like:
    13     name = scrapy.Field()
    14     score = scrapy.Field()
    15     time = scrapy.Field()
    16     long = scrapy.Field()
    17     actor = scrapy.Field()
    18     kind = scrapy.Field()
    19     detail_url = scrapy.Field()

管道文件:

1 # -*- coding: utf-8 -*-
     2 
     3 # Define your item pipelines here
     4 #
     5 # Don't forget to add your pipeline to the ITEM_PIPELINES setting
     6 # See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
     7 
     8 import json
     9 class MovieproPipeline(object):
    10     def __init__(self):
    11         self.fp = open('data.txt','w')
    12     def process_item(self, item, spider):
    13         dic = dict(item)
    14         print(dic)
    15         json.dump(dic,self.fp,ensure_ascii=False)
    16         return item
    17     def close_spider(self,spider):
    18         self.fp.close()

**三. 如何提高scrapy的爬虫效率**

1 增加并发：
     2     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。
     3 
     4 降低日志级别：
     5     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’
     6 
     7 禁止cookie：
     8     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
     9 
    10 禁止重试：
    11     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
    12 
    13 减少下载超时：
    14     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

爬虫文件:

1 import scrapy
     2 from xiaohua.items import XiaohuaItem
     3 
     4 class XiahuaSpider(scrapy.Spider):
     5 
     6     name = 'xiaohua'
     7     allowed_domains = ['www.521609.com']
     8     start_urls = ['http://www.521609.com/daxuemeinv/']
     9 
    10     pageNum = 1
    11     url = 'http://www.521609.com/daxuemeinv/list8%d.html'
    12 
    13     def parse(self, response):
    14         li_list = response.xpath('//div[@class="index_img list_center"]/ul/li')
    15         for li in li_list:
    16             school = li.xpath('./a/img/@alt').extract_first()
    17             img_url = li.xpath('./a/img/@src').extract_first()
    18 
    19             item = XiaohuaItem()
    20             item['school'] = school
    21             item['img_url'] = 'http://www.521609.com' + img_url
    22 
    23             yield item
    24 
    25         if self.pageNum < 10:
    26             self.pageNum += 1
    27             url = format(self.url % self.pageNum)
    28             #print(url)
    29             yield scrapy.Request(url=url,callback=self.parse)

items文件:

1 # -*- coding: utf-8 -*-
     2 
     3 # Define here the models for your scraped items
     4 #
     5 # See documentation in:
     6 # https://doc.scrapy.org/en/latest/topics/items.html
     7 
     8 import scrapy
     9 
    10 
    11 class XiaohuaItem(scrapy.Item):
    12     # define the fields for your item here like:
    13     # name = scrapy.Field()
    14     school=scrapy.Field()
    15     img_url=scrapy.Field()

管道文件:

1 # -*- coding: utf-8 -*-
     2 
     3 # Define your item pipelines here
     4 #
     5 # Don't forget to add your pipeline to the ITEM_PIPELINES setting
     6 # See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
     7 
     8 import json
     9 import os
    10 import urllib.request
    11 class XiaohuaPipeline(object):
    12     def __init__(self):
    13         self.fp = None
    14 
    15     def open_spider(self,spider):
    16         print('开始爬虫')
    17         self.fp = open('./xiaohua.txt','w')
    18 
    19     def download_img(self,item):
    20         url = item['img_url']
    21         fileName = item['school']+'.jpg'
    22         if not os.path.exists('./xiaohualib'):
    23             os.mkdir('./xiaohualib')
    24         filepath = os.path.join('./xiaohualib',fileName)
    25         urllib.request.urlretrieve(url,filepath)
    26         print(fileName+"下载成功")
    27 
    28     def process_item(self, item, spider):
    29         obj = dict(item)
    30         json_str = json.dumps(obj,ensure_ascii=False)
    31         self.fp.write(json_str+'\n')
    32 
    33         #下载图片
    34         self.download_img(item)
    35         return item
    36 
    37     def close_spider(self,spider):
    38         print('结束爬虫')
    39         self.fp.close()

settings文件

1 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'
     2 
     3 # Obey robots.txt rules
     4 ROBOTSTXT_OBEY = False
     5 
     6 # Configure maximum concurrent requests performed by Scrapy (default: 16)
     7 CONCURRENT_REQUESTS = 100
     8 COOKIES_ENABLED = False
     9 LOG_LEVEL = 'ERROR'
    10 RETRY_ENABLED = False
    11 DOWNLOAD_TIMEOUT = 3
    12 # Configure a delay for requests for the same website (default: 0)
    13 # See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay
    14 # See also autothrottle settings and docs
    15 # The download delay setting will honor only one of:
    16 #CONCURRENT_REQUESTS_PER_DOMAIN = 16
    17 #CONCURRENT_REQUESTS_PER_IP = 16
    18 DOWNLOAD_DELAY = 3

转载于:https://www.cnblogs.com/a2534786642/p/10998494.html