13.scrapy框架的日誌等級和請求傳參

今日概要

• 日誌等級
• 請求傳參
• 如何提升scrapy的爬取效率

今日詳情

一.Scrapy的日誌等級

　　- 在使用scrapy crawl spiderFileName運行程序時，在終端裏打印輸出的就是scrapy的日誌信息。

　　- 日誌信息的種類：

　　　　　　　　ERROR ： 通常錯誤

　　　　　　　　WARNING : 警告

　　　　　　　　INFO : 通常的信息

　　　　　　　　DEBUG ： 調試信息

　　　　　　　

　　- 設置日誌信息指定輸出：

　　　　在settings.py配置文件中，加入

                    LOG_LEVEL = ‘指定日誌信息種類’便可。

                    LOG_FILE = 'log.txt'則表示將日誌信息寫入到指定文件中進行存儲。

二.請求傳參

　　- 在某些狀況下，咱們爬取的數據不在同一個頁面中，例如，咱們爬取一個電影網站，電影的名稱，評分在一級頁面，而要爬取的其餘電影詳情在其二級子頁面中。這時咱們就須要用到請求傳參。

　　- 案例展現：爬取www.id97.com電影網，將一級頁面中的電影名稱，類型，評分一級二級頁面中的上映時間，導演，片長進行爬取。

　　爬蟲文件：

# -*- 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(.))表示提取當前節點下全部子節點中的數據值（.）表示當前節點 item['kind'] = div.xpath('.//div[@class="otherinfo"]').xpath('string(.)').extract_first() item['detail_url'] = div.xpath('./div/a/@href').extract_first() #請求二級詳情頁面，解析二級頁面中的相應內容,經過meta參數進行Request的數據傳遞 yield scrapy.Request(url=item['detail_url'],callback=self.parse_detail,meta={'item':item}) def parse_detail(self,response): #經過response獲取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()

三.如何提升scrapy的爬取效率

增長併發：
    默認scrapy開啓的併發線程爲32個，能夠適當進行增長。在settings配置文件中修改CONCURRENT_REQUESTS = 100值爲100,併發設置成了爲100。

下降日誌級別：
    在運行scrapy時，會有大量日誌信息的輸出，爲了減小CPU的使用率。能夠設置log輸出信息爲INFO或者ERROR便可。在配置文件中編寫：LOG_LEVEL = ‘INFO’

禁止cookie：
    若是不是真的須要cookie，則在scrapy爬取數據時能夠進制cookie從而減小CPU的使用率，提高爬取效率。在配置文件中編寫：COOKIES_ENABLED = False

禁止重試：
    對失敗的HTTP進行從新請求（重試）會減慢爬取速度，所以能夠禁止重試。在配置文件中編寫：RETRY_ENABLED = False

減小下載超時：
    若是對一個很是慢的連接進行爬取，減小下載超時能夠能讓卡住的連接快速被放棄，從而提高效率。在配置文件中進行編寫：DOWNLOAD_TIMEOUT = 10 超時時間爲10s

測試案例：爬取校花網校花圖片 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 # # 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('開始爬蟲') 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+"下載成功") def process_item(self, item, spider): obj = dict(item) json_str = json.dumps(obj,ensure_ascii=False) self.fp.write(json_str+'\n') #下載圖片 self.download_img(item) return item def close_spider(self,spider): print('結束爬蟲') 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