python3 scrapy 爬取腾讯招聘
安装scrapy不再赘述,
在控制台中输入scrapy startproject tencent 创建爬虫项目名字为 tencent
接着cd tencent
用pycharm打开tencent项目
构建item文件
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# -*- coding: utf-8 -*- # Define here the models for your scraped items # # See documentation in: # http://doc.scrapy.org/en/latest/topics/items.html import scrapy class TencentItem(scrapy.Item): # define the fields for your item here like: # name = scrapy.Field() #职位名 positionname = scrapy.Field() #详细链接 positionLink = scrapy.Field() #职位类别 positionType = scrapy.Field() #招聘人数 peopleNum = scrapy.Field() #工作地点 workLocation = scrapy.Field() #发布时间 publishTime = scrapy.Field() |
接着在spiders文件夹中新建tencentPostition.py文件代码如下注释写的很清楚
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# -*- coding: utf-8 -*- import scrapy from tencent.items import TencentItem class TencentpostitionSpider(scrapy.Spider): #爬虫名 name = 'tencent' #爬虫域 allowed_domains = [ 'tencent.com' ] #设置URL url = 'http://hr.tencent.com/position.php?&start=' #设置页码 offset = 0 #默认url start_urls = [url + str (offset)] def parse( self , response): #xpath匹配规则 for each in response.xpath( "//tr[@class='even'] | //tr[@class='odd']" ): item = TencentItem() # 职位名 item[ "positionname" ] = each.xpath( "./td[1]/a/text()" ).extract()[ 0 ] # 详细链接 item[ "positionLink" ] = each.xpath( "./td[1]/a/@href" ).extract()[ 0 ] # 职位类别 try : item[ "positionType" ] = each.xpath( "./td[2]/text()" ).extract()[ 0 ] except : item[ "positionType" ] = '空' # 招聘人数 item[ "peopleNum" ] = each.xpath( "./td[3]/text()" ).extract()[ 0 ] # 工作地点 item[ "workLocation" ] = each.xpath( "./td[4]/text()" ).extract()[ 0 ] # 发布时间 item[ "publishTime" ] = each.xpath( "./td[5]/text()" ).extract()[ 0 ] #把数据交给管道文件 yield item #设置新URL页码 if ( self .offset< 2620 ): self .offset + = 10 #把请求交给控制器 yield scrapy.Request( self .url + str ( self .offset),callback = self .parse) |
接着配置管道文件pipelines.py代码如下
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# -*- coding: utf-8 -*- # Define your item pipelines here # # Don't forget to add your pipeline to the ITEM_PIPELINES setting # See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html import json class TencentPipeline( object ): def __init__( self ): #在初始化方法中打开文件 self .fileName = open ( "tencent.json" , "wb" ) def process_item( self , item, spider): #把数据转换为字典再转换成json text = json.dumps( dict (item),ensure_ascii = False ) + "\n" #写到文件中编码设置为utf-8 self .fileName.write(text.encode( "utf-8" )) #返回item return item def close_spider( self ,spider): #关闭时关闭文件 self .fileName.close() |
接下来需要配置settings.py文件
不遵循ROBOTS规则
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ROBOTSTXT_OBEY = False |
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#下载延迟 DOWNLOAD_DELAY = 3 |
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#设置请求头 DEFAULT_REQUEST_HEADERS = { 'User-Agent' : 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.84 Safari/537.36' , 'Accept' : 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8' , } |
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#交给哪个管道文件处理 文件夹.管道文件名.类名 ITEM_PIPELINES = { 'tencent.pipelines.TencentPipeline' : 300 , } |
接下来再控制台中输入
scrapy crawl tencent
即可爬取
源码地址
https://github.com/ingxx/scrapy_to_tencent