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
# -*- 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
# -*- 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
# -*- 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
ROBOTSTXT_OBEY = False
#下载延迟 DOWNLOAD_DELAY = 3
#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', }
#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