Scrapy框架实例（爬取刺猬实习职位信息）

本文主要是介绍Scrapy框架实例（爬取刺猬实习职位信息），希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

点击查看刺猬实习网站

这次用的是scrapy框架爬取，爬的内容是左边分类里面的每一个分类第一页的求职信息

求职信息如图：

这次爬的有职位，薪水，学历，天数，地理位置

思路：

首先在自己创建的小蜘蛛里设置一个函数，处理开始的页面抓到所有的分类链接，然后用callback回调处理页面函数，再将提取信息传入pipelines保存。

代码呈上：

首先是items部分：

# -*- coding: utf-8 -*-# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.htmlimport scrapyclass JobItem(scrapy.Item):# define the fields for your item here like:# name = scrapy.Field()title = scrapy.Field()#职位salary = scrapy.Field()#薪水education_background = scrapy.Field()#学历day = scrapy.Field()#天数location = scrapy.Field()#位置

settings：（只需要修改一些信息即可）

BOT_NAME = 'job'SPIDER_MODULES = ['job.spiders']
NEWSPIDER_MODULE = 'job.spiders'ROBOTSTXT_OBEY = FalseDEFAULT_REQUEST_HEADERS = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/72.0.3626.81 Safari/537.36','Referer': 'https://blog.csdn.net/qq_43391383/article/details/87033451','Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8','Accept-Language': 'en',
}
LOG_LEVEL = 'WARNING'ITEM_PIPELINES = {'job.pipelines.JobPipeline': 300,
}

下面是最重要的小蜘蛛：(这里起名为ciwei)

# -*- coding: utf-8 -*-
import scrapy
from job.items import JobItem
import timeclass CiweiSpider(scrapy.Spider):name = 'ciwei'allowed_domains = ['ciweishixi.com']#域名start_urls = ['https://www.ciweishixi.com/']#初始url#抓取初始页面的各种分类的url然后访问将响应传给get_HTML函数def parse(self, response):infos = response.xpath('/html/body/div[2]/div[1]/div/div')for info in infos:urls = info.xpath('div[2]/a/@href').extract()for url in urls:requests = scrapy.Request(url, method="get", callback=self.get_Html)yield requests#接收响应抽取我们要的信息def get_Html(self, response):infos = response.xpath('/html/body/div[2]/section[2]/div/section/article')for info in infos:item = JobItem()#实习职位item['title'] = info.xpath('div[2]/div[1]/a/text()').extract_first()main = info.xpath('div[2]/div[2]/span/text()').extract()#薪水item['salary'] = main[0]#学历item['education_background'] = main[1]#天数item['day'] = main[-1]#位置item['location'] = info.xpath('div[2]/div[1]/div/i[2]/text()').extract_first()yield itemtime.sleep(1)#设置休眠时间

pipelines：

# -*- 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 csv
import codecsclass JobPipeline(object):#以TXT文本保存# def __init__(self):#     self.fp = open("F://ciwei.txt","a+",encoding="utf-8")## def process_item(self, item, spider):#     self.fp.write(#         str((item['title'].strip(),item['salary'],item['education_background'],item['day'],item['location'])) + '\n'#     )##     return item## def close(self):#     self.fp.close()#Excel保存def __init__(self):with open("F://qiuzhi.csv", "ab+") as self.fp:self.fp.write(codecs.BOM_UTF8)  # 为了防止在windows下直接打开csv文件出现乱码self.fp = open("F://qiuzhi.csv",'a+',newline='',encoding='utf-8')self.write = csv.writer(self.fp)self.write.writerow(['职位', '薪水', '学历', '天数', '地区'])def process_item(self, item, spider):self.write.writerow([item['title'].strip(),item['salary'],item['education_background'],item['day'],item['location']])def close(self):self.fp.close()

最后在cmd中cd到文件所在目录执行scrapy crawl ciwei

可以看到我们要的信息已经保存在F盘中的文件内