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

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