1、创建Scrapy项目

scrapy startproject Tencent2Spider

2.进入项目目录，使用命令genspider创建Spider

scrapy genspider -t crawl tencent "tencent.com"

3、定义要抓取的数据（处理items.py文件）

# -*- coding: utf-8 -*-
import scrapy

class Tencent2SpiderItem(scrapy.Item):
    # 职位名称
    positionName = scrapy.Field()
    # 详情链接
    positionLink = scrapy.Field()
    # 职位类别
    positionType = scrapy.Field()
    # 招聘人数
    peopleNumber = scrapy.Field()
    # 工作地点
    workLocation = scrapy.Field()
    # 发布时间
    publishTime = scrapy.Field()

4、编写提取item数据的Spider（在spiders文件夹下：tencent.py）

# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
# 如果下面在pycharm中有红色波浪线，参照这个设置：https://www.cdsy.xyz/computer/soft/develop/241211/cd65012.html
from Tencent2Spider.items import Tencent2SpiderItem

class TencentSpider(CrawlSpider):
    name = 'tencent'
    allowed_domains = ['hr.tencent.com']
    start_urls = ['https://hr.tencent.com/position.php?&start=0#a']
    # LinkExtractor()贴子的匹配规则,遵循正则
    rules = (
        Rule(LinkExtractor(allow=r'start=\d+'), callback='parse_item', follow=True),
    )
    print("数据处理中……")
    def parse_item(self, response):
        for each in response.xpath('//tr[@class="even"]|//tr[@class="odd"]'):
            # 初始化模型对象
            item = Tencent2SpiderItem()
            # 在当前根节点下查找，extract()方法返回的都是unicode字符串
            positionName = each.xpath("./td[1]/a/text()").extract()[0]
            positionLink = each.xpath("./td[1]/a/@href").extract()[0]
            # 发现职位类别有空的可能，还需要进行判断，如果为空改成未知。
            if each.xpath("./td[2]/text()[.!= '']"):
                self.positionType = each.xpath("./td[2]/text()").extract()[0]
            else:
                self.positionType = "未知"
            peopleNumber = each.xpath("./td[3]/text()").extract()[0]
            workLocation = each.xpath("./td[4]/text()").extract()[0]
            publishTime = each.xpath("./td[5]/text()").extract()[0]

            # 职位名称
            item['positionName'] = positionName.encode('utf-8')
            # 详情链接
            item['positionLink'] = positionLink.encode('utf-8')
            # 职位类别
            item['positionType'] = self.positionType.encode('utf-8')
            # 招聘人数
            item['peopleNumber'] = peopleNumber.encode('utf-8')
            # 工作地点
            item['workLocation'] = workLocation.encode('utf-8')
            # 发布时间
            item['publishTime'] = publishTime.encode('utf-8')

            yield item

5.处理pipelines管道文件保存数据，可将结果保存到文件中（pipelines.py）

# -*- coding: utf-8 -*-
import json

# 转码操作，继承json.JSONEncoder的子类
class MyEncoder(json.JSONEncoder):
    def default(self, o):
        if isinstance(o, bytes):
            return str(o, encoding='utf-8')
        return json.JSONEncoder.default(self, o)

class Tencent2SpiderPipeline(object):
    def __init__(self):
        self.filename = open("tencent.json","w",encoding="utf-8")
    def process_item(self, item, spider):
        text = json.dumps((dict(item)),ensure_ascii=False,cls=MyEncoder) +'\n'
        self.filename.write(text)
        return item

    def close_spider(self,spider):
        print("数据处理完毕，谢谢使用！")
        self.filename.close()

6.配置settings文件（settings.py）

# Obey robots.txt rules，具体含义参照：https://www.cdsy.xyz/computer/programme/Python/241210/cd64912.html
  
ROBOTSTXT_OBEY = False
    
# Override the default request headers:添加User-Agent信息    
DEFAULT_REQUEST_HEADERS = {    
  'User-Agent': 'Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0);',    
  # 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',    
  # 'Accept-Language': 'en',    
}
    
# Configure item pipelines去掉下面注释，打开管道文件    
ITEM_PIPELINES = {    
    'Tencent2Spider.pipelines.Tencent2SpiderPipeline': 300,
}
    
# 还可以将日志存到本地文件中（可选添加设置）    
LOG_FILE = "tencentlog.log"    
LOG_LEVEL = "DEBUG"   

7.以上设置完毕，进行爬取：执行项目命令crawl，启动Spider：

scrapy crawl tencent