使用 scrapy 爬取 微博热搜

安装

pip install Scrapy

创建项目

scrapy startproject weiboHotSearch

创建爬虫

cd weiboHotSearch
scrapy genspider weibo s.weibo.com

编写Item

修改weiboHotSearch中的items.py,添加item

import scrapy


class WeibohotsearchItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    pass
    keyword = scrapy.Field()
    url = scrapy.Field()
    count = scrapy.Field()

编写爬虫

1. 修改start_urls,注意为list格式

2. 使用xpath解析数据

   xpath语法可参考https://www.w3school.com.cn/xpath/xpath_syntax.asp

   解析数据时,可运行scrapy shell "https://s.weibo.com/top/summary"调试xpath

   

3. 引入Item,将数据以Itme对象返回

4. 执行scrapy crawl weibo运行爬虫

   运行结果如下:

   

   weibo.py的完整代码

import scrapy

from weiboHotSearch.items import WeibohotsearchItem
class WeiboSpider(scrapy.Spider):
    name = 'weibo'
    allowed_domains = ['s.weibo.com']
    start_urls = ['https://s.weibo.com/top/summary']

    def parse(self, response):
        pass
        for i in response.xpath('//*[@id="pl_top_realtimehot"]/table/tbody/tr/td[2]'):
            keyword = i.xpath('a/text()').extract_first()
            url = 'https://s.weibo.com'+i.xpath('a/@href').extract_first()
            count = i.xpath('span/text()').extract_first()
            print(keyword)
            print(count)
            # print(url)
            item = WeibohotsearchItem()
            item['keyword'] = keyword
            item['url'] = url
            item['count'] = count
            yield item

保存数据

• 使用Feed export 保存

使用以下命令即可将数据保存到items.json中

scrapy crawl weibo -o items.json
cat items.json

• 使用Item Pipeline保存

  1. 编写pipeline

     修改pipelines.py,添加保存

     class WeibohotsearchPipeline(object):
         def __init__(self):
             self.f = open('items.csv','w')
     
         def process_item(self, item, spider):
             res = item['keyword']+','+item['count']+','+item['url']+"\n"
     
             self.f.write(res)
             return item

  2. 启用item pipline

     将以下内容添加到settings.py中即可启用Pipline

     ITEM_PIPELINES = {
        'weiboHotSearch.pipelines.WeibohotsearchPipeline': 300,
     }

  3. 运行

     scrapy crawl weibo 
     cat items.csv

数据如下:

项目地址

https://gitee.com/yu-se/scrapy-test

参考文档

https://scrapy-chs.readthedocs.io/zh_CN/latest/

标签：xpath,weibo,items,爬取,item,scrapy,com,微博热
来源： https://www.cnblogs.com/lzyuid/p/12403151.html