scrapy入门二(分页抓取文章入库)

分页抓取博客园新闻,先从列表里分析下一页按钮

相关代码:

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

from cnblogs.items import ArticleItem

class BlogsSpider(scrapy.Spider):
    name = 'blogs'
    allowed_domains = ['news.cnblogs.com']
    start_urls = ['https://news.cnblogs.com/']

    def parse(self, response):
        articleList=response.css('.content')

        for item in articleList:
           # 由于详情页里浏览次数是js动态加载的,无法获取,这里需要传递过去
            viewcount = item.css('.view::text').extract_first()[:-3].strip()
            detailurl = item.css('.news_entry a::attr(href)').extract_first()
            detailurl = response.urljoin(detailurl)
            yield scrapy.Request(url=detailurl, callback=self.parse_detail, meta={"viewcount": viewcount})
        #获取下一页标签
        text=response.css('#sideleft > div.pager > a:last-child::text').extract_first().strip()
        if text=='Next >':
            next = response.css('#sideleft > div.pager > a:last-child::attr(href)').extract_first()
            url=response.urljoin(next)

            yield scrapy.Request(url=url,callback=self.parse)

    ##解析详情页内容
    def parse_detail(self, response):
        article=ArticleItem()
        article['linkurl']=response.url
        article['title']=response.css('#news_title a::text').extract_first()
        article['img'] = response.css('#news_content img::attr(src)').extract_first("default.png")
        article['source'] = response.css('.news_poster ::text').extract_first().strip()
        article['releasetime'] = response.css('.time::text').extract_first()[3:].strip()
        article['viewcount']= response.meta["viewcount"]
        article['content']=response.css('#news_body').extract_first("")

        yield article

写入数据库，先在setting.py页面配置mongo连接数据信息

ROBOTSTXT_OBEY = True
MONGODB_HOST='localhost'
MONGO_PORT=27017
MONGO_DBNAME='cnblogs'
MONGO_DOCNAME='article'

修改pipelines.py页面,相关代码

# -*- 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 pymongo
from scrapy.conf import settings
from cnblogs.items import ArticleItem
class CnblogsPipeline(object):
    #初始化信息
    def __init__(self):

        host = settings['MONGODB_HOST']
        port = settings['MONGO_PORT']
        db_name = settings['MONGO_DBNAME']
        client = pymongo.MongoClient(host=host, port=port)
        db = client[db_name]
        self.post=db[settings['MONGO_DOCNAME']]
        
     ##获取值进行入库   
    def process_item(self, item, spider):
        
        article=dict(item)
        self.post.insert(article)

        return item

__init__函数里,获取配置文件里的mongo连接信息,连接mongo库

process_item函数里获取blogs.py里parse里yield返回的每一行,然后将数据入库

最后需要在setting取消注释pipelines.py页面运行的注释，不修改(pipelines.py页面代码可能无法正常调用)

ITEM_PIPELINES = {
   'cnblogs.pipelines.CnblogsPipeline': 300,
}

 

最后在Terminal终端运行命令:scrapy crawl blogs

 

启用后便会开始进行抓取,结束后打开mongo客户端工具：库和表名创建的都是setting.py里配置的

 

 

 

到此,3000条文章资讯数据一条不差的下载下来了