注:大部分内容参考http://www.cnblogs.com/voidsky/p/5490798.html,但原文不是存在数据库中。
首先创建一个项目douban9fen
kuku@ubuntu:~/pachong$ scrapy startproject douban9fenNew Scrapy project 'douban9fen', using template directory '/usr/local/lib/python2.7/dist-packages/scrapy/templates/project', created in:
/home/kuku/pachong/douban9fen
You can start your first spider with:
cd douban9fen
scrapy genspider example example.com
kuku@ubuntu:~/pachong$ cd douban9fen/
首先,我们要确定所要抓取的信息,包括三个字段:(1)书名,(2)评分,(3)作者
然后,让我们分析下,采用火狐浏览器,进入https://www.douban.com/doulist/1264675/
按F12对上述页面进行调试
分别按照1、2、3 的步骤查看每个对象所属的div,关闭调试窗口
进而,在页面中右击查看页面源代码,在页面源代码中查看搜索3中的div标签下class为bd doulist-subject的地方
根据先大后小的原则,我们先用bd doulist-subject,把每个书找到,然后,循环对里面的信息进行提取
提取书大框架:
'//div[@class="bd doulist-subject"]'
提取题目:
'div[@class="title"]/a/text()'
提取得分:
'div[@class="rating"]/span[@class="rating_nums"]/text()'
提取作者:(这里用正则方便点)
'<div class="abstract">(.*?)<br'
经过上述分析,接下来进行代码的编写
kuku@ubuntu:~/pachong/douban9fen$ ls
douban9fen scrapy.cfg
kuku@ubuntu:~/pachong/douban9fen$ tree douban9fen/
douban9fen/├── __init__.py├── items.py├── pipelines.py├── settings.py└── spiders └── __init__.py
kuku@ubuntu:~/pachong/douban9fen/douban9fen/spiders$ vim db_9fen_spider.py
添加以下内容:
# -*- coding:utf8 -*-import scrapyimport reclass Db9fenSpider(scrapy.Spider): name = "db9fen" allowed_domains = ["douban.com"] start_urls = ["https://www.douban.com/doulist/1264675/"] #解析数据 def parse(self,response):# print response.body ninefenbook = response.xpath('//div[@class="bd doulist-subject"]') for each in ninefenbook: title = each.xpath('div[@class="title"]/a/text()').extract()[0] title = title.replace(' ','').replace('\n','') print title author = re.search('<div class="abstract">(.*?)<br',each.extract(),re.S).group(1) author = author.replace(' ','').replace('\n','') print author rate = each.xpath('div[@class="rating"]/span[@class="rating_nums"]/text()').extract()[0] print rate
保存。
为方便执行,我们将建立一个main.py文件
kuku@ubuntu:~/pachong/douban9fen/douban9fen/spiders$ cd ../..kuku@ubuntu:~/pachong/douban9fen$ vim main.py
添加以下内容,
# -*- coding:utf8 -*-import scrapy.cmdline as cmdcmd.execute('scrapy crawl db9fen'.split()) #db9fen 对应着db_9fen_spider.py文件中的name变量值
保存。
此时,我们可以执行下
kuku@ubuntu:~/pachong/douban9fen$ python main.py
但此时只能抓取到当前页面中的信息,查看页面中的后页信息
可以看到是存在标签span中的class="next"下,我们只需要将这个链接提取出来,进而对其进行爬取
'//span[@class="next"]/link/@href'
然后提取后 我们scrapy的爬虫怎么处理呢?
可以使用yield,这样爬虫就会自动执行url的命令了,处理方式还是使用我们的parse函数
yield scrapy.http.Request(url,callback=self.parse)
然后将更改db_9fen_spider.py文件,添加以下内容到for函数中。
nextpage = response.xpath('//span[@class="next"]/link/@href').extract() if nextpage: print nextpage next = nextpage[0] print next yield scrapy.http.Request(next,callback=self.parse)
如图所示
可能有些人想问,next = nextpage[0]什么意思,这里可以解释以下,变量nextpage是一个列表,列表里面存的是一个链接字符串,next = nextpage[0]就是将这个链接取出并赋值给变量next。
现在可以在items文件中定义我们要抓取的字段
kuku@ubuntu:~/pachong/douban9fen/douban9fen$ vim items.py
编辑item.py文件中的内容是:
# -*- coding: utf-8 -*-# Define here the models for your scraped items## See documentation in:# http://doc.scrapy.org/en/latest/topics/items.htmlimport scrapyfrom scrapy import Fieldclass Douban9FenItem(scrapy.Item): # define the fields for your item here like: # name = scrapy.Field() title = Field() author = Field() rate = Field()
定义好字段之后,将重新对db_9fen_spider.py进行编辑,将刚才抓取到的三个字段存放在items.py中类的实例中,作为属性值。
kuku@ubuntu:~/pachong/douban9fen/douban9fen$ cd spiders/kuku@ubuntu:~/pachong/douban9fen/douban9fen/spiders$ vim db_9fen_spider.py
# -*- coding:utf8 -*-import scrapyimport refrom douban9fen.items import Douban9FenItemclass Db9fenSpider(scrapy.Spider): name = "db9fen" allowed_domains = ["douban.com"] start_urls = ["https://www.douban.com/doulist/1264675/"] #解析数据 def parse(self,response):# print response.body ninefenbook = response.xpath('//div[@class="bd doulist-subject"]') for each in ninefenbook: item = Douban9FenItem() title = each.xpath('div[@class="title"]/a/text()').extract()[0] title = title.replace(' ','').replace('\n','') print title item['title'] = title author = re.search('<div class="abstract">(.*?)<br',each.extract(),re.S).group(1) author = author.replace(' ','').replace('\n','') print author item['author'] = author rate = each.xpath('div[@class="rating"]/span[@class="rating_nums"]/text()').extract()[0] print rate item['rate'] = rate yield item nextpage = response.xpath('//span[@class="next"]/link/@href').extract() if nextpage:# print nextpage next = nextpage[0]# print next yield scrapy.http.Request(next,callback=self.parse)
编辑setting.py,添加数据库配置信息
USER_AGENT = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN; rv:1.8.1.14) Gecko/20080404 Firefox/44.0.2'# start MySQL database configure settingMYSQL_HOST = 'localhost'MYSQL_DBNAME = 'douban9fen'MYSQL_USER = 'root'MYSQL_PASSWD = 'openstack' # end of MySQL database configure settingITEM_PIPELINES = { 'douban9fen.pipelines.Douban9FenPipeline': 300,}
注意mysql数据库是预先安装进去的,可以看到数据库的名称为douban9fen,因此我们首先需要在数据库中创建douban9fen 数据库
kuku@ubuntu:~/pachong/douban9fen/douban9fen/spiders$ mysql -uroot -pEnter password: Welcome to the MySQL monitor. Commands end with ; or \g.Your MySQL connection id is 46Server version: 5.5.52-0ubuntu0.14.04.1 (Ubuntu)Copyright (c) 2000, 2016, Oracle and/or its affiliates. All rights reserved.Oracle is a registered trademark of Oracle Corporation and/or itsaffiliates. Other names may be trademarks of their respectiveowners.Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.mysql> create database douban9fen;Query OK, 1 row affected (0.00 sec)
mysql> show databases;
+--------------------+| Database |+--------------------+| information_schema || csvt04 || douban9fen || doubandianying || mysql || performance_schema || web08 |+--------------------+7 rows in set (0.00 sec)
可以看到已经创建数据库成功;
mysql> use douban9fen;
接下来创建数据表
mysql> create table douban9fen (id int(4) not null primary key auto_increment, title varchar(100) not null,author varchar(40) not null, rate varchar(20) not null )CHARACTER SET utf8 COLLATE utf8_general_ci; Query OK, 0 rows affected (0.04 sec)
编辑pipelines.py,将数据储存到数据库中,
kuku@ubuntu:~/pachong/douban9fen/douban9fen$ vim pipelines.py
# -*- 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#将数据存储到mysql数据库from twisted.enterprise import adbapiimport MySQLdbimport MySQLdb.cursorsclass Douban9FenPipeline(object): #数据库参数 def __init__(self): dbargs = dict( host = '127.0.0.1', db = 'douban9fen', user = 'root', passwd = 'openstack', cursorclass = MySQLdb.cursors.DictCursor, charset = 'utf8', use_unicode = True ) self.dbpool = adbapi.ConnectionPool('MySQLdb',**dbargs) def process_item(self, item, spider): res = self.dbpool.runInteraction(self.insert_into_table,item) return item #插入的表,此表需要事先建好 def insert_into_table(self,conn,item): conn.execute('insert into douban9fen( title,author,rate) values(%s,%s,%s)', ( item['title'], item['author'], item['rate'] ) )
编辑好上面的红色标注的文件后,
kuku@ubuntu:~/pachong/douban9fen/douban9fen$ cd ..kuku@ubuntu:~/pachong/douban9fen$
再执行 main.py文件
kuku@ubuntu:~/pachong/douban9fen$ python main.py
执行过程如下:
打开mysql ,查看是否已经写入到数据库中;
kuku@ubuntu:~/pachong/douban9fen$ mysql -uroot -p
输入密码openstack 登录
mysql> show databases;
+--------------------+| Database |+--------------------+| information_schema || csvt04 || douban9fen || doubandianying || mysql || performance_schema || web08 |+--------------------+7 rows in set (0.00 sec)
mysql> use douban9fen;
Reading table information for completion of table and column namesYou can turn off this feature to get a quicker startup with -ADatabase changed
mysql> show tables;
+----------------------+| Tables_in_douban9fen |+----------------------+| douban9fen |+----------------------+1 row in set (0.00 sec)
mysql> select * from douban9fen;
显示能够成功写入到数据库中。
本文出自 “lefteva” 博客,请务必保留此出处http://lefteva.blog.51cto.com/11892835/1874863