环境配置
- Ubuntu 16.04
- Python 3.5
技术框架
- Scrapy
需求目标
本项目为汽车口碑分析，第一步需要爬取对于不同车型的评论数据。
选择58车的车型分类爬取评论数据。
爬取流程
先获取每个车型的链接，以下图中红框内的车型为例
打开链接后，抓取下图红框中的总评分，写入文件中。
写入总评分后，通过拼接链接进入该车型的用户评论页面。
通过第一步中获取的链接拼接上
list_s1_p1.html，组成用户评论页面的链接。【注】此为第一页的链接，若还有下一页，下述步骤会提及处理方法。
抓取评论页面中的各种数据，如
id，评分，评论等。
若该评论页面还有
下一页，则继续抓取下一页中的评论数据。【方法】
判断页面中是否有
下一页元素，若有则回调解析评论页面的方法。将爬取的数据保存到文件中。
详细步骤
创建新工程
先创建工程目录
cd /home/t/dataset/
mkdir carSpider创建新工程
scrapy startproject carSpider编辑items.py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 CarspiderItem(scrapy.Item):
file=scrapy.Field() #文件名
car=scrapy.Field() #车型
score=scrapy.Field() #总评分
u_id=scrapy.Field() #用户ID
u_score=scrapy.Field() #用户评分
u_merit=scrapy.Field() #用户评论优点
u_demerit=scrapy.Field() #用户评论缺点
u_summary=scrapy.Field() #用户评论综述
u_flower=scrapy.Field() #用户评论鲜花数
u_brick=scrapy.Field() #用户评论板砖数编写carSpider.py文件
import scrapy
from carSpider.items import CarspiderItem
baseDir = '/home/t/dataset/carRemark/'
startUrl='http://www.58che.com/brand.html'
class CarSpider(scrapy.Spider):
name='spider' #爬虫名
def __init__(self):
self.start_urls=[startUrl]
#第一层解析方法
def parse(self,response):
#定位到车型元素
subclasses=response.css('body > div.fltop > div.marcenter > div > div > div.r > ul > li > dl > dt > a')
for subclass in subclasses:
subclass_name=subclass.xpath('text()').extract_first() #获取车型名称文本
subclass_link=subclass.xpath('@href').extract_first() #获取车型链接
yield scrapy.Request(url=subclass_link,callback=self.parse_car_subclass,meta={'file':subclass_name}) #回调下一层解析方法，并把车型名称传递给该方法作为文件名
#第二层解析方法
def parse_car_subclass(self,response):
infos=response.css('#line1 > div.cars_line2.l > div.dianpings > div.d_div1.clearfix > font') #定位到总评分元素
for info in infos:
score=info.xpath('text()').extract_first() #获取总评分元素文本
file=response.meta['file'] #获取上个Request传递来的meta['file']
self.writeScore(file,score) #将总评分写入文件中
link=response.url+'list_s1_p1.html' #拼接用户评论第一页链接
yield scrapy.Request(url=link,callback=self.parse_remark,meta={'file':file}) #回调下一层解析方法，把车型名称传递给该方法作为文件名
#第三层解析方法
def parse_remark(self,response):
#定位到用户评论元素
infos=response.css('body > div.newbox > div > div.xgo_cars_w760.l > div.xgo_dianping_infos.mb10 > div.xgo_cars_dianping > div > dl')
for info in infos:
uid=info.xpath('dd[1]/strong/a/text()')[0].extract() #获取用户ID
score=info.xpath('dd[1]/div/div/@style')[0].extract() #获取用户评分星级
score=self.getScore(score) #将用户评分星级转化为5分制评分
try:
#先获取是否有‘优点’元素，若有则定位‘优点’元素的下一个兄弟节点，即‘优点评语’，若无则为空
node=info.xpath('dd[2]/div/div[contains(@class,"l redc00")]')[0]
if node is not None:
merit=node.xpath('following-sibling::*[1]/text()')[0].extract()
else:
merit=''
except:
merit=''
try:
#先获取是否有‘缺点’元素，若有则定位‘缺点’元素的下一个兄弟节点，即‘缺点评语’，若无则为空
node=info.xpath('dd[2]/div/div[contains(@class,"l hei666")]')[0]
if node is not None:
demerit=node.xpath('following-sibling::*[1]/text()')[0].extract()
else:
demerit=''
except:
demerit=''
try:
#先获取是否有‘综述’元素，若有则定位‘综述’元素的下一个兄弟节点，即‘综述评语’，若无则为空
node=info.xpath('dd[2]/div/div[contains(@class,"l")]')[0]
if node is not None:
summary=node.xpath('following-sibling::*[1]/text()')[0].extract()
else:
summary=''
except:
summary=''
flower=info.xpath('dd[2]/div[contains(@class,"apply")]/a[3]/span/text()')[0].extract() #获取鲜花数
brick=info.xpath('dd[2]/div[contains(@class,"apply")]/a[4]/span/text()')[0].extract() #获取板砖数
#创建Item
item=CarspiderItem()
item['file']=response.meta['file']
item['u_id']=uid
item['u_score']=score
item['u_merit']=merit
item['u_demerit']=demerit
item['u_summary']=summary
item['u_flower']=flower
item['u_brick']=brick
#生成Item
yield item
#获取`下一页`元素，若有则回调`parse_remark`第三层解析方法，即继续获取下一页用户评论数据
#定位`下一页`元素
next_pages=response.css('body > div.newbox > div > div.xgo_cars_w760.l > div.xgo_dianping_infos.mb10 > div.xgo_cars_dianping > div > div > a.next')
for next_page in next_pages:
#若有`下一页`元素，则拼接`下一页`元素链接，并回调第三层解析方法，用来获取下一页用户评论数据
if next_page is not None:
next_page_link=next_page.xpath('@href')[0].extract()
next_page_link='http://www.58che.com'+next_page_link
file=response.meta['file']
yield scrapy.Request(url=next_page_link, callback=self.parse_remark, meta={'file': file})
#将总评分写入文件
def writeScore(self,file,score):
with open('/home/t/dataset/carRemark/'+file+'.json','a+') as f:
f.write(score+'\n')
#将用户评分星级转为5分制分数，类似switch功能
def getScore(self,text):
text=text.split(':')[1] #分割文本，原文本格式形如`width:100%`，分割并截取`:`后的文本
return {
'100%':5,
'80%':4,
'60%':3,
'40%':2,
'20%':1,
'0%':0
}.get(text)【解析】
#定位到用户评论元素
infos=response.css('body > div.newbox > div > div.xgo_cars_w760.l > div.xgo_dianping_infos.mb10 > div.xgo_cars_dianping > div > dl')此句代码定位的元素如下图所示，定位到的是评论页面每条评论的元素整体。
for info in infos:
uid=info.xpath('dd[1]/strong/a/text()')[0].extract() #获取用户ID
score=info.xpath('dd[1]/div/div/@style')[0].extract() #获取用户评分星级
score=self.getScore(score) #将用户评分星级转化为5分制评分uid定位到的元素如下图所示，
score定位到的元素如下图所示，获取score元素的style属性，值形如width:80%，需要通过getScore()方法转换为五分制分数。
try:
#先获取是否有‘优点’元素，若有则定位‘优点’元素的下一个兄弟节点，即‘优点评语’，若无则为空
node=info.xpath('dd[2]/div/div[contains(@class,"l redc00")]')[0]
if node is not None:
merit=node.xpath('following-sibling::*[1]/text()')[0].extract()
else:
merit=''
except:
merit=''先定位是否有优点元素，如下图红框所示，若有该元素，则获取优点元素的下一个兄弟节点内容，如下图蓝框所示，若无则为空。
#获取`下一页`元素，若有则回调`parse_remark`第三层解析方法，即继续获取下一页用户评论数据
#定位`下一页`元素
next_pages=response.css('body > div.newbox > div > div.xgo_cars_w760.l > div.xgo_dianping_infos.mb10 > div.xgo_cars_dianping > div > div > a.next')
for next_page in next_pages:
#若有`下一页`元素，则拼接`下一页`元素链接，并回调第三层解析方法，用来获取下一页用户评论数据
if next_page is not None:
next_page_link=next_page.xpath('@href')[0].extract()
next_page_link='http://www.58che.com'+next_page_link
file=response.meta['file']
yield scrapy.Request(url=next_page_link, callback=self.parse_remark, meta={'file': file})解析完上述内容，判断用户评论页面是否有分页，定位是否有下一页元素，如下图红框所示，若有则获取该元素链接，如下图橙框所示。
获取之后，回调parse_remark方法解析下一页的评论页面。
编辑pipelines.py文件
# -*- 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
import codecs
baseDir = '/home/t/dataset/carRemark/'
class CarspiderPipeline(object):
def process_item(self, item, spider):
print(item['file'])
with codecs.open(baseDir+item['file']+'.json','a+',encoding='utf-8') as f:
line=json.dumps(dict(item),ensure_ascii=False)+'\n'
f.write(line)
return item编辑settings.py文件
# -*- coding: utf-8 -*-
# Scrapy settings for carSpider project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
# http://doc.scrapy.org/en/latest/topics/settings.html
# http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
BOT_NAME = 'carSpider'
SPIDER_MODULES = ['carSpider.spiders']
NEWSPIDER_MODULE = 'carSpider.spiders'
# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'carSpider (+http://www.yourdomain.com)'
# Obey robots.txt rules
ROBOTSTXT_OBEY = False
# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32
# Configure a delay for requests for the same website (default: 0)
# See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
#DOWNLOAD_DELAY = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16
# Disable cookies (enabled by default)
#COOKIES_ENABLED = False
# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False
# Override the default request headers:
#DEFAULT_REQUEST_HEADERS = {
# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
# 'Accept-Language': 'en',
#}
# Enable or disable spider middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
# 'carSpider.middlewares.CarspiderSpiderMiddleware': 543,
#}
# Enable or disable downloader middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
# 'carSpider.middlewares.MyCustomDownloaderMiddleware': 543,
#}
# Enable or disable extensions
# See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
#EXTENSIONS = {
# 'scrapy.extensions.telnet.TelnetConsole': None,
#}
# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
'carSpider.pipelines.CarspiderPipeline': 300,
}
# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False
# Enable and configure HTTP caching (disabled by default)
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
HTTPCACHE_ENABLED = False
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = 'httpcache'
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
【解析】
ROBOTSTXT_OBEY = False将原来的True改为False。
ITEM_PIPELINES = {
'carSpider.pipelines.CarspiderPipeline': 300,
}将原来的注释去掉，即注册pipelines，否则无法使用该pipelines。
运行爬虫
在项目根目录下新建文件entrypoint.py
from scrapy.cmdline import execute
execute(['scrapy','crawl','spider'])