Python爬虫实战：爬取【某旅游交通出行类网站中国内热门景点】的评论数据,使用Re、BeautifulSoup与Xpath三种方式解析数据，代码完整

一、分析爬取网页：

1、网址

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https://travel.qunar.com/

2、打开网站，找到要爬取的网页

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https://travel.qunar.com/p-cs299979-chongqing

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进来之后，找到评论界面，如下所示：在这里我选择驴友点评数据爬取

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点击【驴友点评】，进入最终爬取的网址：https://travel.qunar.com/p-cs299979-chongqing-gaikuang-2-1-1#lydp

3、进入开发者模型（F12），分析网页，找到数据接口

（1）点击网络

（2）点击左边网页中的第二、第三、第四...页，观察右边的变化：发现右边有一地址带有页数和每页数据量，因此点击该地址在网页中打开发现带有json格式的数据并且数据对应就是该页的内容，如下所示：

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接口地址：https://travel.qunar.com/place/api/html/comments/dist/299979?sortField=1&pageSize=10&page=1

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并且只要变换接口地址后面的page就可以获取不同页数的数据。同理，我们发现【热门攻略】也是如此，因此将其顺带也爬取出来，数据接口地址：https://travel.qunar.com/place/api/html/books/dist/299979?sortField=0&pageSize=10&page=2

三、请求网页数据并将数据进行保存

当我们确定了真实数据的URL后，这里便可以用requests的get或post方法进行请求网页数据。关于requests库的更多使用方式，大家可以前往(https://requests.readthedocs.io/zh_CN/latest/ 或 https://www.cnblogs.com/aaronthon/p/9332757.html)查看。

1、分析爬取的json数据，为提取数据做准备，如下图所示：json数据里提取的data数据是我们所需要的数据，而data数据就是html形式的字符串，打开网页与其对比，发现最后需要获取的数据在li标签里面，因此我们选择对其进行提取：采用正则与Beautiful Soup、xpath来解析数据

2、正则re提取数据，完整代码如下：

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# coding:utf-8
import requests,time,os,openpyxl,re
from openpyxl import Workbook
import mysql.connector

class RenrenLogin(object):
    def __init__(self):
        # 设置存储数据文件路径
        self.excellj = ''
        self.excellj1 = r"C:\XXXXXXXXXXXX\qne1.xlsx"
        self.excellj2 = r"C:\XXXXXXXXXXXX\qne2.xlsx"

    def get_html(self, url,names):
        # 因此f12查看时，数据为json格式
        data1 = requests.get(url=url).json()
        self.parse_html(data1,names)

    def parse_html(self, data,names):
        L1,L2,L3,L4,L5,L6,L7,L8 = [],[],[],[],[],[],[],[]
        if(names == "热门攻略"):
            userurl = re.findall(r'<a rel="nofollow" class="face" target="_blank" href="(.*?)".*?</a>', data["data"],re.S)                     # 用户url地址
            userpicture = re.findall(r'<img class="imgf" width="50" height="50" src="(.*?)"', data["data"], re.S)                              # 用户头像
            usertitle = re.findall(r'<img class="imgf".*?title="(.*?)"', data["data"], re.S)                                                   # 用户昵称
            L1 = re.findall(r'<h3 class="tit"><a data-beacon="travelbook" target="_blank" href=".*?">(.*?)</h3>',data["data"], re.S)           # 用户发表标题
            for i in L1:
                L2.append(''.join(re.findall('[\u4e00-\u9fa5]', i)))
            usersubject = L2

            userinfourl =  re.findall(r'<a data-beacon="travelbook" target="_blank" href="(.*?)"', data["data"], re.S)                         # 用户详情
            L3 =  re.findall(r'<p class="places">(.*?)<span class="colOrange">(.*?)</span></p><p class="places">',data["data"], re.S)          # 用户途径
            for i in L3:
                L4.append(i[1])
            useraddress = L4
            L5 = re.findall(r'<p class="places">途经：(.*?)</p><ul class="pics">', data["data"], re.S)                                          # 用户行程
            for i in L5:
                L6.append(''.join(re.findall('[\u4e00-\u9fa5： ]',i)))
            userstroke = L6
            L7 = re.findall(r'<ul class="pics">(.*?)</li></ul>', data["data"], re.S)                                                           # 用户发表图片
            for i in L7:
                L8.append(re.findall(r'src="(.*?)"', i, re.S))
            userimages = L8
            userdz = re.findall(r'<i class="iconfont">&#xe09d;</i><span>(.*?)</span>', data["data"], re.S)                                     # 用户点赞数量
            userpl = re.findall(r'<i class="iconfont">&#xf04f;</i><span>(.*?)</span>', data["data"], re.S)                                     # 用户评论数量
            for i in range(len(usertitle)):
                alldata = []
                alldata.append(usertitle[i])
                alldata.append(usersubject[i])
                alldata.append(useraddress[i])
                alldata.append(userstroke[i])
                alldata.append(userdz[i])
                alldata.append(userpl[i])
                alldata.append(userpicture[i])
                alldata.append(userurl[i])
                alldata.append(userinfourl[i])
                alldata.append(str(userimages[i]))
                self.parse_excel(alldata,names)
        else:
            usertitle = re.findall(r'<div class="e_comment_usr_name"><a rel="nofollow" href=".*?" target="_blank">(.*?)</a></div>',data["data"], re.S)
            userurl = re.findall(r'<div class="e_comment_usr_name"><a rel="nofollow" href="(.*?)" target="_blank">.*?</a></div>',data["data"], re.S)
            usercomtit = re.findall(r'<a data-beacon="comment_title" href=".*?" target="_blank">(.*?)</a><span class="icon_gold_camel">',data["data"], re.S)
            L1 = re.findall(r'<div class="e_comment_content">(.*?)阅读全部</a></div>', data["data"], re.S)
            for i in L1:
                L2.append(''.join(re.findall('[\u4e00-\u9fa5 ]',i)))
            usercomment = L2
            L3 = re.findall(r'<ul class="base_fl" ><li><a rel="nofollow" data-beacon="comment_pic" href=".*?" target="_blank">共.*?张》',data["data"], re.S)
            for i in L3:
                L4.append(re.findall(r'src="(.*?)"', i, re.S))
            if(len(L4) < 10 ):
                for i in range(10-len(L4)):
                    L4.append('空')
                userimages = L4
            else:
                userimages = L4
            userpicture = re.findall(r'<div class="e_comment_usr_pic"><a rel="nofollow" href=".*?" target="_blank"><img .*? src="(.*?)" /></a></div>',data["data"], re.S)
            for i in range(len(usertitle)):
                alldata = []
                alldata.append(usertitle[i])
                alldata.append(usercomtit[i])
                alldata.append(usercomment[i])
                alldata.append(userurl[i])
                alldata.append(str(userimages[i]))
                alldata.append(userpicture[i])
                self.parse_excel(alldata, names)
        return True

    def parse_excel(self, alldata,names):
        if(names == "热门攻略"):
            self.excellj = self.excellj1
            filetitle = ["用户昵称","用户发表主题","用户途径","用户路径","用户点赞数","用户评论数","用户头像","用户主页地址","用户详情地址","用户发布图片"]
        else:
            self.excellj = self.excellj2
            filetitle = ["用户昵称","用户发表主题","用户评论","用户主页地址","用户发布图片","用户头像"]
        if not os.path.exists(self.excellj):
            workbook = Workbook()
            workbook.save(self.excellj)
            wb = openpyxl.load_workbook(self.excellj)
            wa = wb.active
            wa.append(filetitle)
            wa.append(alldata)
            wb.save(self.excellj)
        else:
            wb = openpyxl.load_workbook(self.excellj)
            wa = wb.active
            wa.append(alldata)
            wb.save(self.excellj)
        return True

    def main(self, ):
        UrlList = ["https://travel.qunar.com/place/api/html/books/dist/299979?sortField=0&pageSize=10&page=","https://travel.qunar.com/place/api/html/comments/dist/299979?sortField=1&pageSize=10&page="]
        names = ["热门攻略","驴友点评"]
        for i in range(len(UrlList)):
            for j in range(1,3):
                url = UrlList[i] + str(j)
                self.get_html(url,names[i])
                print(f"重庆地区【{names[i]}】第{j}页数据爬取结束！！！")
                time.sleep(10)

if __name__ == '__main__':
    spider = RenrenLogin()
    spider.main()

结果如下所示：

【热门攻略】：

【驴友点评】：

3、BeautifulSoup提取数据，完整代码如下：这里只爬取了驴友点评，热门攻略也是一样方法

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# coding:utf-8
import requests,time,os,openpyxl,re
from openpyxl import Workbook
from bs4 import BeautifulSoup

class RenrenLogin(object):
    def __init__(self):
        self.excellj = r"C:\XXXXXXXXXXXX\qne1.xlsx"

    def get_html(self, url):
        data1 = requests.get(url=url).json()
        self.parse_html(data1)

    def parse_html(self, data):
        soup = BeautifulSoup(data["data"], 'lxml')
        L1,L2,L3,L4,L5,L6,L7,L8 = [],[],[],[],[],[],[],[]
        sellList1 = soup.find_all('div',class_="e_comment_usr_name")
        for i in sellList1:
            soup1 = BeautifulSoup(str(i), 'lxml')
            div_tag = soup1.find('div')
            a_tags = div_tag.find('a')
            userhref = a_tags.get('href')
            L1.append(userhref)
            L2.append(a_tags.text)
        usertitle = L2
        userurl = L1
        sellList2 = soup.find_all('div',class_="e_comment_title")
        for i in sellList2:
            soup1 = BeautifulSoup(str(i), 'lxml')
            div_tag = soup1.find('div')
            a_tags = div_tag.find('a')
            L3.append(a_tags.text)
        usercomtit = L3
        sellList3 = soup.find_all('div',class_="e_comment_content")
        for i in sellList3:
            str1 = ''
            soup1 = BeautifulSoup(str(i), 'lxml')
            div_tag = soup1.find('div')
            a_tags = div_tag.find_all('p')
            for tag in a_tags:
                str1 = str1 + tag.text +' '
            L4.append(str1)
        usercomment = L4
        sellList4 = soup.find_all('div', class_="e_comment_imgs clrfix")
        L1 = []
        for i in sellList4:
            str1 = ''
            soup1 = BeautifulSoup(str(i), 'lxml')
            div_tag = soup1.find('div')
            a_tags = div_tag.find_all('img')
            for j in a_tags:
                str1 = str1 + j.get("src") + ' , '
            L5.append(str1)
        if (len(L5) < 10):
            for i in range(10 - len(L4)):
                L5.append('空')
            userimages = L5
        else:
            userimages = L5
        sellList5 = soup.find_all('div',class_="e_comment_usr_pic")
        for i in sellList5:
            soup1 = BeautifulSoup(str(i), 'lxml')
            div_tag = soup1.find('div')
            a_tags = div_tag.find('a')
            userhref = a_tags.get('href')
            L6.append(userhref)
        userpicture = L6
        for i in range(len(usertitle)):
            alldata = []
            alldata.append(usertitle[i])
            alldata.append(usercomtit[i])
            alldata.append(usercomment[i])
            alldata.append(userurl[i])
            alldata.append(str(userimages[i]))
            alldata.append(userpicture[i])
            self.parse_excel(alldata)
        return True

    def parse_excel(self, alldata):
        filetitle = ["用户昵称","用户发表主题","用户评论","用户主页地址","用户发布图片","用户头像"]
        if not os.path.exists(self.excellj):
            workbook = Workbook()
            workbook.save(self.excellj)
            wb = openpyxl.load_workbook(self.excellj)
            wa = wb.active
            wa.append(filetitle)
            wa.append(alldata)
            wb.save(self.excellj)
        else:
            wb = openpyxl.load_workbook(self.excellj)
            wa = wb.active
            wa.append(alldata)
            wb.save(self.excellj)
        return True

    def main(self, ):
        UrlList = ["https://travel.qunar.com/place/api/html/comments/dist/299979?sortField=1&pageSize=10&page="]
        names = ["驴友点评"]
        for i in range(len(UrlList)):
            for j in range(1,3):
                url = UrlList[i] + str(j)
                self.get_html(url)
                print(f"重庆地区【{names[i]}】第{j}页数据爬取结束！！！")
                time.sleep(10)

if __name__ == '__main__':
    spider = RenrenLogin()
    spider.main()

【驴友点评】：

4、Xpath提取数据，完整代码如下：这里只爬取了热门攻略，驴友点评也是一样方法

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# coding:utf-8
import requests,time,os,openpyxl,re
from openpyxl import Workbook
from lxml import etree

class RenrenLogin(object):
    def __init__(self):
        self.excellj = r"C:\XXXXXXXXXX\qne1.xlsx"

    def get_html(self, url):
        data1 = requests.get(url=url).json()
        self.parse_html(data1)

    def parse_html(self, data):
        L1,L2,L3,L4,L6 = [],[],[],[],[]
        html = etree.HTML(data["data"])
        usertitle = html.xpath('//span[@class="user_name"]/a/text()')
        userurl = html.xpath('//span[@class="user_name"]/a/@href')
        userpicture = html.xpath('//img[@class="imgf"]/@src')
        for i in range(10):
            userzt1 = html.xpath('//h3[@class="tit"]')[i]
            userzt2 = userzt1.xpath('./a/text()')
            str1 = ''
            for j in range(len(userzt2)):
                str1 = str1 + userzt2[j]
            L1.append(str1)
        usersubject = L1
        for i in range(10):
            useraddres1 = html.xpath('//li[@class="list_item"]')[i]
            useraddres2 = useraddres1.xpath('p/text()')[0]
            useraddres3 = html.xpath('//span[@class="colOrange"]')[i]
            useraddres4 = useraddres3.xpath('./text()')[0]
            L2.append(useraddres2 + useraddres4)
        useraddress = L2
        for i in range(10):
            userstroke1 = html.xpath('//li[@class="list_item"]')[i]
            userstroke2 = userstroke1.xpath('p[4]/text()')
            L3.append(userstroke2)
        userstroke = L3
        for i in range(10):
            userimages = html.xpath('//ul[@class="pics"]')[i]
            L5 = []
            for j in range(1, len(userimages) + 1):
                L5.append(userimages.xpath(f'li[{j}]/a/img/@src'))
            L4.append(L5)
        userimages = L4
        userdz = html.xpath('//span[@class="icon_view"]/span/text()')
        userpl = html.xpath('//span[@class="icon_love"]/span/text()')
        for i in range(len(usertitle)):
            alldata = []
            alldata.append(usertitle[i])
            alldata.append(usersubject[i])
            alldata.append(useraddress[i])
            alldata.append(str(userstroke[i]))
            alldata.append(userdz[i])
            alldata.append(userpl[i])
            alldata.append(userpicture[i])
            alldata.append(userurl[i])
            alldata.append(str(userimages[i]))
            self.parse_excel(alldata)
        return True

    def parse_excel(self, alldata):
        filetitle = ["用户昵称","用户发表主题","用户途径","用户路径","用户点赞数","用户评论数","用户头像","用户主页地址","用户发布图片"]
        if not os.path.exists(self.excellj):
            workbook = Workbook()
            workbook.save(self.excellj)
            wb = openpyxl.load_workbook(self.excellj)
            wa = wb.active
            wa.append(filetitle)
            wa.append(alldata)
            wb.save(self.excellj)
        else:
            wb = openpyxl.load_workbook(self.excellj)
            wa = wb.active
            wa.append(alldata)
            wb.save(self.excellj)
        return True

    def main(self, ):
        UrlList = ["https://travel.qunar.com/place/api/html/books/dist/299979?sortField=0&pageSize=10&page="]
        names = ["热门攻略"]
        for i in range(len(UrlList)):
            for j in range(1,3):
                url = UrlList[i] + str(j)
                self.get_html(url)
                print(f"重庆地区【{names[i]}】第{j}页数据爬取结束！！！")
                time.sleep(10)

if __name__ == '__main__':
    spider = RenrenLogin()
    spider.main()

结果如下：

Python爬虫实战：爬取【某旅游交通出行类网站中国内热门景点】的评论数据,使用Re、BeautifulSoup与Xpath三种方式解析数据，代码完整

一、分析爬取网页：

1、网址

2、 打开网站，找到要爬取的网页

3、 进入开发者模型（F12），分析网页，找到数据接口

三、请求网页数据并将数据进行保存

2、正则re提取数据，完整代码如下：

3、BeautifulSoup提取数据，完整代码如下：这里只爬取了驴友点评，热门攻略也是一样方法

4、Xpath提取数据，完整代码如下：这里只爬取了热门攻略，驴友点评也是一样方法

2、打开网站，找到要爬取的网页

3、进入开发者模型（F12），分析网页，找到数据接口