网络爬虫 | 使用Python采集豆瓣小组组员信息

一、寻找网址规律

点击很多个页面，最后发现网址规律

https://www.douban.com/group/{group_id}/members?start={offset}

其中

group_id为小组的id
offset 为36的倍数，随着页码的增加而增大


template = 'https://www.douban.com/group/{group_id}/members?start={offset}'

for page in range(1, 94):
    url = template.format(group_id='735596', offset=(page-1)*36)
    print(page, ' ', url)

Run

1    https://www.douban.com/group/735596/members?start=0
2    https://www.douban.com/group/735596/members?start=36
3    https://www.douban.com/group/735596/members?start=72
...... 
91    https://www.douban.com/group/735596/members?start=3240
92    https://www.douban.com/group/735596/members?start=3276
93    https://www.douban.com/group/735596/members?start=3312

二、访问测试

尝试对第一页进行方法，为了避免反爬，访问时加入header伪装头。最后检查第一页截图与resp.text内容对应上。如果一切顺利，即可定位数据。

import requests

header = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36'}

#group_id = '735596'
#url = template.format(group_id=group_id, offset=0)
url = 'https://www.douban.com/group/735596/members?start=0'

resp = requests.get(url, headers=header)
resp.text

Run

    '<!DOCTYPE html>\n<html lang="zh-CN">\n<head>\n    <meta http-equiv="Content-Type" content="text/html; charset=utf-8">\n    <meta name="renderer" content="webkit">\n    <meta name="referrer" content="always">\n    <meta name="google-site-verification" content="ok0wCgT20tBBgo9_zat2iAcimtN4Ftf5ccsh092Xeyw" />\n    <title>\n        全职儿女工作交流中心小组成员\n</title>\n    \n    \n    <meta http-equiv="Pragma" content="no-cache">\n    <meta http-equiv="Expires" content="Sun, 6 Mar 2005 01:00:00 GMT">\n class="pic">\n          <a href="https://www.douban.com/people/meetyuan/" class="nbg">\n              <img src="https://img9.doubanio.com/icon/up215413041-5.jpg" class="imgnoga" alt="无聊ớ ₃ờ" width="48px" height="48px"/>\n          </a>\n          </div>\n\n          <div class="name">\n              <a href="https://www.douban.com/people/meetyuan/" class="">无聊ớ ₃ờ</a>\n         href="https://www.douban.com/people/139539208/" class="nbg">\n              <img src="https://img2.doubanio.com/icon/up139539208-1.jpg" class="imgnoga" alt="Fortis817" width="48px" height="48px"/>\n          </a>\n          </div>\n\n          <div class="name">\n              <a href="https://www.douban.com/people/139539208/" class="">Fortis817</a>\n          <br/>\n          \n          <span class="pl">(商丘)</span>\n          </div>\n      </li>\n      \n    \n      <li class="member-item">\n          <div class="pic">\n          <a href="https://www.douban.com/people/caozhe1/" class="nbg">\n              <img src="https://img1.doubanio.com/icon/up6807132-7.jpg" class="imgnoga" alt="泛思哲" width="48px" height="48px"/>\n          </a>\n          </div>\n\n          <div class="name">\n              <a href="https://www.douban.com/people/caozhe1/" class="">泛思哲</a>\n          <br/>\n          \n          <span class="pl">(界首)</span>\n          </div>\n      </li>\n      \n    \n      <li class="member-item">\n          <div class="pic">\n          <a href="https://www.douban.com/people/234804718/" class="nbg">\n              <img src="https://img2.doubanio.com/icon/up234804718-1.jpg" class="imgnoga" alt="明月渡鴻影" width="48px" height="48px"/>\n          </a>\n          </div>\n\n          <div class="name">\n              <a href="https://www.douban.com/people/234804718/" class="">明月渡鴻影</a>\n          <br/>\n          \n          <span class="pl"></span>\n          </div>\n      </li>\n      \n    \n      <li class="member-item">\n          <div class="pic">\n          <a href="https://www.douban.com/people/138762699/" class="nbg">\n              <img src="https://img2.doubanio.com/icon/up138762699-2.jpg" class="imgnoga" alt="火焰大地" width="48px" height="48px"/>\n          </a>\n          </div>\n\n          <div class="name">\n              <a href="https://www.douban.com/people/138762699/" class="">火焰大地</a>\n          <br/>\n          \n          <span class="pl">(武汉)</span>\n          </div>\n      </li>\n      \n    \n      <li class="member-item">\n          <div class="pic">\n          <a href="https://www.douban.com/people/73205393/" class="nbg">\n              <img src="https://img2.doubanio.com/icon/up73205393-1.jpg" 
......

三、定位数据

使用pyquery定位数据，保存用户昵称、主页链接、id、城市、头像。下图是对应关系和对应的定位pyquery选择器表达式。

pyquery比较难，建议大家B站搜「大邓 Python网络爬虫快速入门」，有专门的章节讲pyquery。

from pyquery import PyQuery

doc = PyQuery(resp.text)
for item in doc.items('.member-item'):
    data = {
        'name': item('.name a').text(),
        'link': item('.name a').attr('href'),
        'id': item('.name a').attr('href').split('/')[-2],
        'city': item('.name .pl').text().replace('(', '').replace(')', ''),
        'avatar': item('.pic a img').attr('src'),
        
    }
    print(data)

Run


    {'name': '无聊ớ ₃ờ', 'link': 'https://www.douban.com/people/meetyuan/', 'id': 'meetyuan', 'city': '重庆', 'avatar': 'https://img9.doubanio.com/icon/up215413041-5.jpg'}
    {'name': '无聊ớ ₃ờ', 'link': 'https://www.douban.com/people/meetyuan/', 'id': 'meetyuan', 'city': '重庆', 'avatar': 'https://img9.doubanio.com/icon/up215413041-5.jpg'}
    {'name': 'Fortis817', 'link': 'https://www.douban.com/people/139539208/', 'id': '139539208', 'city': '商丘', 'avatar': 'https://img2.doubanio.com/icon/up139539208-1.jpg'}
    {'name': '泛思哲', 'link': 'https://www.douban.com/people/caozhe1/', 'id': 'caozhe1', 'city': '界首', 'avatar': 'https://img1.doubanio.com/icon/up6807132-7.jpg'}
   
 ......
    {'name': '豆瓣zufang', 'link': 'https://www.douban.com/people/237754807/', 'id': '237754807', 'city': '', 'avatar': 'https://img2.doubanio.com/icon/up237754807-1.jpg'}
    {'name': '豆友3giqV8i6EY', 'link': 'https://www.douban.com/people/250606383/', 'id': '250606383', 'city': '', 'avatar': 'https://img2.doubanio.com/icon/up250606383-1.jpg'}
    {'name': 'momo', 'link': 'https://www.douban.com/people/254617952/', 'id': '254617952', 'city': '南京', 'avatar': 'https://img1.doubanio.com/icon/up254617952-8.jpg'}

四、存储数据

使用csv的字典写入方式，存储数据。

import csv

group_id = '735596'

with open(f'{group_id}.csv', 'w', newline='', encoding='utf-8') as csvf:
    #定义csv内的字段
    fieldnames = ['name', 'link', 'id', 'city', 'avatar']
    writer = csv.DictWriter(csvf, fieldnames=fieldnames)
    writer.writeheader()
    
    doc = PyQuery(resp.text)
    for item in doc.items('.member-item'):
        data = {
            'name': item('.name a').text(),
            'link': item('.name a').attr('href'),
            'id': item('.name a').attr('href').split('/')[-2],
            'city': item('.name .pl').text().replace('(', '').replace(')', ''),
            'avatar': item('.pic a img').attr('src'),

        }
        
        #逐行写入
        writer.writerow(data)

五、汇总代码

将一、二、三、四等部分汇总合并，调整代码，既可以采集该豆瓣小组的信息。

import requests
import csv
import time

header = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36'}
template = 'https://www.douban.com/group/{group_id}/members?start={offset}'

group_id = '735596'

with open(f'{group_id}.csv', 'w', newline='', encoding='utf-8') as csvf:
    #定义csv内的字段
    fieldnames = ['name', 'link', 'id', 'city', 'avatar']
    writer = csv.DictWriter(csvf, fieldnames=fieldnames)
    writer.writeheader()
    
    for page in range(1, 94):
        print(f'正在采集page: {page} ')
        time.sleep(1)
        url = template.format(group_id=group_id, offset=(page-1)*36)
        resp = requests.get(url, headers=header)
        doc = PyQuery(resp.text)
        for item in doc.items('.member-item'):
            data = {
                'name': item('.name a').text(),
                'link': item('.name a').attr('href'),
                'id': item('.name a').attr('href').split('/')[-2],
                'city': item('.name .pl').text().replace('(', '').replace(')', ''),
                'avatar': item('.pic a img').attr('src'),

            }
            #逐行写入
            writer.writerow(data)

Run

    正在采集page: 1 
    正在采集page: 2 
    正在采集page: 3 
    ......
    正在采集page: 91 
    正在采集page: 92 
    正在采集page: 93

六、欣赏结果

读取数据，欣赏下结果。

import pandas as pd

df = pd.read_csv('735596.csv', encoding='utf-8')
print('小组成员数量: ', len(df))
df.head()

Run

    记录数:  3317

df.city.value_counts(ascending=False)

Run


    北京               235
    上海               148
    广州                78
    深圳                61
    南京                58
                    ... 
    河池                 1
    Faroe Islands      1
    Coventry           1
    丽江                 1
    Warszawa           1
    Name: city, Length: 275, dtype: int64

import matplotlib.pyplot as plt
import matplotlib
import matplotlib_inline
matplotlib_inline.backend_inline.set_matplotlib_formats('png', 'svg')
import scienceplots
import platform
plt.style.use(['science', 'no-latex', 'cjk-sc-font'])
system = platform.system()  # 获取操作系统类型

if system == 'Windows':
    font = {'family': 'SimHei'}
elif system == 'Darwin':
    font = {'family': 'Arial Unicode MS'}
else:
    font = {'family': 'sans-serif'}
matplotlib.rc('font', **font)  # 设置全局字体

plt.figure(figsize=(12, 8))
df.city.value_counts(ascending=False)[:15].plot(kind='pie')

svg

在饼形图中可以看到，全职儿女坐标主要集中于大城市。需要注意，豆瓣用户标注的地理位置，不一定体现现在所处的位置。

代码下载

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网络爬虫 | 使用Python采集豆瓣小组组员信息

相关内容

一、寻找网址规律

二、访问测试

三、定位数据

四、存储数据

五、汇总代码

六、欣赏结果

代码下载

广而告之

相关内容#

一、寻找网址规律#

二、访问测试#

三、 定位数据#

四、存储数据#

五、汇总代码#

六、欣赏结果#

代码下载#

广而告之#

相关内容

一、寻找网址规律

二、访问测试

三、定位数据

四、存储数据

五、汇总代码

六、欣赏结果

代码下载

广而告之