初级爬虫实战——麻省理工学院新闻

浅浅的花香味﹌ 2024-04-06 15:29 119阅读 0赞

#### 文章目录 ####

*  发现宝藏
 *  一、 目标
 *  二、 浅析
 *  三、获取所有模块
 *  四、请求处理模块、版面、文章
 *   *  1. 分析切换页面的参数传递
     *  2. 获取共有多少页标签并遍历版面
     *  3.解析版面并保存版面信息
     *  4. 解析文章列表和文章
     *  5. 清洗文章
     *  6. 保存文章图片
 *  五、完整代码
 *  六、效果展示

## 发现宝藏 ##

前些天发现了一个巨牛的人工智能学习网站，通俗易懂，风趣幽默，忍不住分享一下给大家。【[宝藏入口][Link 1]】。

## 一、 目标 ##

爬取`news.mit.edu`的字段,包含标题、内容，作者，发布时间，链接地址，文章快照 (可能需要翻墙才能访问)

## 二、 浅析 ##

**1.全部新闻大致分为4个模块**  
![在这里插入图片描述][12eea90e254b441784941f2251974cea.png]

**2.每个模块的标签列表大致如下**

![在这里插入图片描述][44eb8f184bbe4e0db5543f275f2d0c71.png]  
**3.每个标签对应的文章列表大致如下**

![在这里插入图片描述][7ee4a4171b784df99704ea99939f0628.png]

**4.具体每篇文章对应的结构如下**

![在这里插入图片描述][d18d96988be24f1eac70c9d43d8eaacf.png]

## 三、获取所有模块 ##

其实就四个模块，列举出来就好，然后对每个分别解析爬取每个模块

class MitnewsScraper:
        def __init__(self, root_url, model_url, img_output_dir):
            self.root_url = root_url
            self.model_url = model_url
            self.img_output_dir = img_output_dir
            self.headers = {
        
                'Referer': 'https://news.mit.edu/',
                'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
                              'Chrome/122.0.0.0 Safari/537.36',
                'Cookie': '替换成你自己的',
            }
    
            ...
    
    def run():
        root_url = 'https://news.mit.edu/'
        model_urls = ['https://news.mit.edu/topic', 'https://news.mit.edu/clp',
                      'https://news.mit.edu/department', 'https://news.mit.edu/']
        output_dir = 'D:\imgs\mit-news'
    
        for model_url in model_urls:
            scraper = MitnewsScraper(root_url, model_url, output_dir)
            scraper.catalogue_all_pages()

## 四、请求处理模块、版面、文章 ##

`先处理一个模块（TOPICS）`

### 1. 分析切换页面的参数传递 ###

如图可知是get请求,需要传一个参数page

![在这里插入图片描述][18ec989a723d448cbb5c92feb84b2be9.png]

### 2. 获取共有多少页标签并遍历版面 ###

实际上是获取所有的page参数，然后进行遍历获取所有的标签

![在这里插入图片描述][2bbea76d9c5648c2a428c099e2591086.png]

# 获取一个模块有多少版面
        def catalogue_all_pages(self):
            response = requests.get(self.model_url, headers=self.headers)
            soup = BeautifulSoup(response.text, 'html.parser')
            try:
                match = re.search(r'of (\d+) topics', soup.text)
                total_catalogues = int(match.group(1))
                total_pages = math.ceil(total_catalogues / 20)
                print('topics模块一共有' + match.group(1) + '个版面,' + str(total_pages) + '页数据')
                for page in range(0, total_pages):
                    self.parse_catalogues(page)
                    print(f"========Finished catalogues page {
          page + 1}========")
            except:
                self.parse_catalogues(0)

### 3.解析版面并保存版面信息 ###

前三个模块的版面列表

![在这里插入图片描述][c74fd12556af49c7b03797cac1583f67.png]

第四个模块的版面列表

![在这里插入图片描述][73c27c9b986e470fae47cf40dbb6a9f6.png]

# 解析版面列表里的版面
        def parse_catalogues(self, page):
            params = {
        'page': page}
            response = requests.get(self.model_url, params=params, headers=self.headers)
            if response.status_code == 200:
                soup = BeautifulSoup(response.text, 'html.parser')
                if self.root_url == self.model_url:
                    catalogue_list = soup.find('div',
                                               'site-browse--recommended-section site-browse--recommended-section--schools')
                    catalogues_list = catalogue_list.find_all('li')
                else:
                    catalogue_list = soup.find('ul', 'page-vocabulary--views--list')
                    catalogues_list = catalogue_list.find_all('li')
    
                for index, catalogue in enumerate(catalogues_list):
                    # 操作时间
                    date = datetime.now()
                    # 版面标题
                    catalogue_title = catalogue.find('a').get_text(strip=True)
                    print('第' + str(index + 1) + '个版面标题为:' + catalogue_title)
    
                    catalogue_href = catalogue.find('a').get('href')
                    # 版面id
                    catalogue_id = catalogue_href[1:]
                    catalogue_url = self.root_url + catalogue_href
                    print('第' + str(index + 1) + '个版面地址为:' + catalogue_url)
    
                    # 根据版面url解析文章列表
                    response = requests.get(catalogue_url, headers=self.headers)
                    soup = BeautifulSoup(response.text, 'html.parser')
                    match = re.search(r'of (\d+)', soup.text)
                    # 查找一个版面有多少篇文章
                    total_cards = int(match.group(1))
                    total_pages = math.ceil(total_cards / 15)
                    print(f'{
          catalogue_title}版面一共有{
          total_cards}篇文章,' + f'{
          total_pages}页数据')
                    for page in range(0, total_pages):
                        self.parse_cards_list(page, catalogue_url, catalogue_id)
                        print(f"========Finished {
          catalogue_title} 版面 page {
          page + 1}========")
    
                    # 连接 MongoDB 数据库服务器
                    client = MongoClient('mongodb://localhost:27017/')
                    # 创建或选择数据库
                    db = client['mit-news']
                    # 创建或选择集合
                    catalogues_collection = db['catalogues']
                    # 插入示例数据到 catalogues 集合
                    catalogue_data = {
        
                        'id': catalogue_id,
                        'date': date,
                        'title': catalogue_title,
                        'url': catalogue_url,
                        'cardSize': total_cards
                    }
                    catalogues_collection.insert_one(catalogue_data)
                return True
            else:
                raise Exception(f"Failed to fetch page {
          page}. Status code: {
          response.status_code}")

### 4. 解析文章列表和文章 ###

![在这里插入图片描述][3b74ffb3ebf6440db67554c66f41a307.png]  
![在这里插入图片描述][e0bab2825e194aa7acc4b5e54d37adae.png]  
寻找冗余部分并删除，例如

![在这里插入图片描述][52bc8b38880c4c76aa85e6c294a050ac.png]

# 解析文章列表里的文章
        def parse_cards_list(self, page, url, catalogue_id):
            params = {
        'page': page}
            response = requests.get(url, params=params, headers=self.headers)
            if response.status_code == 200:
                soup = BeautifulSoup(response.text, 'html.parser')
                card_list = soup.find('div', 'page-term--views--list')
                cards_list = card_list.find_all('div', 'page-term--views--list-item')
                for index, card in enumerate(cards_list):
                    # 对应的版面id
                    catalogue_id = catalogue_id
                    # 操作时间
                    date = datetime.now()
                    # 文章标题
                    card_title = card.find('a', 'term-page--news-article--item--title--link').find('span').get_text(
                        strip=True)
    
                    # 文章简介
                    card_introduction = card.find('p', 'term-page--news-article--item--dek').find('span').get_text(
                        strip=True)
                    # 文章更新时间
                    publish_time = card.find('p', 'term-page--news-article--item--publication-date').find('time').get(
                        'datetime')
                    updateTime = datetime.strptime(publish_time, '%Y-%m-%dT%H:%M:%SZ')
                    # 文章地址
                    temp_url = card.find('div', 'term-page--news-article--item--cover-image').find('a').get('href')
                    url = 'https://news.mit.edu' + temp_url
                    # 文章id
                    pattern = r'(\w+(-\w+)*)-(\d+)'
                    match = re.search(pattern, temp_url)
                    card_id = str(match.group(0))
                    card_response = requests.get(url, headers=self.headers)
                    soup = BeautifulSoup(card_response.text, 'html.parser')
                    # 原始htmldom结构
                    html_title = soup.find('div', id='block-mit-page-title')
                    html_content = soup.find('div', id='block-mit-content')
    
                    # 合并标题和内容
                    html_title.append(html_content)
                    html_cut1 = soup.find('div', 'news-article--topics')
                    html_cut2 = soup.find('div', 'news-article--archives')
                    html_cut3 = soup.find('div', 'news-article--content--side-column')
                    html_cut4 = soup.find('div', 'news-article--press-inquiries')
                    html_cut5 = soup.find_all('div', 'visually-hidden')
                    html_cut6 = soup.find('p', 'news-article--images-gallery--nav--inner')
    
                    # 移除元素
                    if html_cut1:
                        html_cut1.extract()
                    if html_cut2:
                        html_cut2.extract()
                    if html_cut3:
                        html_cut3.extract()
                    if html_cut4:
                        html_cut4.extract()
                    if html_cut5:
                        for item in html_cut5:
                            item.extract()
                    if html_cut6:
                        html_cut6.extract()
                    # 获取合并后的内容文本
                    html_content = html_title
                    # 文章作者
                    author_list = html_content.find('div', 'news-article--authored-by').find_all('span')
                    author = ''
                    for item in author_list:
                        author = author + item.get_text()
                    # 增加保留html样式的源文本
                    origin_html = html_content.prettify()  # String
                    # 转义网页中的图片标签
                    str_html = self.transcoding_tags(origin_html)
                    # 再包装成
                    temp_soup = BeautifulSoup(str_html, 'html.parser')
                    # 反转译文件中的插图
                    str_html = self.translate_tags(temp_soup.text)
                    # 绑定更新内容
                    content = self.clean_content(str_html)
                    # 下载图片
                    imgs = []
                    img_array = soup.find_all('div', 'news-article--image-item')
                    for item in img_array:
                        img_url = self.root_url + item.find('img').get('data-src')
                        imgs.append(img_url)
                    if len(imgs) != 0:
                        # 下载图片
                        illustrations = self.download_images(imgs, card_id)
                    # 连接 MongoDB 数据库服务器
                    client = MongoClient('mongodb://localhost:27017/')
                    # 创建或选择数据库
                    db = client['mit-news']
                    # 创建或选择集合
                    cards_collection = db['cards']
                    # 插入示例数据到 catalogues 集合
                    card_data = {
        
                        'id': card_id,
                        'catalogueId': catalogue_id,
                        'type': 'mit-news',
                        'date': date,
                        'title': card_title,
                        'author': author,
                        'card_introduction': card_introduction,
                        'updatetime': updateTime,
                        'url': url,
                        'html_content': str(html_content),
                        'content': content,
                        'illustrations': illustrations,
                    }
                    cards_collection.insert_one(card_data)
    
                return True
            else:
                raise Exception(f"Failed to fetch page {
          page}. Status code: {
          response.status_code}")

### 5. 清洗文章 ###

# 工具 转义标签
        def transcoding_tags(self, htmlstr):
            re_img = re.compile(r'\s*<(img.*?)>\s*', re.M)
            s = re_img.sub(r'\n @@##\1##@@ \n', htmlstr)  # IMG 转义
            return s
    
        # 工具 转义标签
        def translate_tags(self, htmlstr):
            re_img = re.compile(r'@@##(img.*?)##@@', re.M)
            s = re_img.sub(r'<\1>', htmlstr)  # IMG 转义
            return s
    
        # 清洗文章
        def clean_content(self, content):
            if content is not None:
                content = re.sub(r'\r', r'\n', content)
                content = re.sub(r'\n{2,}', '', content)
                content = re.sub(r' {6,}', '', content)
                content = re.sub(r' {3,}\n', '', content)
                content = re.sub(r'<img src="../../../image/zxbl.gif"/>', '', content)
                content = content.replace(
                    '<img border="0" src="****处理标记：[Article]时， 字段 [SnapUrl] 在数据源中没有找到! ****"/> ', '')
                content = content.replace(
                    ''' <!--/enpcontent<INPUT type=checkbox value=0 name=titlecheckbox sourceid="<Source>SourcePh " style="display:none">''',
                    '') \
                    .replace(' <!--enpcontent', '').replace('<TABLE>', '')
                content = content.replace('<P>', '').replace('<\P>', '').replace(' ', ' ')
            return content

### 6. 保存文章图片 ###

# 下载图片
        def download_images(self, img_urls, card_id):
            # 根据card_id创建一个新的子目录
            images_dir = os.path.join(self.img_output_dir, card_id)
            if not os.path.exists(images_dir):
                os.makedirs(images_dir)
                downloaded_images = []
                for index, img_url in enumerate(img_urls):
                    try:
                        response = requests.get(img_url, stream=True, headers=self.headers)
                        if response.status_code == 200:
                            # 从URL中提取图片文件名
                            img_name_with_extension = img_url.split('/')[-1]
                            pattern = r'^[^?]*'
                            match = re.search(pattern, img_name_with_extension)
                            img_name = match.group(0)
    
                            # 保存图片
                            with open(os.path.join(images_dir, img_name), 'wb') as f:
                                f.write(response.content)
                            downloaded_images.append([img_url, os.path.join(images_dir, img_name)])
                    except requests.exceptions.RequestException as e:
                        print(f'请求图片时发生错误：{
          e}')
                    except Exception as e:
                        print(f'保存图片时发生错误：{
          e}')
                return downloaded_images
            # 如果文件夹存在则跳过
            else:
                print(f'文章id为{
          card_id}的图片文件夹已经存在')
                return []

## 五、完整代码 ##

import os
    from datetime import datetime
    import requests
    from bs4 import BeautifulSoup
    from pymongo import MongoClient
    import re
    import math
    
    class MitnewsScraper:
        def __init__(self, root_url, model_url, img_output_dir):
            self.root_url = root_url
            self.model_url = model_url
            self.img_output_dir = img_output_dir
            self.headers = {
        
                'Referer': 'https://news.mit.edu/',
                'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
                              'Chrome/122.0.0.0 Safari/537.36',
                'Cookie': '替换成你自己的'
            }
    
        # 获取一个模块有多少版面
        def catalogue_all_pages(self):
            response = requests.get(self.model_url, headers=self.headers)
            soup = BeautifulSoup(response.text, 'html.parser')
            try:
                match = re.search(r'of (\d+) topics', soup.text)
                total_catalogues = int(match.group(1))
                total_pages = math.ceil(total_catalogues / 20)
                print('topics模块一共有' + match.group(1) + '个版面,' + str(total_pages) + '页数据')
                for page in range(0, total_pages):
                    self.parse_catalogues(page)
                    print(f"========Finished catalogues page {
          page + 1}========")
            except:
                self.parse_catalogues(0)
    
        # 解析版面列表里的版面
        def parse_catalogues(self, page):
            params = {
        'page': page}
            response = requests.get(self.model_url, params=params, headers=self.headers)
            if response.status_code == 200:
                soup = BeautifulSoup(response.text, 'html.parser')
                if self.root_url == self.model_url:
                    catalogue_list = soup.find('div',
                                               'site-browse--recommended-section site-browse--recommended-section--schools')
                    catalogues_list = catalogue_list.find_all('li')
                else:
                    catalogue_list = soup.find('ul', 'page-vocabulary--views--list')
                    catalogues_list = catalogue_list.find_all('li')
    
                for index, catalogue in enumerate(catalogues_list):
                    # 操作时间
                    date = datetime.now()
                    # 版面标题
                    catalogue_title = catalogue.find('a').get_text(strip=True)
                    print('第' + str(index + 1) + '个版面标题为:' + catalogue_title)
    
                    catalogue_href = catalogue.find('a').get('href')
                    # 版面id
                    catalogue_id = catalogue_href[1:]
                    catalogue_url = self.root_url + catalogue_href
                    print('第' + str(index + 1) + '个版面地址为:' + catalogue_url)
    
                    # 根据版面url解析文章列表
                    response = requests.get(catalogue_url, headers=self.headers)
                    soup = BeautifulSoup(response.text, 'html.parser')
                    match = re.search(r'of (\d+)', soup.text)
                    # 查找一个版面有多少篇文章
                    total_cards = int(match.group(1))
                    total_pages = math.ceil(total_cards / 15)
                    print(f'{
          catalogue_title}版面一共有{
          total_cards}篇文章,' + f'{
          total_pages}页数据')
                    for page in range(0, total_pages):
                        self.parse_cards_list(page, catalogue_url, catalogue_id)
                        print(f"========Finished {
          catalogue_title} 版面 page {
          page + 1}========")
    
                    # 连接 MongoDB 数据库服务器
                    client = MongoClient('mongodb://localhost:27017/')
                    # 创建或选择数据库
                    db = client['mit-news']
                    # 创建或选择集合
                    catalogues_collection = db['catalogues']
                    # 插入示例数据到 catalogues 集合
                    catalogue_data = {
        
                        'id': catalogue_id,
                        'date': date,
                        'title': catalogue_title,
                        'url': catalogue_url,
                        'cardSize': total_cards
                    }
                    catalogues_collection.insert_one(catalogue_data)
                return True
            else:
                raise Exception(f"Failed to fetch page {
          page}. Status code: {
          response.status_code}")
    
        # 解析文章列表里的文章
        def parse_cards_list(self, page, url, catalogue_id):
            params = {
        'page': page}
            response = requests.get(url, params=params, headers=self.headers)
            if response.status_code == 200:
                soup = BeautifulSoup(response.text, 'html.parser')
                card_list = soup.find('div', 'page-term--views--list')
                cards_list = card_list.find_all('div', 'page-term--views--list-item')
                for index, card in enumerate(cards_list):
                    # 对应的版面id
                    catalogue_id = catalogue_id
                    # 操作时间
                    date = datetime.now()
                    # 文章标题
                    card_title = card.find('a', 'term-page--news-article--item--title--link').find('span').get_text(
                        strip=True)
    
                    # 文章简介
                    card_introduction = card.find('p', 'term-page--news-article--item--dek').find('span').get_text(
                        strip=True)
                    # 文章更新时间
                    publish_time = card.find('p', 'term-page--news-article--item--publication-date').find('time').get(
                        'datetime')
                    updateTime = datetime.strptime(publish_time, '%Y-%m-%dT%H:%M:%SZ')
                    # 文章地址
                    temp_url = card.find('div', 'term-page--news-article--item--cover-image').find('a').get('href')
                    url = 'https://news.mit.edu' + temp_url
                    # 文章id
                    pattern = r'(\w+(-\w+)*)-(\d+)'
                    match = re.search(pattern, temp_url)
                    card_id = str(match.group(0))
                    card_response = requests.get(url, headers=self.headers)
                    soup = BeautifulSoup(card_response.text, 'html.parser')
                    # 原始htmldom结构
                    html_title = soup.find('div', id='block-mit-page-title')
                    html_content = soup.find('div', id='block-mit-content')
    
                    # 合并标题和内容
                    html_title.append(html_content)
                    html_cut1 = soup.find('div', 'news-article--topics')
                    html_cut2 = soup.find('div', 'news-article--archives')
                    html_cut3 = soup.find('div', 'news-article--content--side-column')
                    html_cut4 = soup.find('div', 'news-article--press-inquiries')
                    html_cut5 = soup.find_all('div', 'visually-hidden')
                    html_cut6 = soup.find('p', 'news-article--images-gallery--nav--inner')
    
                    # 移除元素
                    if html_cut1:
                        html_cut1.extract()
                    if html_cut2:
                        html_cut2.extract()
                    if html_cut3:
                        html_cut3.extract()
                    if html_cut4:
                        html_cut4.extract()
                    if html_cut5:
                        for item in html_cut5:
                            item.extract()
                    if html_cut6:
                        html_cut6.extract()
                    # 获取合并后的内容文本
                    html_content = html_title
                    # 文章作者
                    author_list = html_content.find('div', 'news-article--authored-by').find_all('span')
                    author = ''
                    for item in author_list:
                        author = author + item.get_text()
                    # 增加保留html样式的源文本
                    origin_html = html_content.prettify()  # String
                    # 转义网页中的图片标签
                    str_html = self.transcoding_tags(origin_html)
                    # 再包装成
                    temp_soup = BeautifulSoup(str_html, 'html.parser')
                    # 反转译文件中的插图
                    str_html = self.translate_tags(temp_soup.text)
                    # 绑定更新内容
                    content = self.clean_content(str_html)
                    # 下载图片
                    imgs = []
                    img_array = soup.find_all('div', 'news-article--image-item')
                    for item in img_array:
                        img_url = self.root_url + item.find('img').get('data-src')
                        imgs.append(img_url)
                    if len(imgs) != 0:
                        # 下载图片
                        illustrations = self.download_images(imgs, card_id)
                    # 连接 MongoDB 数据库服务器
                    client = MongoClient('mongodb://localhost:27017/')
                    # 创建或选择数据库
                    db = client['mit-news']
                    # 创建或选择集合
                    cards_collection = db['cards']
                    # 插入示例数据到 catalogues 集合
                    card_data = {
        
                        'id': card_id,
                        'catalogueId': catalogue_id,
                        'type': 'mit-news',
                        'date': date,
                        'title': card_title,
                        'author': author,
                        'card_introduction': card_introduction,
                        'updatetime': updateTime,
                        'url': url,
                        'html_content': str(html_content),
                        'content': content,
                        'illustrations': illustrations,
                    }
                    cards_collection.insert_one(card_data)
    
                return True
            else:
                raise Exception(f"Failed to fetch page {
          page}. Status code: {
          response.status_code}")
    
        # 下载图片
        def download_images(self, img_urls, card_id):
            # 根据card_id创建一个新的子目录
            images_dir = os.path.join(self.img_output_dir, card_id)
            if not os.path.exists(images_dir):
                os.makedirs(images_dir)
                downloaded_images = []
                for index, img_url in enumerate(img_urls):
                    try:
                        response = requests.get(img_url, stream=True, headers=self.headers)
                        if response.status_code == 200:
                            # 从URL中提取图片文件名
                            img_name_with_extension = img_url.split('/')[-1]
                            pattern = r'^[^?]*'
                            match = re.search(pattern, img_name_with_extension)
                            img_name = match.group(0)
    
                            # 保存图片
                            with open(os.path.join(images_dir, img_name), 'wb') as f:
                                f.write(response.content)
                            downloaded_images.append([img_url, os.path.join(images_dir, img_name)])
                    except requests.exceptions.RequestException as e:
                        print(f'请求图片时发生错误：{
          e}')
                    except Exception as e:
                        print(f'保存图片时发生错误：{
          e}')
                return downloaded_images
            # 如果文件夹存在则跳过
            else:
                print(f'文章id为{
          card_id}的图片文件夹已经存在')
                return []
    
        # 工具 转义标签
        def transcoding_tags(self, htmlstr):
            re_img = re.compile(r'\s*<(img.*?)>\s*', re.M)
            s = re_img.sub(r'\n @@##\1##@@ \n', htmlstr)  # IMG 转义
            return s
    
        # 工具 转义标签
        def translate_tags(self, htmlstr):
            re_img = re.compile(r'@@##(img.*?)##@@', re.M)
            s = re_img.sub(r'<\1>', htmlstr)  # IMG 转义
            return s
    
        # 清洗文章
        def clean_content(self, content):
            if content is not None:
                content = re.sub(r'\r', r'\n', content)
                content = re.sub(r'\n{2,}', '', content)
                content = re.sub(r' {6,}', '', content)
                content = re.sub(r' {3,}\n', '', content)
                content = re.sub(r'<img src="../../../image/zxbl.gif"/>', '', content)
                content = content.replace(
                    '<img border="0" src="****处理标记：[Article]时， 字段 [SnapUrl] 在数据源中没有找到! ****"/> ', '')
                content = content.replace(
                    ''' <!--/enpcontent<INPUT type=checkbox value=0 name=titlecheckbox sourceid="<Source>SourcePh " style="display:none">''',
                    '') \
                    .replace(' <!--enpcontent', '').replace('<TABLE>', '')
                content = content.replace('<P>', '').replace('<\P>', '').replace(' ', ' ')
            return content
    
    def run():
        root_url = 'https://news.mit.edu/'
        model_urls = ['https://news.mit.edu/topic', 'https://news.mit.edu/clp',
                      'https://news.mit.edu/department', 'https://news.mit.edu/']
        output_dir = 'D:\imgs\mit-news'
    
        for model_url in model_urls:
            scraper = MitnewsScraper(root_url, model_url, output_dir)
            scraper.catalogue_all_pages()
    
    if __name__ == "__main__":
        run()

## 六、效果展示 ##

![在这里插入图片描述][a6ea2d60ecca40a8a1ef191fa08a0caf.png]  
![在这里插入图片描述][6819c5afd3a44f689c7a370ec4876da0.png]

![在这里插入图片描述][a10a76a70d80440fb8356aa81be4b561.png]  
![在这里插入图片描述][217f757e66054b44a34392b107bcfb5d.png]

[Link 1]: https://www.captainbed.cn/dl
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[c74fd12556af49c7b03797cac1583f67.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/06/10dddddd3b0d4f10a609c122e99531ec.png
[73c27c9b986e470fae47cf40dbb6a9f6.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/06/962f2139e543452e8ac51ce6a8a9447f.png
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[217f757e66054b44a34392b107bcfb5d.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/06/bb48acd4cb3546b78e8e9081ec59df36.png