一、起因：
昨天在简书上看到这么一篇文章，看完之后个人是比较认同作者的观点。
不过，翻了下评论，发现评论区争议颇大，基本两极化。好奇，想看看整体的评论是个什么样，就写个爬虫，做了词云。
二、怎么做：
① 观察页面，找到获取评论的请求，查看评论数据样式，写爬虫
② 用 jieba 模块，将爬取的评论做分词处理
③ 用 wordcloud 模块，生成词云
三、代码如下：
#!/usr/bin/env python3# -*- coding: utf-8 -*-import requests,json,timeimport jiebaimport matplotlib.pyplot as pltfrom bs4 import BeautifulSoupfrom wordcloud import WordCloud,STOPWORDS,ImageColorGenerator# 存储爬取结果def write(path,text): with open(path,'a', encoding='utf-8') as f: f.writelines(text) f.write('\n')# 爬取评论def getcomments(num,path): url = 'https://www.jianshu.com/notes/23437010/comments?comment_id=&author_only=false&since_id=0&max_id=1586510606000&order_by=likes_count&page='+str(num) response = requests.get(url).text response = json.loads(response) num = response['total_pages'] for i in response['comments']: comment = BeautifulSoup(i['compiled_content'],'lxml').text write(path,comment) return num# jieba 分词def read(path): text='' with open(path, encoding='utf-8') as s: for line in s.readlines(): line.strip() text += ' '.join(jieba.cut(line)) return text# WordCloud 生成词云def wordcloud(imagepath): backgroud_Image = plt.imread(imagepath) wc = WordCloud(background_color='white', # 设置背景颜色 mask=backgroud_Image, # 设置背景图片 max_words=2000, # 设置最大现实的字数 stopwords=STOPWORDS, # 设置停用词 font_path='C:/Users/Windows/fonts/msyh.ttf', # 设置字体格式，如不设置显示不了中文 max_font_size=120, # 设置字体最大值 random_state=30, # 设置有多少种随机生成状态，即有多少种配色方案 ) wc.generate(text) image_colors = ImageColorGenerator(backgroud_Image) wc.recolor(color_func=image_colors) plt.imshow(wc) plt.axis('off') plt.show()if __name__ == '__main__': path = '评论.txt' # 评论path imagepath = 'heart.jpg' #词云背景图path print('正在爬取评论') i,num=1,2 while i <= num: num=getcomments(i,path) # 爬取评论 time.sleep(2) i += 1 print('正在分词处理') text = read(path) # jieba 分词处理 print('正在生成词云') wordcloud(imagepath) # WordCloud 生成词云 print('词云生成成功') 效果：
