《我不是药神》影评，逐页评论自动生成词云

注意事项：

import requests from bs4 import BeautifulSoup import time import jieba from wordcloud import WordCloud from PIL import Image import numpy as np import matplotlib.pyplot as plt import re def getHtml(url): try: r = requests.get(url,headers={'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36 QIHU 360EE'}, cookies={'cookie':'1012'}) r.raise_for_status() r.encoding = "utf-8" return r.text except: print("到此为止。原因豆瓣不登录用户只能访问到影评的前12页的数据， 登录后的用户可以看到前24页的数据（豆瓣影评数据只展示24页") def getData(html): f = open("new.txt",'wb+') soup = BeautifulSoup(html,"html.parser") comment_list = soup.find('div',attrs={'class':'mod-bd'}) for comment in comment_list.find_all('div',attrs={'class':'comment-item'}): comment_content = comment.find('span',attrs={'class':'short'}).get_text() f.write(comment_content.encode('utf-8')) def seg_sentence(): #实现句子的分词 final = '' fn1 = open("new.txt", 'r',encoding='utf-8').read() #加载爬取的内容 for k in range(len(fn1)): final+=str(fn1[k]).strip() filtrate= re.compile(r'[u4e00-u9fa5]') filterdata = re.findall(filtrate, final) newtxt=''.join(filterdata) #print(newtxt) fn2 = open("new.txt", "w", encoding='utf-8') fn2.write(newtxt) def wordcloud(m): # 加载图片 image = Image.open('fbb'+str(m)+'.png', 'r') img = np.array(image) # 词云 cut = open('new.txt', 'r',encoding='utf-8') cut_txt=cut.read() cut.close() newtxtls = jieba.lcut(cut_txt) txtls=[] for i in range(len(newtxtls)): if len(newtxtls[i])!=1: txtls.append(newtxtls[i]) continue newtxt=' '.join(txtls) #print(newtxt) wordcloud = WordCloud( mask=img, # 使用该参数自动忽略height,width background_color='white', max_words=500, # 设置最大词数 max_font_size=40, font_path="simhei.ttf").generate(newtxt) # 显示图片 plt.imshow(wordcloud, interpolation='bilinear') plt.axis('off') # 去掉坐标轴 plt.show() #直接显示 wordcloud .to_file('wc'+str(m)+'.png') #存为图片 plt.axis("off") def main(): k = 0 #start = k i = 0 while k <300: url = 'https://movie.douban.com/subject/26752088/comments?start=' + str(k) + '&limit=20&sort=new_score&status=P' k += 20 i += 1 print("正在爬取第" + str(i) + "页的数据") time.sleep(1) # 设置睡眠时间 html = getHtml(url) getData(html) seg_sentence() wordcloud(i) if __name__ == "__main__": main()