0.前言

最近爱情公寓上线了大电影，卖的就是情怀，但是据说豆瓣上已经给出了2.7的评分，也就比第一烂片逐梦演艺圈高那么一点点，于是今天写了一个爬虫，爬了豆瓣一千多条短评，看一看这个电影为什么这么渣。

1.代码

废话不说，直接代码，因为还是挺简单的

from lxml import etree
from urllib import request
import ssl
from jieba import analyse
import jieba
from wordcloud import WordCloud, STOPWORDS
from matplotlib import pyplot as plt//得到所有短评
def get_comments(comments):print(comments)root = etree.HTML(comments)comment_content = ''comment_list = root.xpath('//*[@class="short-content"]/text()')print('comment size is %d' % len(comment_list))for comment in comment_list:comment_content += commentcomment_content = comment_content.replace('()', '')print("comment_content is %s" % comment_content)return comment_content//生成词云
def generate_wordcloud(comments):stopwords = set(STOPWORDS)stopwords.add('爱情')stopwords.add('公寓')stopwords.add('电影')stopwords.add('评分')stopwords.add('...')comments = jieba.cut(comments)comments = [comment for comment in comments if comment not in stopwords]comments = ' '.join(comments)comments = str(analyse.extract_tags(comments, topK=300))background = plt.imread('pic.jpg')wc = WordCloud(font_path='msyh.ttf', random_state=30, width=800, height=800,mask=background, background_color='white',max_font_size=80, max_words=2000)wc = wc.generate_from_text(comments)plt.imshow(wc)plt.axis('off')plt.show()//调用上面的方法生成词云
url = 'https://movie.douban.com/subject/24852545/reviews?start=%d'
ssl._create_default_https_context = ssl._create_unverified_context
comments = ''
for i in range(0, 20):offset_url = url % (20 * i)print("url is %s" % offset_url)with request.urlopen(offset_url) as f:content = f.read()comment = get_comments(content)comments += comment
generate_wordcloud(comments)复制代码

2.结果

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