python和工程数学俩实验真累啊
python学习：
import re
from collections import Counter
import requests
from lxml import etree
import pandas as pd
import jieba
import matplotlib.pyplot as plt
from wordcloud import WordCloud
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.54 Safari/537.36 Edg/101.0.1210.39"}
comments = []
words = []
def regex_change(line):
# 前缀的正则 username_regex = re.compile(r"^\\d+::") # URL，为了防止对中文的过滤，所以使用\[a-zA-Z0-9\]而不是\\w url_regex = re.compile(r""" (https?://)? (\[a-zA-Z0-9\]+) (\\.\[a-zA-Z0-9\]+) (\\.\[a-zA-Z0-9\]+)\* (/\[a-zA-Z0-9\]+)\* """, re.VERBOSE | re.IGNORECASE) # 剔除日期 data_regex = re.compile(u""" #utf-8编码 年 | 月 | 日 | (周一) | (周二) | (周三) | (周四) | (周五) | (周六) """, re.VERBOSE) # 剔除所有数字 decimal_regex = re.compile(r"\[^a-zA-Z\]\\d+") # 剔除空格 space_regex = re.compile(r"\\s+") regEx = "\[\\n”“|,，；;''/?! 。的了是\]" # 去除字符串中的换行符、中文冒号、|，需要去除什么字符就在里面写什么字符 line = re.sub(regEx, "", line) line = username_regex.sub(r"", line) line = url_regex.sub(r"", line) line = data_regex.sub(r"", line) line = decimal_regex.sub(r"", line) line = space_regex.sub(r"", line) return linedef getComments(url):
score = 0 resp = requests.get(url, headers=headers).text html = etree.HTML(resp) comment_list = html.xpath(".//div\[@class='comment'\]") for comment in comment_list: status = "" name = comment.xpath(".//span\[@class='comment-info'\]/a/text()")\[0\] # 用户名 content = comment.xpath(".//p\[@class='comment-content'\]/span\[@class='short'\]/text()")\[0\] # 短评内容 content = str(content).strip() word = jieba.cut(content, cut_all=False, HMM=False) time = comment.xpath(".//span\[@class='comment-info'\]/a/text()")\[1\] # 评论时间 mark = comment.xpath(".//span\[@class='comment-info'\]/span/@title") # 评分 if len(mark) == 0: score = 0 else: for i in mark: status = str(i) if status == "力荐": score = 5 elif status == "推荐": score = 4 elif status == "还行": score = 3 elif status == "较差": score = 2 elif status == "很差": score = 1 good = comment.xpath(".//span\[@class='comment-vote'\]/span\[@class='vote-count'\]/text()")\[0\] # 点赞数（有用数） comments.append(\[str(name), content, str(time), score, int(good)\]) for i in word: if len(regex_change(i)) >= 2: words.append(regex_change(i))def getWordCloud(words):
# 生成词云 all_words = \[\] all_words += \[word for word in words\] dict_words = dict(Counter(all_words)) bow_words = sorted(dict_words.items(), key=lambda d: d\[1\], reverse=True) print("热词前10位：") for i in range(10): print(bow_words\[i\]) text = ' '.join(words) w = WordCloud(background_color='white', width=1000, height=700, font_path='simhei.ttf', margin=10).generate(text) plt.show() plt.imshow(w) w.to_file('wordcloud.png')print("请选择以下选项:")
print(" 1.热门评论")
print(" 2.最新评论")
info = int(input())
print("前10位短评信息：")
title = ['用户名', '短评内容', '评论时间', '评分', '点赞数']
if info == 1:
comments = \[\] words = \[\] for i in range(0, 60, 20): url = "https://book.douban.com/subject/10517238/comments/?start={}&limit=20&status=P&sort=new_score".format( i) # 前3页短评信息（热门） getComments(url) df = pd.DataFrame(comments, columns=title) print(df.head(10)) print("点赞数前10位的短评信息：") df = df.sort_values(by='点赞数', ascending=False) print(df.head(10)) getWordCloud(words)elif info == 2:
comments = \[\] words=\[\] for i in range(0, 60, 20): url = "https://book.douban.com/subject/10517238/comments/?start={}&limit=20&status=P&sort=time".format( i) # 前3页短评信息（最新） getComments(url) df = pd.DataFrame(comments, columns=title) print(df.head(10)) print("点赞数前10位的短评信息：") df = df.sort_values(by='点赞数', ascending=False) print(df.head(10)) getWordCloud(words)