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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 line

def 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)