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polhntkjb 2 months ago
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commit 6b10f071b6
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t1.py
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import requests
import re
from bs4 import BeautifulSoup
from collections import Counter
from openpyxl import load_workbook
import pandas as pd
import jieba
import wordcloud
import imageio
# 模拟浏览器
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36 Edg/128.0.0.0",
"cookie": "CURRENT_FNVAL=4048; buvid_fp_plain=undefined; buvid4=04DF7AEF-34D9-CC62-690A-D369B35D458509591-023061415-%2FxwqHe8zHTWav6Q4ZiB1Ag%3D%3D; enable_web_push=DISABLE; FEED_LIVE_VERSION=V_WATCHLATER_PIP_WINDOW3; PVID=1; buvid3=D5B12366-476E-6163-1D79-774D300DF97306537infoc; b_nut=1718270506; _uuid=243B710F9-1010E3-9654-E867-4A8D8BB10AB1307743infoc; header_theme_version=CLOSE; rpdid=0zbfAHMKHr|S8rGMSwG|1uI|3w1Sum1G; fingerprint=042b265e3c7da3104d09a0692278e922; CURRENT_QUALITY=80; home_feed_column=5; browser_resolution=1659-836; bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjU5NDEwOTEsImlhdCI6MTcyNTY4MTgzMSwicGx0IjotMX0.j7rN8z5QOwH-7R7gPvyBxJzDLqymAWFfZeFF-QAXoTQ; bili_ticket_expires=1725941031; bp_t_offset_482950113=974463371485118464; buvid_fp=042b265e3c7da3104d09a0692278e922; b_lsid=DDE103767_191D4FCA152"
}
def contains_ai_or_artificial_intelligence(text):
ai_pattern = re.compile( r'(\bai\b|人工智能|([\u4e00-\u9fff]|\s|^)ai([\u4e00-\u9fff]|\s|$))', re.IGNORECASE)
return re.search(ai_pattern, text)
# 获取html文本
def get_html(url):
response = requests.get(url,headers=headers)
response.encoding = 'utf-8'
html=response.text
return html
# 查找正确的api链接
def seek_api_urls(html_data):
soup = BeautifulSoup(html_data, 'html.parser')
#创建列表储存筛选完的内容
urls = set()
# 筛选a标签内容
a_tags=soup.find_all('a', href=True)
for a_link in a_tags:
# 获取href的值
link = a_link['href']
urls.add(link)
# 筛选正确的链接
pattern = re.compile(r'https://api\.bilibili\.com/x/v1/dm/list\.so\?')
api_urls = [url_find for url_find in urls if pattern.match(url_find)]
#返回链接值
return api_urls
# 获取弹幕接口链接函数
def get_api_urls(url):
response = requests.get(url, headers=headers)
if response.status_code == 200:
# 若请求成功则查找api链接
html_data=response.text
api_urls=seek_api_urls(html_data)
return api_urls
else:
# 返回一个空列表作为默认值
return []
# 获取视频接口函数
def get_urls(page):
# 获得搜索页面url
url = f"https://search.bilibili.com/video?keyword=%E5%B7%B4%E9%BB%8E%E5%A5%A5%E8%BF%90%E4%BC%9A&from_source=webtop_search&spm_id_from=333.1007&search_source=2&page={page}"
html_data=get_html(url)
soup = BeautifulSoup(html_data, 'html.parser')
# 创建列表储存筛选完的内容
urls = set()
a_tags=soup.find_all('a', href=True)
for a_link in a_tags:
link = a_link['href']
# 补全链接
full_link=f'https:{link}'
urls.add(full_link)
# 筛选正确的链接
pattern = re.compile(r'https://www\.bilibili\.com/video')
#7x42=294，前七页全部读取
if page != 8:
vedieo_urls_f = [url_find for url_find in urls if pattern.match(url_find)]
return vedieo_urls_f
#第8页只读6个
else: vedieo_urls_f = []
num = 0
for url_find in urls:
if pattern.match(url_find):
num = num + 1
vedieo_urls_f.append(url_find)
if num == 6:
return vedieo_urls_f
#获取接口链接
def vedio_transform_port(url):
html_data = get_html(url)
soup = BeautifulSoup(html_data,"html.parser")
page_num = [] #储存总共的分p数
span_tag = None #用做判断有无分p的flag
# 分p视频部分源代码如下：
# <div class="head-left">
# <h3>视频选集</h3>
# <span class="cur-page">(1/12)</span>
div_tags = soup.findAll("div",attrs={"class":"head-left"}) #找到class=head-left的div
for tag in div_tags:
span_tag=(tag.findAll("span",attrs={"class":"cur-page"})) #再从中找到class=cur-page的span
if span_tag == None: #值为None则为单个视频
port_url = url.replace("bilibili.com", "ibilibili.com")
port_urls.add(port_url)
else:
for page in span_tag:
pages = jieba.lcut(page.get_text()) #取得span的内容“（x/y)"，用jieba拆分成'(','x','/','y',')',其中y即为分p总数
page_num = pages[3] #取得y的值
# 替换每个分p视频的链接
for page in range(1,int(page_num)+1):
port_url = f"{url}?p={page}"
port_urls.add(port_url.replace("bilibili.com", "ibilibili.com"))
# 循环10页，每页42个视频，总300个
for page in range(1,8):
# 获取视频链接
vedio_urls=get_urls(page)
# 创建接口链接列表
port_urls=set()
for vedio_url in vedio_urls:
# 将视频链接转换成接口链接
port_url = vedio_transform_port(vedio_url)
# 循环访问接口
for url in port_urls:
#获取弹幕链接
api_urls=get_api_urls(url)
# 检查列表是否为空
if api_urls:
#不为空，则将获取弹幕链接
api_url = api_urls[0]
html_data = get_html(api_url)
soup = BeautifulSoup(html_data, 'html.parser')
content_list =re.findall('<d p=".*?">(.*?)</d>',html_data)
content='\n'.join(content_list)
with open('弹幕.txt',mode='a',encoding='utf-8') as f:
f.write(content)
ai_list = [] #用于储存关于ai弹幕
most_common_barrages = [] #储存数量前八弹幕
with open('弹幕.txt', 'r', encoding='utf-8') as file:
content_txt = file.readlines() # 按行读取弹幕
for barrage in content_txt:
if contains_ai_or_artificial_intelligence(barrage): #筛选关于ai的弹幕
ai_list.append(barrage.strip()) # 使用strip()去除每行的换行符
# 使用Counter统计每个弹幕的出现次数
counter = Counter(ai_list)
# 获取出现次数最多的前8个弹幕
most_common_barrages = counter.most_common(8)
#转变类型才可以写入excel
ai_list1 = counter.most_common()
# 输出结果
for barrage, count in most_common_barrages:
print(f'弹幕: {barrage} 出现次数: {count}')
# 将数据转换为DataFrame
df = pd.DataFrame(ai_list1, columns=['弹幕', '出现次数'])
# 写入Excel文件
excel_path = '弹幕统计.xlsx'
df.to_excel(excel_path, index=False, engine='openpyxl')
# 调整列宽
wb = load_workbook(excel_path)
ws = wb.active
# 设置“弹幕”列的宽度
ws.column_dimensions['A'].width = 60
# 保存修改后的Excel文件
wb.save(excel_path)
ai_str = '\n'.join(ai_list) #分割成字符型
#绘制词云图
img = imageio.imread('test2.png')
wc = wordcloud.WordCloud(
width = 500,
height = 500,
mask=img,
background_color = 'white',
font_path = 'msyh.ttc'
)
wc.generate(ai_str)
wc.to_file('词云.png')
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