from bs4 import BeautifulSoup import re import pandas as pd import jieba import requests import imageio import wordcloud from openpyxl import load_workbook from collections import Counter #获取User-Agent和cookie 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": "buvid3=0C047DB7-FB67-6565-B853-68B19196AEE053166infoc; buvid4=D2E32722-EB31-8B5B-8BC7-420F049CDE3657801-022071821-mG8+jYWtWHQ35A9yqIgZIA%3D%3D; buvid_fp=60e37bdf4fe67cde89d283db25adff46; _uuid=FCEA6C48-BB82-123A-61106-3F5410106BB410B03170infoc; b_nut=100; header_theme_version=CLOSE; enable_web_push=DISABLE; bsource=search_bing; CURRENT_FNVAL=4048; SESSDATA=aa6a6590%2C1742210524%2C7b1c4%2A92CjCxud8rqp6tuF7AYkzmJF0YS7_L4_80iMI3NuY5q-M7BEW3cf0_bVyhIcnZMJapP7YSVnJiQ2NVcTJZZ1ZIMFduRURJXzZXOWtaTTl2WnBFSHkwckM0UzdwY2xHMG9MNVl4c1pUSHlFaFJ4RnQ5WjY3ZHRtcm5qcDhNSVo3eXZORDczc0VlYlF3IIEC; bili_jct=5232d057d308c18c1419d19271a3b85e; DedeUserID=1576579979; DedeUserID__ckMd5=da7d6054e70acbba; home_feed_column=5; browser_resolution=1528-748; bp_t_offset_1576579979=978508367389523968; bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjY5MjQzMzUsImlhdCI6MTcyNjY2NTA3NSwicGx0IjotMX0.9m3fjjjWd1wCsWNsTPwS9afVCknRz7dWtL6JV0CTQgI; bili_ticket_expires=1726924275; b_lsid=E4323108A_19205503541; sid=4q83ttnl; rpdid=|(u))kkY|mmJ0J'u~kYYYmmml" } #检查文本是否包含“ai”和“人工智能”字样 #此函数用于检查 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 #该函数发送HTTP GET请求到指定URL,并返回网页的源码 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 #解析HTML数据,提取标签 def seek_api_urls(html_data): soup = BeautifulSoup(html_data, 'html.parser') urls = set() 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: html_data=response.text api_urls=seek_api_urls(html_data) return api_urls else: 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 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")) for page in range(1,8): vedio_urls=get_urls(page) port_urls=set() for vedio_url in vedio_urls: port_url = vedio_transform_port(vedio_url) for url in port_urls: api_urls=get_api_urls(url) if api_urls: api_url = api_urls[0] html_data = get_html(api_url) soup = BeautifulSoup(html_data, 'html.parser') content_list =re.findall('(.*?)',html_data) content='\n'.join(content_list) with open('弹幕.txt',mode='a',encoding='utf-8') as f: f.write(content) ai_list = [] most_common_barrages = [] with open('弹幕.txt', 'r', encoding='utf-8') as file: content_txt = file.readlines() for barrage in content_txt: if contains_ai_or_artificial_intelligence(barrage): ai_list.append(barrage.strip()) # 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}') 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') wb = load_workbook(excel_path) ws = wb.active ws.column_dimensions['A'].width = 60 wb.save(excel_path) ai_str = '\n'.join(ai_list) #分割成字符型