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： #
#

视频选集

# (1/12) 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('(.*?)',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')