import requests import re import time from collections import Counter import pandas as pd from wordcloud import WordCloud import matplotlib.pyplot as plt query = "2024巴黎奥运会" headers = { "Cookie": "buvid3=F85083C9-B0B0-58EF-387E-9810D717FBD394717infoc; b_nut=1695630694; i-wanna-go-back=-1; b_ut=7; _uuid=4691069C1-57109-F951-5C2C-71061B15CAB9C93820infoc; buvid4=80C1A4DB-57B6-89F1-B7AB-7AE606C3BFB795506-023092516-b1nz50QSFWAVh9QAs1wBqg%3D%3D; DedeUserID=391260816; DedeUserID__ckMd5=874384c11cc311ca; hit-dyn-v2=1; rpdid=|(JlRYJ~Yk||0J'uYmlYJ|~mu; buvid_fp_plain=undefined; LIVE_BUVID=AUTO7816956505396915; is-2022-channel=1; enable_web_push=DISABLE; header_theme_version=CLOSE; FEED_LIVE_VERSION=V_WATCHLATER_PIP_WINDOW3; CURRENT_BLACKGAP=0; bp_video_offset_391260816=964407697698979840; CURRENT_FNVAL=4048; CURRENT_QUALITY=116; fingerprint=0caf6ff40a6d821a9253179cd16721cc; buvid_fp=daecdb2a27b0352be0af14099f69b721; bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjU1MDk5MzUsImlhdCI6MTcyNTI1MDY3NSwicGx0IjotMX0.uE2PcZgAdDTBtqyfu7qsT_GKqNMsmsvjtdKYmeQ0eno; bili_ticket_expires=1725509875; SESSDATA=d4e31c61%2C1740843740%2Cc4b21%2A91CjBgFJe4MbiVSvKl_Z-oJcHfxPNmwxIX4iMw7S41V1DMuuAhaahCmSK6_p-xsyPHvC8SVi13bXN4RE40V2NCeGYwNWhYclNJckNfaGx4SzZydk05aE56ajdkS2dzZUVRWG9YeE5jbXFVdXF1aTZWTmxQZnRjZXZYaHJLU1dleElsRVczZG4wQW9RIIEC; bili_jct=f25b09f990746c712d4ef672d19e2628; PVID=1; sid=84brlx1u; home_feed_column=5; browser_resolution=2048-1018; bp_t_offset_391260816=973171033005621248; b_lsid=54110E26A_191BB365E57", "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" } total_page = 10 cid_pattern = re.compile(r'"cid":(\d+)') total_cid_list = [] total_comment_dict = {} bvid_pattern = re.compile(r'bvid:"(.*?)"') def GetFirstBidUrl(): # 获取第一个视频的bid return "https://search.bilibili.com/all?vt=82099157&keyword=2024%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=5&page=2&o=36" def GetCid(): # 获取300个视频的 bvid for page in range(1, total_page + 1): if len(total_cid_list) >= 300: break print(f"Processing page {page}...\n", ) start = time.time() if page == 1: search_url = GetFirstBidUrl() else: search_url = f"https://search.bilibili.com/all?vt=82451961&keyword=2024%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=5&page={page}&o=36" respons = requests.get(search_url, headers=headers) current_bvid_list = bvid_pattern.findall(respons.text) end = time.time() print(f"获取bid用时{end - start}s\n") start = time.time() # 通过bvid获取300个视频的cid for index, bvid in enumerate(current_bvid_list): video_url = f"https://www.bilibili.com/video/{bvid}" respons = requests.get(video_url, headers=headers) current_cid = cid_pattern.search(respons.text).group(1) print(f"获取到第{len(total_cid_list) + 1}个cid:{current_cid}") total_cid_list.append(current_cid) if len(total_cid_list) >= 300: break # time.sleep(1) end = time.time() print(f"获取cid用时:{end - start}s\n") time.sleep(1) def Getdanmu(): # 遍历所有视频的 cid,获取对应弹幕 get_cid_index = 0 for cid in total_cid_list: get_cid_index += 1 print(f"正在获取第{get_cid_index}个视频的弹幕") DanMu_url = f"https://api.bilibili.com/x/v1/dm/list.so?oid={cid}" respons = requests.get(DanMu_url, headers=headers) respons.encoding = 'utf-8' current_danmu_list = re.findall('(.*?)', respons.text) current_comment_dict = {} # 将每条弹幕加入到总的弹幕列表中 for danmu in current_danmu_list: if danmu in current_comment_dict: current_comment_dict[danmu] += 1 else: current_comment_dict[danmu] = 1 for k, v in current_comment_dict.items(): if k in total_comment_dict: total_comment_dict[k] += v else: total_comment_dict[k] = v time.sleep(0.5) # 在得到的弹幕里筛选与ai相关的弹幕 def Sortdanmu(): ai_pattern1 = re.compile(r'ai[\u4e00-\u9fff]', re.IGNORECASE) ai_pattern2 = re.compile(r'[\u4e00-\u9fff]ai', re.IGNORECASE) ai_comment = {} for k, v in total_comment_dict.items(): if ai_pattern1.search(k) and 'aiden' not in k and 'Aiden' not in k: ai_comment[k] = v if ai_pattern2.search(k) and 'aiden' not in k and 'Adien' not in k: ai_comment[k] = v if '人工智能' in k: ai_comment[k] = v global sorted_comment_dict sorted_comment_dict = dict(sorted(ai_comment.items(), key=lambda x: x[1], reverse=True)) print(sorted_comment_dict) df = pd.DataFrame(list(sorted_comment_dict.items()), columns=['Comment', 'Count']) df.to_excel('comments.xlsx', index=False) def CreatWordCloud(): # 根据弹幕表格生成词云图 comment_text = ' '.join([((k + ' ') * v) for k, v in sorted_comment_dict.items()]) wordcloud = WordCloud( font_path='C:/Windows/Fonts/simsun.ttc', width=800, height=400, background_color='white', max_words=200, colormap='viridis' ).generate(comment_text) def main(): GetCid() Getdanmu() Sortdanmu() CreatWordCloud() if __name__ == "__main__": main()