From 58a8049fd39ff5cfad5d0077e936db8918e91d3d Mon Sep 17 00:00:00 2001
From: QMZ <1164250597@qq.com>
Date: Mon, 16 Sep 2024 16:34:18 +0800
Subject: [PATCH] =?UTF-8?q?demo=204.0=20=E5=AE=9E=E7=8E=B0=E5=9F=BA?=
 =?UTF-8?q?=E6=9C=AC=E5=8A=9F=E8=83=BD?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 demo.py | 49 ++++++++++++++++++++++++++++++++++++-------------
 1 file changed, 36 insertions(+), 13 deletions(-)

diff --git a/demo.py b/demo.py
index ece161a..ec97928 100644
--- a/demo.py
+++ b/demo.py
@@ -3,10 +3,12 @@ from bs4 import BeautifulSoup
 import re
 import time
 import random
-import jieba  # 结巴分词 pip install jieba
-import wordcloud  # 词云图 pip install wordcloud
-import imageio  # 读取本地图片 修改词云图形
+import jieba  
+import wordcloud  
 import matplotlib.pyplot as plt
+import pandas as pd  
+from pandas import ExcelWriter
+from collections import Counter
 headers = {
     'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36 Edg/127.0.0.0',
    
@@ -16,10 +18,6 @@ keywords = [
     '算法', '数据科学', '智能算法', '自然语言处理', '计算机视觉', 
     '智能机器人', '智能系统', '人工智能技术', 'AI技术', 'AI应用', 
     '智能设备', '智能分析', 'AI模型', '大数据', '预测分析', 
-    '模式识别', '语音识别', '图像识别', '机器人技术', '数据挖掘',
-    '智能决策', '虚拟助手', '增强现实', '计算智能', '自适应系统',
-    '智能网络', '知识图谱', '智能交互', 'AI解决方案', '计算机智能',
-    '自然语言生成', '深度神经网络', '强化学习', '迁移学习', '生成对抗网络',
     '智能预测', '智慧城市', '智能制造', '机器视觉', '自动驾驶',
     '智能传感器', '智能控制', '智能推荐', '计算机科学', '人工智能应用',
     '人工智能发展', 'AI伦理', '人工智能安全', '智能算法应用', '数据分析',
@@ -37,7 +35,6 @@ def get_search_page(search_url):
 def extract_video_links(page_content):
     soup = BeautifulSoup(page_content, 'html.parser')
     video_links = []
-    # 选择器根据实际网页结构可能需要调整
     for a_tag in soup.select(".video-list.row div.bili-video-card > div > a"):
         link = a_tag.get('href')
         video_links.append(link)
@@ -53,6 +50,7 @@ def extract__BV(video_urls):
             links.append(video_id_match.group(1))
     return links
 
+# 将视频BV号转为CID
 def get_cid_from_bv(bv_ids):
     cids=[]
     for bv_id in bv_ids:
@@ -68,7 +66,8 @@ def get_cid_from_bv(bv_ids):
             cid = data.get('data', {}).get('cid')
             cids.append(cid)
     return cids
-    
+
+#获取弹幕
 def get_danmu(id):
     global videosnumber
     video_url = f'https://api.bilibili.com/x/v1/dm/list.so?oid={id}'
@@ -86,11 +85,13 @@ def get_danmu(id):
     time.sleep(random.randint(0,2)+random.random())
     return(txtsss) ###打印便可看见一条条弹幕的属性和内容了。
 
+#翻页
 def page(url,num):
     num=num+1
     url=f'https://search.bilibili.com/video?keyword=2024巴黎奥运会&page={num}'
     return url
 
+#处理弹幕
 def chuli(alltxt):
     danmustr=''.join(i for i in alltxt) #将所有弹幕拼接在一起
     words=list(jieba.cut(danmustr))  ###利用jieba库将弹幕按词进行切分
@@ -101,11 +102,29 @@ def chuli(alltxt):
     plt.imshow(wc)
     plt.show()
 
+def sort(txt, keywords):
+    
+    comment_counter = Counter()
+    for line in txt:
+        if any(word in keywords for word in jieba.cut(line)):
+            comment_counter[line] += 1
+    
+    return comment_counter
+
+comment_counter = sort(alltxt, keywords)
+top_comments = comment_counter.most_common(8) #输出排名前八
+
+#存入excel
+def save_to_excel(danmu_data, filename='danmu_data.xlsx'):
+    # 创建 DataFrame
+    df = pd.DataFrame(danmu_data, columns=['弹幕'])
+    # 保存到 Excel
+    with ExcelWriter(filename, engine='openpyxl') as writer:
+        df.to_excel(writer, index=False)
 
 # 主函数
 def main(kword,mubiao):
     search_url= f'https://search.bilibili.com/video?keyword={kword}'
-    print(search_url)
     for i in range(100):
         search_url=page(search_url,i)
         page_content = get_search_page(search_url)
@@ -122,9 +141,13 @@ def main(kword,mubiao):
     return(alltxt)
 
 # 示例搜索页 URL（需要替换为实际的搜索页 URL）
-keword = "2024巴黎奥运会"
-flag = 5 #你要爬的视频数量
+keword = "2024巴黎奥运会" #视频关键词
+flag = 300 #你要爬的视频数量
+
 alltxt=main(keword,flag)
 chuli(alltxt)
+save_to_excel(alltxt)
 
-
+# 输出排名前8的AI相关弹幕
+for comment, count in top_comments:
+    print(f'弹幕: {comment}, 数量: {count}')
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