parent
ad1dbd0191
commit
709561633a
@ -1,94 +0,0 @@
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import requests
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from bs4 import BeautifulSoup
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import time
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import pandas as pd
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from collections import Counter
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from wordcloud import WordCloud
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import matplotlib.pyplot as plt
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cnt = 0 #已爬取视频数
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danmuku_all = [] #弹幕库
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headers = {
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user-agent Mozilla5.0 (Windows NT 10.0; Win64; x64) AppleWebKit537.36 (KHTML, like Gecko) Chrome128.0.0.0 Safari537.36
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}
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def get_cid(bvid)
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url = fhttpsapi.bilibili.comxplayerpagelistbvid={bvid}
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try
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response = requests.get(url, headers=headers, timeout=10)
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response.raise_for_status()
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Json = response.json()
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return Json['data'][0]['cid']
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except requests.exceptions.RequestException as e
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print(f请求失败 {e})
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return None
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def get_danmuku(cid)
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if cid is None
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return []
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url = fhttpscomment.bilibili.com{cid}.xml
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try
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response = requests.get(url, headers=headers, timeout=10)
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response.encoding = 'utf-8'
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soup = BeautifulSoup(response.text, 'xml')
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return [i.text for i in soup.find_all('d')]
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except requests.exceptions.RequestException as e
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print(f请求失败 {e})
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return []
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for Page in range(1, 22)
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url = f'httpsapi.bilibili.comxweb-interfacesearchtypesearch_type=video&keyword=巴黎奥运会&page={Page}'
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try
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response = requests.get(url, headers=headers, timeout=10)
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response.raise_for_status()
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Json = response.json()
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results = Json['data']['result']
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for result in results
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cid = get_cid(result['bvid'])
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danmuku = get_danmuku(cid)
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danmuku_all.extend(danmuku)
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cnt += 1
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if cnt = 300
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break
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if cnt = 300
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break
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except requests.exceptions.RequestException as e
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print(f请求失败 {e})
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time.sleep(1) #延时1秒防止被屏蔽
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def filter_danmuku(danmuku_list, keywords)
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#筛选包含指定关键词的弹幕
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keywords_lower = [keyword.lower() for keyword in keywords] # 关键词小写
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filtered = [d for d in danmuku_list if any(keyword in d.lower() for keyword in keywords_lower)]
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return filtered
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#读取弹幕文件
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with open('所有视频弹幕.txt', 'r', encoding='utf-8') as file
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danmuku_all = file.readlines()
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#筛选包含关键词的弹幕
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keywords = ['AI识曲','AI生成','神经网络','卷积神经网络','循环神经网络','智能家居','自动驾驶','智能推荐','智能算法','强化学习','计算机视觉','ai还原','ai合成']
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filtered_danmuku = filter_danmuku(danmuku_all, keywords)
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#统计弹幕数量
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counter = Counter(filtered_danmuku)
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most_common = counter.most_common(8)
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#将结果按列写入Excel
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data = {'弹幕内容' [content.strip() for content, count in most_common],
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'数量' [count for content, count in most_common]}
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df = pd.DataFrame(data)
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df.to_excel('AI_人工智能_弹幕统计.xlsx', index=False)
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print(前8位弹幕统计已保存到 'AI_人工智能_弹幕统计.xlsx'.)
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font_path = r'CWindowsFontssimhei.ttf'
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try
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df = pd.read_excel('AI_人工智能_弹幕统计.xlsx')
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if '弹幕内容' not in df.columns
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raise ValueError(Excel 文件中没有找到 '弹幕内容' 列)
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text = ' '.join(df['弹幕内容'].dropna())
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wordcloud = WordCloud(font_path=font_path, width=800, height=400, background_color='white').generate(text)
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plt.figure(figsize=(10, 5))
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plt.imshow(wordcloud, interpolation='bilinear')
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plt.axis('off')
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plt.show()
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wordcloud.to_file('词云图.png')
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except FileNotFoundError
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print(文件未找到，请检查文件路径)
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except ValueError as ve
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print(ve)
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except Exception as e
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print(f发生错误 {e})
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