From 709561633a1f6572ec5d244d01cfdc82f4c7ed52 Mon Sep 17 00:00:00 2001
From: pu6qcatis <916351100@qq.com>
Date: Sun, 15 Sep 2024 09:11:32 +0800
Subject: [PATCH] Delete 'requirements.txt'

---
 requirements.txt | 94 ------------------------------------------------
 1 file changed, 94 deletions(-)
 delete mode 100644 requirements.txt

diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index 4232bd5..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,94 +0,0 @@
-import requests
-from bs4 import BeautifulSoup
-import time
-import pandas as pd
-from collections import Counter
-from wordcloud import WordCloud
-import matplotlib.pyplot as plt
-cnt = 0  #已爬取视频数
-danmuku_all = []  #弹幕库
-
-headers = {
-    user-agent Mozilla5.0 (Windows NT 10.0; Win64; x64) AppleWebKit537.36 (KHTML, like Gecko) Chrome128.0.0.0 Safari537.36
-}
-def get_cid(bvid)
-    url = fhttpsapi.bilibili.comxplayerpagelistbvid={bvid}
-    try
-        response = requests.get(url, headers=headers, timeout=10)
-        response.raise_for_status()
-        Json = response.json()
-        return Json['data'][0]['cid']
-    except requests.exceptions.RequestException as e
-        print(f请求失败 {e})
-        return None
-def get_danmuku(cid)
-    if cid is None
-        return []
-    url = fhttpscomment.bilibili.com{cid}.xml
-    try
-        response = requests.get(url, headers=headers, timeout=10)
-        response.encoding = 'utf-8'
-        soup = BeautifulSoup(response.text, 'xml')
-        return [i.text for i in soup.find_all('d')]
-    except requests.exceptions.RequestException as e
-        print(f请求失败 {e})
-        return []
-for Page in range(1, 22)
-    url = f'httpsapi.bilibili.comxweb-interfacesearchtypesearch_type=video&keyword=巴黎奥运会&page={Page}'
-    try
-        response = requests.get(url, headers=headers, timeout=10)
-        response.raise_for_status()
-        Json = response.json()
-        results = Json['data']['result']
-        for result in results
-            cid = get_cid(result['bvid'])
-            danmuku = get_danmuku(cid)
-            danmuku_all.extend(danmuku)
-            cnt += 1
-            if cnt = 300
-                break
-        if cnt = 300
-            break
-    except requests.exceptions.RequestException as e
-        print(f请求失败 {e})
-time.sleep(1)  #延时1秒防止被屏蔽
-def filter_danmuku(danmuku_list, keywords)
-    #筛选包含指定关键词的弹幕
-    keywords_lower = [keyword.lower() for keyword in keywords]  # 关键词小写
-    filtered = [d for d in danmuku_list if any(keyword in d.lower() for keyword in keywords_lower)]
-    return filtered
-
-#读取弹幕文件
-with open('所有视频弹幕.txt', 'r', encoding='utf-8') as file
-    danmuku_all = file.readlines()
-
-#筛选包含关键词的弹幕
-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']
-filtered_danmuku = filter_danmuku(danmuku_all, keywords)
-#统计弹幕数量
-counter = Counter(filtered_danmuku)
-most_common = counter.most_common(8)
-#将结果按列写入Excel
-data = {'弹幕内容' [content.strip() for content, count in most_common],
-        '数量' [count for content, count in most_common]}
-df = pd.DataFrame(data)
-df.to_excel('AI_人工智能_弹幕统计.xlsx', index=False)
-print(前8位弹幕统计已保存到 'AI_人工智能_弹幕统计.xlsx'.)
-font_path = r'CWindowsFontssimhei.ttf'
-try
-    df = pd.read_excel('AI_人工智能_弹幕统计.xlsx')
-    if '弹幕内容' not in df.columns
-        raise ValueError(Excel 文件中没有找到 '弹幕内容' 列)
-    text = ' '.join(df['弹幕内容'].dropna())
-    wordcloud = WordCloud(font_path=font_path, width=800, height=400, background_color='white').generate(text)
-    plt.figure(figsize=(10, 5))
-    plt.imshow(wordcloud, interpolation='bilinear')
-    plt.axis('off')
-    plt.show()
-    wordcloud.to_file('词云图.png')
-except FileNotFoundError
-    print(文件未找到，请检查文件路径)
-except ValueError as ve
-    print(ve)
-except Exception as e
-    print(f发生错误 {e})
\ No newline at end of file