102201314/main.py

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 = {
    "cookie": "cookie",
    "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"
}


def get_cid(bvid):
    url = f"https://api.bilibili.com/x/player/pagelist?bvid={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 = f"https://comment.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):  # 1到22页够300个视频
    url = f'https://api.bilibili.com/x/web-interface/search/type?search_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配音' , 'ai配音' , '人工智能' , 'ai画图' , 'AI画图' , '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'C:\Windows\Fonts\simhei.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}")