软工作业

2 months ago · 004a9f61ee
parent 24be71f82b
commit 004a9f61ee
1 changed files with 238 additions and 0 deletions
--- a/danmu.py
+++ b/danmu.py
@ -0,0 +1,238 @@
+
+import requests
+import re
+import xml.etree.ElementTree as ET
+from DrissionPage import ChromiumPage
+from bs4 import BeautifulSoup
+from collections import OrderedDict
+from collections import Counter
+import pandas as pd
+from PIL import Image
+import numpy as np
+import jieba
+from wordcloud import WordCloud
+import matplotlib.pyplot as plt
+
+
+headers = {
+    # cookie用户信息：用于检测用户是否登录账号
+    "cookie": "buvid4=B1349383-F2A6-E4E5-ED2C-A5B428CC0ED955473-022061918-9v4qmUz9VFkZrXyhSPgawQ%3D%3D; buvid_fp_plain=undefined; LIVE_BUVID=AUTO2216562263398747; is-2022-channel=1; CURRENT_FNVAL=4048; DedeUserID=406267828; DedeUserID__ckMd5=a7899a47ba8a07ab; enable_web_push=DISABLE; rpdid=|(u))kkYu||u0J'u~|JkJR)ul; FEED_LIVE_VERSION=V_WATCHLATER_PIP_WINDOW3; CURRENT_QUALITY=80; buvid3=3D0F285C-7560-9E88-C05A-1AFF4D9CAD7617643infoc; b_nut=1718944717; _uuid=BAAADDA5-4DDD-184B-DB310-EC4105D97D51E17974infoc; header_theme_version=CLOSE; fingerprint=5d019e2bddbce042baa44b97851bb2fd; buvid_fp=5d019e2bddbce042baa44b97851bb2fd; PVID=3; SESSDATA=e97fd178%2C1741840358%2C6c71f%2A91CjB7QCyKSGsn3CjY0C0HRTQF_8a0AYz9r9QLq2FL2YiXLfQFehx5MdXHV3EDcePi4mwSVlM3TVE3LWcyczhLbXoycnhOTWtwa2g5OEl4RVdxOVRQZjljWGJ5d2czbFZpTkVhd3hfRnFmYTE4TVRISTlkdXFpemd1SmhOejNnVm1mYlJ0UDZEcTNBIIEC; bili_jct=4b351ffc7724b0bb10c029efdfad7f75; sid=6jnrbe6l; bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjY1NDc1NzEsImlhdCI6MTcyNjI4ODMxMSwicGx0IjotMX0.l-PQPoCUFvsMgRpDwqUKwUY9jLLjI-p-HZ1Qaq7AIjI; bili_ticket_expires=1726547511; b_lsid=1564BAD10_191F00CC884; bp_t_offset_406267828=976996173829111808; home_feed_column=5; browser_resolution=2048-1030",
+    # user-agent用户代理：表示浏览器设备的基本信息
+    "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 Edg/128.0.0.0"
+}
+
+def get_video_details(search_url):
+
+    response = requests.get(search_url, headers=headers)
+    # 确保请求成功
+    response.raise_for_status()
+
+    soup = BeautifulSoup(response.text, 'html.parser')
+
+    # 匹配 BV 号
+    bv_pattern = re.compile(r'BV[1-9A-Za-z]{10}')
+    bv_l=[]
+    for tag in soup.find_all('a', href=True):
+        if 'BV' in tag['href']:
+            bv = bv_pattern.search(tag['href'])
+            bv_l.append(bv.group())
+            bv_l = list(OrderedDict.fromkeys(bv_l))# 去重
+
+    return bv_l
+
+def get_video_info(bv_id):
+    """ 获取视频信息并解析CID """
+    url = f'https://api.bilibili.com/x/web-interface/view?bvid={bv_id}'
+    response = requests.get(url, headers=headers)
+    response.encoding = 'utf-8'
+    response.raise_for_status()
+    data = response.json()
+    cid = data['data']['cid']
+    return cid
+
+
+def get_danmaku_xml(cid):
+    """ 根据CID获取弹幕XML数据 """
+    url = f'https://comment.bilibili.com/{cid}.xml'
+    response = requests.get(url, headers=headers)
+    response.encoding = 'utf-8'
+    # 确保请求成功
+    response.raise_for_status()
+    return response.text
+
+
+def parse_danmaku_xml(xml_str):
+    """ 解析弹幕XML数据 """
+    root = ET.fromstring(xml_str)
+    danmaku_list = [d.text for d in root.findall('.//d') if d.text]
+    return danmaku_list
+
+
+def save_danmaku_to_excel(danmaku_content, file_name='danmaku_content.xlsx'):
+    """
+    将弹幕内容保存到 Excel 文件中
+    :param danmaku_content: 包含弹幕内容的列表
+    :param file_name: Excel 文件名
+    """
+    # 检查是否已经存在文件
+    try:
+        # 尝试读取现有文件
+        existing_df = pd.read_excel(file_name,engine='openpyxl')
+    except FileNotFoundError:
+        # 文件不存在，则创建新的 DataFrame
+        existing_df = pd.DataFrame(columns=['content'])
+
+    # 将新弹幕内容转换为 DataFrame，并自动生成 'id'
+    new_df = pd.DataFrame(danmaku_content, columns=['content'])
+    # new_df['id'] = range(len(existing_df), len(existing_df) + len(new_df))
+
+    # 合并现有内容和新内容
+    updated_df = pd.concat([existing_df, new_df], ignore_index=True)
+
+    # 保存到 Excel 文件
+    updated_df.to_excel(file_name, index=False)
+
+
+def savef(video_url):
+    """ 主函数，获取并展示弹幕数据 """
+
+    # 提取BV号
+    bv_id = re.search(r'BV\w+', video_url).group(0)
+
+    # 获取视频CID
+    cid = get_video_info(bv_id)
+    # print(f"提取的CID: {cid}")
+
+    # 获取弹幕数据
+    xml_data = get_danmaku_xml(cid)
+    danmakus = parse_danmaku_xml(xml_data)
+
+    save_danmaku_to_excel(danmakus, file_name='danmaku_content.xlsx')
+
+    # # 保存并打印弹幕
+    # for i, danmaku in enumerate(danmakus):
+    #     # 遍历爬取的弹幕内容并逐条保存
+    #
+    #     print(f"弹幕 {i + 1}: {danmaku}")
+    # file_name = 'danmaku_content.xlsx'
+    # print(f"弹幕内容已保存到 {file_name}")
+
+# 网址
+driver = ChromiumPage()
+url = "https://search.bilibili.com/all?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=3&page=2&o=36"
+driver.get('https://search.bilibili.com/all?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=3&page=2&o=36')
+j=0
+for page in range(8):
+    bv_list = get_video_details(url)
+    for bv in bv_list:
+        if j==300:
+            break
+        j+=1
+        # 函数入口，定义函数需要调用
+        video_url = f'https://www.bilibili.com/video/{bv}/?spm_id_from=333.337'
+        # 调用保存的函数
+        print(f"v{j}")
+        savef(video_url)
+    # 点击下一页
+    driver.ele('css:vui_button vui_pagenation--btn vui_pagenation--btn-side').click()
+
+
+
+
+# 读取xlsx文件
+df = pd.read_excel('danmaku_content.xlsx',engine='openpyxl')
+
+# 假设弹幕数据在名为'danmaku'的列中
+danmaku_column = df['content']
+
+def filter_ai_danmaku(danmaku_series, keywords):
+    ai_danmaku = []
+    for danmaku in danmaku_series:
+        if pd.notna(danmaku):  # 检查弹幕是否为空
+            danmaku_str = str(danmaku)  # 转换为字符串
+            if any(keyword in danmaku_str for keyword in keywords):
+                ai_danmaku.append(danmaku_str)
+    return ai_danmaku
+
+ai_keywords = ["AI", "AI技术", "机器学习", "深度学习", "智能", "VR/AR", "全景直播", "360度", "3D", "追踪" ,"虚拟", "数字", "人工智能", "面部识别", "云技术", "安保", "检测", "监测", "福州大学"]
+# 筛选与AI相关的弹幕
+filtered_danmaku = filter_ai_danmaku(danmaku_column, ai_keywords)
+
+# print(len(filtered_danmaku))
+
+# 统计每种弹幕的数量
+danmaku_count = Counter(filtered_danmaku)
+
+# 排序并获取前n项
+sorted_danmaku = danmaku_count.most_common(15)
+
+# print(sorted_danmaku)
+
+# 输出排名前n的弹幕及数量
+for i, (danmaku, count) in enumerate(sorted_danmaku, 1):
+    print(f"排名 {i}: {danmaku} - 数量: {count}")
+
+# 将数据转化为DataFrame
+danmaku_df = pd.DataFrame(sorted_danmaku, columns=['弹幕内容', '数量'])
+
+# 导出到Excel文件
+danmaku_df.to_excel('ai_danmaku_statistics.xlsx', index=False, engine='openpyxl')
+
+
+def generate_beautiful_wordcloud(file_name='ai_danmaku_statistics.xlsx', mask_image_path=None,font_path=r"C:\Users\wyk93\Desktop\苹方黑体-准-简.ttf"):
+    # 读取 Excel 文件
+    df = pd.read_excel(file_name)
+
+    # 合并所有弹幕内容为一个大字符串
+    text = ' '.join(df['弹幕内容'].dropna().astype(str))
+
+    # 使用 jieba 进行分词
+    seg_list = jieba.cut(text, cut_all=True)
+    segmented_text = " ".join(seg_list)
+
+    # # 打印合并后的文本以检查内容
+    # print("Text content:")
+    # print(text[:500])  # 打印前500个字符以检查
+
+    # 读取自定义形状图片
+    if mask_image_path:
+        mask_image = np.array(Image.open(mask_image_path).convert('L'))
+        mask_image[mask_image > 200] = 255
+        mask_image[mask_image <= 200] = 0
+    else:
+        mask_image = None
+
+    background_image = Image.open(mask_image_path)
+
+    # 创建词云对象
+    wordcloud = WordCloud(
+        background_color='white',# 透明背景
+        mask=mask_image,
+        contour_color=None,
+        contour_width=2,
+        width=2000,  # 词云图的宽度
+        height=2000,  # 词云图的高度
+        colormap='viridis' , # 使用 'viridis' 颜色映射
+        max_words=20000,
+        # min_font_size=10,
+        # max_font_size=100,
+        # prefer_horizontal=0.9,  # 更高的水平优先级
+        font_path=font_path # 如果需要显示中文，需要指定中文字体路径
+    ).generate(segmented_text)  # 这里替换为你自己的文本数据
+
+    # 显示词云图
+    plt.figure(figsize=(10, 8))
+    plt.imshow(background_image, interpolation='bilinear')
+    plt.imshow(wordcloud, interpolation='bilinear', alpha=0.4)  # 设置透明度
+    plt.axis('off')  # 不显示坐标轴
+    plt.show()
+
+# 调用函数生成词云
+# 可选: 使用自定义形状的掩膜图像
+generate_beautiful_wordcloud(mask_image_path=r"C:\Users\wyk93\Desktop\图片素材\sucai3.jpg")
+
+
+
+
+
+