import requests
import json
import re
import jieba
import time
import wordcloud
import numpy as np
from PIL import Image
import pandas as pd

def get_search(v_keyword, max_videos=300):
    video_count = 0  # 记录已爬取的视频数量
    page_size = 30  # 每页视频数量
    max_page = max_videos // page_size  # 计算需要爬取的页数

    for page in range(1, max_page + 1):
        if video_count >= max_videos:
            break

        # 请求地址
        url = 'https://api.bilibili.com/x/web-interface/wbi/search/type'
        # 请求头
        headers = {
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
            'Referer': 'https://www.bilibili.com/video/BV1xxxxxxx',  # 修改为目标视频的 URL
            'Accept': 'application/json, text/plain, */*',
            'cookie':'buvid3 = 2C1B627D - C611 - D842 - 783F - 1D6D6205BE8E30149infoc;b_nut = 1716183429;buvid4 = 58C6836B - CD3C - B8D8 - B75E - 014E5D19E71730149 - 024052005 - BX9TPJ1Qd1SMwWPyECcJSQ % 3D % 3D;_uuid = 88852C4D - 2847 - F2A7 - 1043A - FCF7104D7E6DD13761infoc;rpdid = | (JlklRl)~Yu0Ju~uYu)Jlu~; DedeUserID=22863112; DedeUserID__ckMd5=f744f10bf9a83bc2; enable_web_push=DISABLE; header_theme_version=CLOSE; hit-dyn-v2=1; buvid_fp_plain=undefined; LIVE_BUVID=AUTO1617162131622559; CURRENT_FNVAL=4048; fingerprint=3b1cd80e32b9900fd22fdd2e95f8b55f; home_feed_column=5; CURRENT_QUALITY=80; browser_resolution=1488-738; PVID=1; buvid_fp=3b1cd80e32b9900fd22fdd2e95f8b55f; SESSDATA=234b58b7%2C1741842619%2C4f93a%2A91CjAqN6Nk1W9q-NW-cK5kX_jJcu9jtvJEQe4MTO1eHvrS8hz-apd6jYPG1Lm9-_NlfGQSVkZnM1FNa2hGYzl5a1pCbkkzZ2JpQlc1RFRYUTY2N3VlU0Q5ZmVTZ01zLUE3aXVPY0VzcXpGeVNDMVU5dUNsNlYxbHpRYXZab3h0amEyQ011ZFBCdTl3IIEC; bili_jct=4e3c35728fb766db9f42f2eded6a02c2; b_lsid=86E10C228_191F3A74756; bp_t_offset_22863112=977239569625776128'
        }

        params = {
            '__refresh__': 'true',
            'page': page,
            'page_size': page_size,
            'keyword': v_keyword,
            'order': 'totalrank',
            'search_type': 'video',
            'csrf': 'your_bili_jct_value'  # 确保这里是从 Cookie 中获取的有效值
        }

        # 向页面发送请求
        r = requests.get(url, headers=headers, params=params)
        if r.status_code != 200:
            print(f"请求失败，状态码：{r.status_code}")
            break

        result = r.json().get('data', {}).get('result', [])
        if not result:
            print(f"第{page}页没有结果，停止爬取。")
            break


        # 处理当前页的搜索结果
        for index in result:
            if video_count >= max_videos:
                break
            bv_id = index['bvid']
            print(f"正在处理视频: {bv_id}")  # 打印视频ID
            with open('bv_id_1.txt', mode='a', encoding='utf-8') as f:
                f.write(bv_id)
                f.write('\n')

            # 获取视频弹幕的 cid
            cid_url = f'https://api.bilibili.com/x/player/pagelist?bvid={bv_id}&jsonp=jsonp'
            response = requests.get(url=cid_url, headers=headers)
            if response.status_code != 200:
                print(f"获取 cid 失败，状态码：{response.status_code}")
                continue

            res_dict = json.loads(response.content.decode('utf-8'))
            values = res_dict.get('data', [])
            if not values:
                print(f"没有找到视频 {bv_id} 的 cid。")
                continue

            for cid_values in values:
                cid = str(cid_values.get('cid'))

                # 获取弹幕内容
                danmu_url = f'https://api.bilibili.com/x/v1/dm/list.so?oid={cid}'
                response = requests.get(danmu_url, headers=headers)
                if response.status_code != 200:
                    print(f"获取弹幕失败，状态码：{response.status_code}")
                    continue

                # 提取弹幕文本
                content_list = re.findall('<d p=".*?">(.*?)</d>', response.content.decode('utf-8'))
                if not content_list:
                    print(f"视频 {bv_id} 没有弹幕。")
                    continue

                print(f"视频 {bv_id} 的弹幕数量: {len(content_list)}")  # 打印弹幕数量

                # 保存弹幕文本
                with open('弹幕文本.txt', mode='a', encoding='utf-8') as f:
                    for content in content_list:
                        f.write(content)
                        f.write('\n')

            video_count += 1
            print(f"当前已爬取视频数量: {video_count}")
            time.sleep(1)  # 添加延迟以减少被封的风险

def get_wordcloud():
    """生成词云图"""
    with open('弹幕文本.txt', encoding='utf-8') as f:
        txt = f.read().strip()  # 读取文件并去除空白字符
    if not txt:
        print("错误：弹幕文本为空，无法生成词云。")
        return
    # 切词并生成词云
    stopwords = set(["哈哈", "哈哈哈", "哈哈哈哈", "哈哈哈哈哈", "哈哈哈哈哈哈", "哈哈哈哈哈哈哈", "哈哈哈哈哈哈哈哈哈",
         "哈哈哈哈哈哈哈哈哈", "哈哈哈哈哈哈哈哈哈哈", "哈哈哈哈哈哈哈哈哈哈哈哈哈", "哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈",
         "哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈", "哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈", '的', '了', '啊','在', '是', '我', '你', '他', '她', '它', '有', '和', '这', '那', '这个','不是','真的','我们', '你们', '他们'])
    string = ' '.join(jieba.cut(txt))
    mask = np.array(Image.open("7.png"))  # 使用图片作为遮罩
    wc = wordcloud.WordCloud(
        background_color='white',
        font_path='msyh.ttc',
        colormap='Blues',
        mask=mask,
        stopwords = stopwords
    )
    wc.generate(string)
    wc.to_file('词云图.png')
    print("词云图生成成功！")


def get_excel():
    """统计弹幕出现次数并导出Excel"""
    with open('弹幕文本.txt', 'r', encoding='utf-8') as file:
        lines = file.readlines()

    # 去除换行符后统计出现次数
    line_counts = pd.Series([line.strip() for line in lines]).value_counts()
    df = pd.DataFrame({'弹幕': line_counts.index, '出现次数': line_counts.values})
    df.to_excel('结果统计.xlsx', index=False)


def analyze_ai_application():
    """分析AI相关关键词并导出Excel"""
    with open('弹幕文本.txt', encoding='utf8') as file:
        text = file.read()
    ai_keywords = ["智能装备", "数据分析", "虚拟训练", "人工智能", "AR", "3D分析", "自动裁判", "ai","科学","自动","芯片","算法","智能","建模"]
    keyword_counts = {kw: text.count(kw) for kw in ai_keywords}
    df = pd.DataFrame(sorted(keyword_counts.items(), key=lambda x: x[1], reverse=True), columns=['关键词', '出现次数'])
    df.to_excel('关键词统计.xlsx', index=False)


if __name__ == '__main__':
    get_search('2024巴黎奥运会', max_videos=300)
    get_wordcloud()
    get_excel()
    analyze_ai_application()