import itertools
import re
import time
from collections import Counter
from multiprocessing import Pool
from random import random
import requests
from fake_useragent import UserAgent
from openpyxl import Workbook
from bilibili_api import video
import asyncio
import configparser


# 定义一些参数
uA = UserAgent()
BVs = []  # 存储bv号
counts = Counter()
header = {  # 从浏览器中复制下请求头
    'Accept': 'application/json, text/plain, */*',  # 接受的响应类型，包括 JSON、纯文本和所有其他类型
    'Accept-Encoding': 'gzip, deflate, br',  # 支持的编码方式，包括 gzip、deflate 和 br
    'Accept-Language': 'zh-CN,zh;q=0.9',  # 接受的语言，优先考虑简体中文
    'Origin': 'https://search.bilibili.com',  # 请求的起始地址
    'Referer': 'https://search.bilibili.com/all?vt=17031316&keyword=2024%E5%B7%B4%E9%BB%8E%E5%A5%A5%E8%BF%90%E4%BC%9A',  # 请求的来源页面地址
    'Sec-Ch-Ua': '"Chromium";v="128", "Not;A=Brand";v="24", "Microsoft Edge";v="128"',  # 客户端的浏览器信息
    'Sec-Ch-Ua-Mobile': '?0',  # 客户端是否是移动设备，0 表示不是
    'Sec-Ch-Ua-Platform': '"Windows"',  # 客户端的操作系统平台
    'Sec-Fetch-Dest': 'empty',  # 请求的目标类型
    'Sec-Fetch-Mode': 'cors',  # 请求模式，表示跨域资源共享（CORS）
    'Sec-Fetch-Site': 'same-site',  # 请求的来源网站，表示请求是来自同一站点
    'User-Agent': uA.random  # 用户代理信息，`uA.random` 是一个随机生成的用户代理字符串
}

header1 = {
    'UserAgent': uA.random
}


def get_Response(html_Url, h=header):
    try:
        response = requests.get(html_Url, headers=h)
        response.raise_for_status()
        response.encoding = 'utf-8'
        return response
    except requests.exceptions.RequestException as e:
        print(f"请求网页发生错误，错误信息：{e}")
        time.sleep(1)
        return None

# 从B站搜索栏中找排名前total_Num的视频，爬取他们的BV号，target为搜索内容,step为一页读取的视频数，默认为30
def get_Target_Video(arg):
    page, target, step, Cookie = arg
    header['Cookie'] = Cookie
    params = {  # 针对搜索栏，从浏览器中复制参数调用api
        '__refresh__': 'true',
        '_extra': '',
        'context': '',
        'page': page,
        'page_size': step,  # 设置一页读取step个视频
        'from_source': '',
        'from_spmid': '333.337',
        'platform': 'pc',
        'highlight': '1',
        'single_column': '0',
        'keyword': target,  # 此处是搜索内容
        'qv_id': '00d1q7iUbrvfsPdFZv2zXXtDqfcWuzER',
        'ad_resource': '5654',
        'source_tag': '3',
        'gaia_vtoken': '',
        'category_id': '',
        'search_type': 'video',
        'dynamic_offset': (step + 1) * (page - 1),
        'web_location': '1430654',
        'w_rid': 'f879864ca2210cc6a911552ceacadd6e',
        'wts': '1693922979'
    }

    api_Url = "https://api.bilibili.com/x/web-interface/wbi/search/type"  # 搜索栏的api
    print(f"开始爬取第{page}页视频")
    response = requests.get(api_Url, params, headers=header)
    if response.ok:
        content = response.text
        #print(content)
        match_Text = r'"bvid":"([^"]+)"'
        print(f"已爬取第{page}页视频")
        return re.findall(match_Text, content)
    else:
        print(f"请求网页失败,状态码：{response.status_code},可能是Cookie有误")
        return list()


# 根据bvid请求得到cid
def get_Cid(bvid):
    # 视频地址：https://www.bilibili.com/video/BV1PK4y1b7dt?t=1
    url = f'https://api.bilibili.com/x/player/pagelist?bvid={bvid}'
    # 转换接送类型，便于获取cid号
    res = requests.get(url).json()
    # 将获取的网页json编码字符串转换为python对象，字典类型
    cid = res["data"][0]['cid']
    return cid


def get_Danmu(BV):  # 对于一个BV号，将其分析为cid，后进入弹幕网站并爬取弹幕进行分析
    try:
        # 使用事件循环执行异步的 get_Cid 方法
        cid = asyncio.get_event_loop().run_until_complete(get_Cid(BV))
        if not cid:
            print(f"未能解析到 cid: {BV}")
            return None

        print(f"正在解析cid:{cid}的弹幕")
        danmu_Url = f"https://api.bilibili.com/x/v1/dm/list.so?oid={cid}.xml"
        content = get_Response(danmu_Url, header1)

        if not content:
            print(f"获取弹幕内容失败, BV号: {BV}")
            return None

        # 解析弹幕内容
        match_Text = r'<d[^>]*>([^<]+)</d>'
        matches = re.findall(match_Text, content.text)  # 爬取到的弹幕全部存储在列表中
        new_Counts = Counter(matches)  # 利用 counter 库对弹幕进行计数，统计每条弹幕的出现次数
        return new_Counts

    except AttributeError as e:
        print(f"出现属性错误: {e}")
        return None  # 如果 get_Cid() 返回 None，跳过，报错已经在 get_Cid 中进行了



def main():
    # Step 1：利用线程池找到前综合排序前300个视频
    print("Step 1: 利用线程池找到前综合排序前300个视频")
    pool = Pool(10)
    # 得到一个list，其每个元素为装着bv号的list
    args = []
    for i in range(1, (total_Num // step) + 1):
        args.append((i, target, step, Cookie))
    bv = pool.map(get_Target_Video, args)
    BVs = list(itertools.chain(*bv))  # 将得到的列表整合到一起
    pool.close()
    pool.join()
    # print(BVs)

    # Step 2：利用线程池对每一个视频的弹幕进行分析并分析频率
    print("Step 2: 利用线程池对每一个视频的弹幕进行爬取并分析频率")
    pool = Pool(max_Processing_Num)  # 线程太多会403、412，少用一些线程
    all_counts = pool.map(get_Danmu, BVs)
    for count in all_counts:
        counts.update(count)
    print("分析完成,正在导入Excel....")
    pool.close()
    pool.join()

    # Step 3: 取出现次数前8的弹幕，将他导入Excel
    print("Step 3: 取出现次数前8的弹幕，将他导入Excel")
    Top_8_Count = counts.most_common(8)
    all_counts = counts.most_common()
    # 创建一个新的 Excel 工作簿
    workbook = Workbook()
    worksheet1 = workbook.active
    worksheet1.title = "Top 8"
    # 将出现次数前 8 多的元素和计数器写入 Excel 表格中
    for row, (item, count) in enumerate(Top_8_Count, start=1):
        worksheet1.cell(row=row, column=1, value=item)
        worksheet1.cell(row=row, column=2, value=count)

    # 在第二页保存所有弹幕留档
    worksheet2 = workbook.create_sheet(title="所有弹幕")
    for row, (item, count) in enumerate(all_counts, start=1):
        worksheet2.cell(row=row, column=1, value=item)
        worksheet2.cell(row=row, column=2, value=count)
    # 保存 Excel 工作簿
    workbook.save('output/Top8_danmu.xlsx')
    print("导入完成！")


import configparser

if __name__ == "__main__":
    config = configparser.ConfigParser()

    # 读取配置文件时指定编码为 'utf-8'
    try:
        with open('config/config.ini', encoding='utf-8') as f:
            config.read_file(f)
    except UnicodeDecodeError as e:
        print(f"读取配置文件时发生编码错误: {e}")
        # 这里可以选择其他编码或采取其他措施
        exit(1)

    config_Section_Name = "CR_DEFAULT"

    # 获取配置项
    target = config.get(config_Section_Name, 'target', fallback="2024巴黎奥运会")
    total_Num = config.getint(config_Section_Name, 'total_Num', fallback=300)
    step = config.getint(config_Section_Name, 'step', fallback=30)
    max_Processing_Num = config.getint(config_Section_Name, 'max_Processing_Num', fallback=2)
    Cookie = config.get(config_Section_Name, 'Cookie',
                        fallback='buvid4=99B52D59-84E1-D6E5-3334-00A5ABF5485951328-023051720-QsQqaACvYRbeH92Bxo5wCA%3D%3D; enable_web_push=DISABLE; header_theme_version=CLOSE; _uuid=FE44153E-EED7-BA1F-B241-10F7389A82B2B15963infoc; buvid3=46549500-1464-AD65-9582-A44F9C4A512231965infoc; b_nut=1720278731; DedeUserID=357687474; DedeUserID__ckMd5=611d95a70851412a; buvid_fp_plain=undefined; PVID=1; CURRENT_QUALITY=64; CURRENT_FNVAL=4048; rpdid=|(JlklRl)~Yu0Ju~kYuJkk)); SESSDATA=58accf91%2C1741958959%2Ce9f13%2A92CjCG0FTU3yXRKTjvmpd9wl7RXlqJ6qUlwhLziQUN_oRfPs8uPa7egHmLWm8l6qhWVxUSVmcxM0ZYbUM3LUhiYkwxckVKNFA4aDNoWFQ0cWR3clROMnZvR1YwRXBTcDN4WWM4aWZrT2RRUlBkZ2haMVJzbGx0N0JZT1VLNWpmZUJTajJHeHE0TnBRIIEC; bili_jct=29dfdcaafd6930788ec4b9d06acc07cd; bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjY2NjYzMjUsImlhdCI6MTcyNjQwNzA2NSwicGx0IjotMX0.xjzf0c6AFp5o6yLJ6ahcJvyGwJZHK-NDBZsmlX0F6As; bili_ticket_expires=1726666265; fingerprint=556cd93cd4317211728f459c230e65c0; bsource=search_bing; home_feed_column=5; browser_resolution=1482-787; bp_t_offset_357687474=977795428588191744; sid=6jfn4n6l; buvid_fp=556cd93cd4317211728f459c230e65c0; b_lsid=D64E4486_191FB90E96C')

    # 确保 header 字典已初始化
    header = {}
    header['Cookie'] = Cookie

    main()