# 2.1
# 数据获取

# 导入必要的库
import requests                             # 用于发送HTTP请求
import json                                 # 用于处理JSON数据
import re                                   # 用于正则表达式匹配
import openpyxl                             # 用于操作Excel文件
import pandas as pd                         # 用于数据处理和分析
import matplotlib.pyplot as plt             # 导入matplotlib模块pyplot函数并使用as给函数起个别名plt
import jieba                                # 导入jieba分词模块
import wordcloud                            # 导入词云图模块
import numpy as np                          # 导入numpy模块
from wordcloud import ImageColorGenerator   # 用于从图片生成颜色以渲染词云
from PIL import Image                       # 从PIL模块中导入Image函数
from collections import Counter             # 导入Counter类，用于计数 

# 定义目标URL，用于搜索Bilibili视频
url = "https://api.bilibili.com/x/web-interface/wbi/search/type?page_size=50&keyword=2024%E5%B7%B4%E9%BB%8E%E5%A5%A5%E8%BF%90%E4%BC%9A&search_type=video"

# 设置请求头，模拟浏览器访问
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36 SLBrowser/9.0.3.5211 SLBChan/105"
}

# 设置Cookies
cookies = {
    "buvid3":"11680F37-E62C-C9EF-B7B2-D198332B61D003377infoc",
    "LIVE_BUVID": "AUTO6416610696475006",
    "rpdid": "|(u))kkYu|R~0J'uY~|)R)Ylm",
    "header_theme_version": "CLOSE",
    "FEED_LIVE_VERSION": "V8",
    "buvid4": "3385D89E-82EA-B792-EDDB-1C760C74377804485-022082013-T76gCyS8edfpVC%2B%2FEm%2F9gg%3D%3D",
    "CURRENT_FNVAL": "4048",
    "DedeUserID": "476167968",
    "DedeUserID__ckMd5": "99a92c4d7eeebff0",
    "b_nut": "100",
    "_uuid": "62A11A33-AE63-6B810-5BA8-74B644C9153733847infoc",
    "buvid_fp_plain": "undefined",
    "enable_web_push": "DISABLE",
    "buvid_fp": "283c30b12d458a0311744e346aebd9e9",
    "home_feed_column": "5",
    "fingerprint": "c828157aaa66d22b3a4b841dc0dd5a96",
    "PVID": "2",
    "browser_resolution": "2074-1144",
    "SESSDATA": "82243f05%2C1742112657%2C2d174%2A92CjA9CO3snstNoEvGickntljsVXZ2EcZHTxBcUE6h9oSQ1xl21MqQVX6gOpdj74xy2VoSVkJfdzRzTy1RUkVyNGhjcDQtejBMMHBHUEUxbWI0bWowU1lWVG9mUmVoQkE4X3lPS2phUjVqS2tHRTVpdlo1U19WQVd4dzQ4RzRpNUtIZjdPX0ZkOS13IIEC",
    "bili_jct": "efe32125b9809a8323328e31b7fa7e99",
    "hit-dyn-v2": "1",
    "bili_ticket": "eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjY4MjUxMDYsImlhdCI6MTcyNjU2NTg0NiwicGx0IjotMX0.n0BlSThp9ye0k6US20pEh5gz191I6-1IgplXC1yJ2uI",
    "bili_ticket_expires": "1726825046",
    "b_lsid": "13EA7118_191FFF83B6D",
    "bp_t_offset_476167968": "978129864806629376",
    "sid": "6bro4vni",
}

# 初始化一个空列表，用于存储弹幕内容
danmu_list = []

# 定义一个函数，用于获取指定视频的弹幕
def get_danmu(bvid,headers):
    cid_url = "https://api.bilibili.com/x/web-interface/view?bvid=" + bvid  # 构造获取视频cid的URL
    cid_req = requests.get(cid_url, headers=headers)                        # 发送请求获取视频cid
    cid_res = json.loads(cid_req.text)                                      # 将响应内容转换为JSON格式
    cid = cid_res['data']['cid']                                            # 从响应中提取视频的cid
    danmu_url = "https://comment.bilibili.com/" + str(cid) + ".xml"         # 构造获取弹幕的URL
    danmu_req = requests.get(danmu_url, headers=headers)                    # 发送请求获取弹幕内容
    danmu_req.encoding = 'utf-8'                                            # 设置响应内容的编码为utf-8
    danmu_list = re.findall('<d p=".*?">(.*?)</d>',danmu_req.text)          # 使用正则表达式匹配弹幕内容
    return danmu_list                                                       # 返回匹配到的弹幕列表

# 循环发送请求，获取多页视频数据
for i in range(10): 
    sess = requests.session()                                                       # 创建一个requests.session()对象，用于维持会话
    req = sess.get(url + "&page=" + str(i+1), headers=headers, cookies=cookies)     # 构造分页请求的URL，发送请求
    res = json.loads(req.text)                                                      # 将响应内容转换为JSON格式
    for video in res['data']['result']:                                             # 遍历响应中的视频数据
        danmu_list = danmu_list + get_danmu(video['bvid'],headers)                  # 调用函数获取每个视频的弹幕，并追加到danmu_list列表中

df = pd.DataFrame(danmu_list)                               # 将弹幕列表转换为pandas DataFrame  
df.to_excel('danmu.xlsx',index=False,engine='openpyxl')     # 将DataFrame保存到Excel文件
print("弹幕已保存")                                          # 打印提示信息


# 2.2
# 数据统计

# 定义关键词列表  
keywords = ['Ai','智能','3D','技术','科学']  
  
# 过滤包含关键词的弹幕  
filtered_danmu_list = [danmu for danmu in danmu_list if any(keyword in danmu.lower() for keyword in keywords)]  
  
# 对过滤后的弹幕进行计数  
danmu_count = Counter(filtered_danmu_list)  
  
# 获取数量排名前8的弹幕
top_8_count = danmu_count.most_common(8)  
  
# 创建新的Excel表，写入统计结果  
workbook = openpyxl.Workbook()
sheet = workbook.active  
  
# 写入表头  
sheet['A1'] = '弹幕'  
sheet['B1'] = '数量'  
  
# 写入数据  
for i, (danmu, count) in enumerate(top_8_count, start=2):  
    sheet[f'A{i}'] = danmu  
    sheet[f'B{i}'] = count  

# 打印提示信息
print("弹幕已过滤") 

# 保存Excel表  
workbook.save('danmu_count.xlsx')


# 2.3
# 数据可视化

# 读取Excel文件  
df = pd.read_excel('danmu_count.xlsx', usecols=['弹幕']) 

# 获取弹幕列表
text = ' '.join(df['弹幕'].astype(str).tolist()) # 提取弹幕内容并合并为一个长字符串
cut_text = jieba.cut(text)                       # 分词处理
word = ' '.join(cut_text)                        # 以空格分割文本

# 设置停用词
stopwords = set(["的", "了", "和", "是", "在", "我", "你", "他", "她"])

# 读取图片
pic = np.array(Image.open('1.png'))         # 打开并加载图片文件
image_colors = ImageColorGenerator(pic)     # 创建颜色生成器，用于从图片中提取颜色 

# 配置并生成词云图
wd = wordcloud.WordCloud(
    mask=pic,                       # 使用图片作为词云的形状                   
    font_path='simhei.ttf',         # 指定字体路径，以支持中文显示     
    background_color='white',       # 设置背景颜色为白色    
    ) 
wd.generate(word)                   # 根据提供的文本生成词云

# 图片颜色渲染词云图的颜色，用color_func指定
plt.imshow(wd.recolor(color_func=image_colors), interpolation='bilinear')   # 展示词云图
plt.axis('off')                                                             # 关闭显示x轴、y轴下标
plt.show()                                                                  # 显示图像