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from bs4 import BeautifulSoup
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import re
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import pandas as pd
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import jieba
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import requests
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import imageio
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import wordcloud
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from openpyxl import load_workbook
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from collections import Counter
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#获取User-Agent和cookie
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headers = {
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"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",
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"cookie": "buvid3=0C047DB7-FB67-6565-B853-68B19196AEE053166infoc; buvid4=D2E32722-EB31-8B5B-8BC7-420F049CDE3657801-022071821-mG8+jYWtWHQ35A9yqIgZIA%3D%3D; buvid_fp=60e37bdf4fe67cde89d283db25adff46; _uuid=FCEA6C48-BB82-123A-61106-3F5410106BB410B03170infoc; b_nut=100; header_theme_version=CLOSE; enable_web_push=DISABLE; bsource=search_bing; CURRENT_FNVAL=4048; SESSDATA=aa6a6590%2C1742210524%2C7b1c4%2A92CjCxud8rqp6tuF7AYkzmJF0YS7_L4_80iMI3NuY5q-M7BEW3cf0_bVyhIcnZMJapP7YSVnJiQ2NVcTJZZ1ZIMFduRURJXzZXOWtaTTl2WnBFSHkwckM0UzdwY2xHMG9MNVl4c1pUSHlFaFJ4RnQ5WjY3ZHRtcm5qcDhNSVo3eXZORDczc0VlYlF3IIEC; bili_jct=5232d057d308c18c1419d19271a3b85e; DedeUserID=1576579979; DedeUserID__ckMd5=da7d6054e70acbba; home_feed_column=5; browser_resolution=1528-748; bp_t_offset_1576579979=978508367389523968; bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjY5MjQzMzUsImlhdCI6MTcyNjY2NTA3NSwicGx0IjotMX0.9m3fjjjWd1wCsWNsTPwS9afVCknRz7dWtL6JV0CTQgI; bili_ticket_expires=1726924275; b_lsid=E4323108A_19205503541; sid=4q83ttnl; rpdid=|(u))kkY|mmJ0J'u~kYYYmmml"
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}
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#检查文本是否包含“ai”和“人工智能”字样
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#此函数用于检查
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def contains_ai_or_artificial_intelligence(text):
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ai_pattern = re.compile( r'(\bai\b|人工智能|([\u4e00-\u9fff]|\s|^)ai([\u4e00-\u9fff]|\s|$))', re.IGNORECASE)
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return re.search(ai_pattern, text)
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#获取html文本
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#该函数发送HTTP GET请求到指定URL，并返回网页的源码
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def get_html(url):
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response = requests.get(url,headers=headers)
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response.encoding = 'utf-8'
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html=response.text
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return html
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# 查找正确的api链接
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#解析HTML数据，提取标签
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def seek_api_urls(html_data):
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soup = BeautifulSoup(html_data, 'html.parser')
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urls = set()
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a_tags=soup.find_all('a', href=True)
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for a_link in a_tags:
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# 获取href的值
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link = a_link['href']
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urls.add(link)
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# 筛选正确的链接
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pattern = re.compile(r'https://api\.bilibili\.com/x/v1/dm/list\.so\?')
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api_urls = [url_find for url_find in urls if pattern.match(url_find)]
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#返回链接值
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return api_urls
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# 获取弹幕接口链接函数
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def get_api_urls(url):
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response = requests.get(url, headers=headers)
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if response.status_code == 200:
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html_data=response.text
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api_urls=seek_api_urls(html_data)
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return api_urls
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else:
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return []
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# 获取视频接口函数
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def get_urls(page):
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# 获得搜索页面url
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url = f"https://search.bilibili.com/video?keyword=%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=2&page={page}"
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html_data=get_html(url)
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soup = BeautifulSoup(html_data, 'html.parser')
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# 创建列表储存筛选完的内容
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urls = set()
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a_tags=soup.find_all('a', href=True)
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for a_link in a_tags:
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link = a_link['href']
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# 补全链接
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full_link=f'https:{link}'
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urls.add(full_link)
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# 筛选正确的链接
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pattern = re.compile(r'https://www\.bilibili\.com/video')
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#7x42=294，前七页全部读取
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if page != 8:
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vedieo_urls_f = [url_find for url_find in urls if pattern.match(url_find)]
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return vedieo_urls_f
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#第8页只读6个
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else: vedieo_urls_f = []
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num = 0
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for url_find in urls:
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if pattern.match(url_find):
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num = num + 1
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vedieo_urls_f.append(url_find)
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if num == 6:
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return vedieo_urls_f
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#获取接口链接
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def vedio_transform_port(url):
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html_data = get_html(url)
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soup = BeautifulSoup(html_data,"html.parser")
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page_num = [] #储存总共的分p数
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span_tag = None #用做判断有无分p的flag
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div_tags = soup.findAll("div",attrs={"class":"head-left"}) #找到class=head-left的div
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for tag in div_tags:
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span_tag=(tag.findAll("span",attrs={"class":"cur-page"})) #再从中找到class=cur-page的span
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if span_tag == None: #值为None则为单个视频
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port_url = url.replace("bilibili.com", "ibilibili.com")
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port_urls.add(port_url)
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else:
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for page in span_tag:
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pages = jieba.lcut(page.get_text()) #取得span的内容“（x/y)"，用jieba拆分成'(','x','/','y',')',其中y即为分p总数
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page_num = pages[3] #取得y的值
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# 替换每个分p视频的链接
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for page in range(1,int(page_num)+1):
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port_url = f"{url}?p={page}"
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port_urls.add(port_url.replace("bilibili.com", "ibilibili.com"))
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for page in range(1,8):
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vedio_urls=get_urls(page)
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port_urls=set()
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for vedio_url in vedio_urls:
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port_url = vedio_transform_port(vedio_url)
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for url in port_urls:
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api_urls=get_api_urls(url)
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if api_urls:
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api_url = api_urls[0]
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html_data = get_html(api_url)
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soup = BeautifulSoup(html_data, 'html.parser')
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content_list =re.findall('<d p=".*?">(.*?)</d>',html_data)
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content='\n'.join(content_list)
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with open('弹幕.txt',mode='a',encoding='utf-8') as f:
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f.write(content)
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ai_list = []
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most_common_barrages = []
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with open('弹幕.txt', 'r', encoding='utf-8') as file:
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content_txt = file.readlines()
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for barrage in content_txt:
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if contains_ai_or_artificial_intelligence(barrage):
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ai_list.append(barrage.strip())
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# 使用Counter统计每个弹幕的出现次数
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counter = Counter(ai_list)
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# 获取出现次数最多的前8个弹幕
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most_common_barrages = counter.most_common(8)
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#转变类型才可以写入excel
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ai_list1 = counter.most_common()
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# 输出结果
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for barrage, count in most_common_barrages:
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print(f'弹幕: {barrage} 出现次数: {count}')
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df = pd.DataFrame(ai_list1, columns=['弹幕', '出现次数'])
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# 写入Excel文件
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excel_path = '弹幕统计.xlsx'
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df.to_excel(excel_path, index=False, engine='openpyxl')
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wb = load_workbook(excel_path)
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ws = wb.active
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ws.column_dimensions['A'].width = 60
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wb.save(excel_path)
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ai_str = '\n'.join(ai_list) #分割成字符型
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# 创建词云图
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#create_wordcloud(ai_danmakus) |
