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code.py

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+import requests
+import  re
+from bs4 import BeautifulSoup
+from urllib.parse import urljoin
+from collections import Counter
+import pandas as pd
+from wordcloud import WordCloud
+import matplotlib.pyplot as plt
+
+headers = {
+        "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",
+        "cookie": "CURRENT_FNVAL=4048; buvid_fp_plain=undefined; buvid4=04DF7AEF-34D9-CC62-690A-D369B35D458509591-023061415-%2FxwqHe8zHTWav6Q4ZiB1Ag%3D%3D; enable_web_push=DISABLE; FEED_LIVE_VERSION=V_WATCHLATER_PIP_WINDOW3; PVID=1; buvid3=D5B12366-476E-6163-1D79-774D300DF97306537infoc; b_nut=1718270506; _uuid=243B710F9-1010E3-9654-E867-4A8D8BB10AB1307743infoc; header_theme_version=CLOSE; rpdid=0zbfAHMKHr|S8rGMSwG|1uI|3w1Sum1G; fingerprint=042b265e3c7da3104d09a0692278e922; CURRENT_QUALITY=80; home_feed_column=5; browser_resolution=1659-836; bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjU5NDEwOTEsImlhdCI6MTcyNTY4MTgzMSwicGx0IjotMX0.j7rN8z5QOwH-7R7gPvyBxJzDLqymAWFfZeFF-QAXoTQ; bili_ticket_expires=1725941031; bp_t_offset_482950113=974463371485118464; buvid_fp=042b265e3c7da3104d09a0692278e922; b_lsid=DDE103767_191D4FCA152"
+    }
+vedio_sum=0
+
+def contains_ai_or_artificial_intelligence(text):
+    ai_pattern = re.compile( r'(\bai\b|人工智能|([\u4e00-\u9fff]|\s|^)ai([\u4e00-\u9fff]|\s|$))', re.IGNORECASE)
+    return re.search(ai_pattern, text)
+
+def filter_strings(strings_list):
+    return [string for string in strings_list if contains_ai_or_artificial_intelligence(string)]
+
+def top_n_strings(strings_list, n):
+    filtered_strings = filter_strings(strings_list)
+    # 统计每个字符串的出现次数
+    counter = Counter(filtered_strings)
+    # 获取出现次数最多的前n个字符串
+    most_common = counter.most_common(n)
+    return most_common
+
+def dm_urls(url):
+    try:
+        response = requests.get(url, headers=headers)
+        response.raise_for_status()
+        soup = BeautifulSoup(response.text, 'html.parser')
+        urls = set()
+        for a_tag in soup.find_all('a', href=True):
+            href = a_tag['href']
+            urls.add(href)
+        pattern = re.compile(r'https://api\.bilibili\.com/x/v1/dm/list\.so\?oid=\d+')
+        # 过滤符合格式的URL
+        specific_urls = [url1 for url1 in urls if pattern.match(url1)]
+        return specific_urls
+    except:
+        return []  # 返回一个空列表作为默认值
+
+def extract_urls(url):
+    response = requests.get(url, headers=headers)
+    response.raise_for_status()
+    soup = BeautifulSoup(response.text, 'html.parser')
+    urls = set()
+    urlbilibili="https://"
+    for a_tag in soup.find_all('a', href=True):
+        href = a_tag['href']
+        # 将相对URL转换为绝对URL
+        full_url = urljoin(urlbilibili, href)
+        urls.add(full_url)
+    pattern = re.compile(r'^https://www\.bilibili\.com/video')
+    # 过滤符合格式的URL
+    specific_urls = [url1 for url1 in urls if pattern.match(url1)]
+    if (len(specific_urls) + vedio_sum > 300):
+        specific_urls = specific_urls[:6]  # 保留前六个元素
+    return specific_urls
+
+def vedio_transform_port(url):
+    response = requests.get(url, headers=headers)
+    response.raise_for_status()
+    soup = BeautifulSoup(response.text, 'html.parser')
+    page_num = []   #储存总共的分p数
+    span_tag = None #用做判断有无分p的flag
+    div_tags = soup.findAll("div",attrs={"class":"head-left"}) #找到class=head-left的div
+    for tag in div_tags:
+        span_tag = tag.findAll("span", attrs={"class": "cur-page"})  # 再从中找到class=cur-page的span
+    if not span_tag:  # 值为None则为单个视频
+        return 0
+    else:
+        for tag in span_tag:
+            pattern = re.compile(r'\((\d+)/(\d+)\)')
+            match = pattern.search(tag.text)  # 使用tag.text提取文本内容
+            if match:  # 确保找到匹配项
+                page_num = int(match.group(2))  # 获取总页数
+    return page_num
+
+list=[]
+
+for page_num in range(1,9):
+    urls = extract_urls(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_num}")
+    mod_urls=set()
+    vedio_sum +=len(urls)
+    for ori_url in urls:
+        clean_url = re.sub(r'\?.*$', '', ori_url)
+        p_sum=vedio_transform_port(ori_url)
+        if (p_sum == 0):
+            modified_url = clean_url.replace("bilibili.com", "ibilibili.com")
+            mod_urls.add(modified_url)
+        else:
+            for p_num in range(1, p_sum + 1):
+                ori2_url = f"{clean_url}?p={p_num}"
+                modified_url = ori2_url.replace("bilibili.com", "ibilibili.com")
+                mod_urls.add(modified_url)
+
+    for url in mod_urls:
+        dmurls=dm_urls(url)
+        if dmurls:  # 检查列表是否为空
+            dmurl = dmurls[0]
+            response = requests.get(dmurl, headers=headers)
+            response.encoding = 'utf-8'
+            html = response.text
+            soup = BeautifulSoup(html, "lxml-xml")
+            # 提取所有评论
+            comments = soup.find_all('d')
+            for comment in comments:
+                comment_text = comment.get_text()
+                list.append(comment_text)
+
+result = top_n_strings(list,len(list))
+# 创建 DataFrame
+df = pd.DataFrame(result, columns=['Element', 'Count'])
+# 写入 Excel 文件
+df.to_excel('output.xlsx', index=False)
+
+result8=top_n_strings(list,8)
+for item, count in result8:
+    print(f'{item}: {count}')
+
+df = pd.read_excel('output.xlsx')
+# 创建词云输入格式
+text = ' '.join(df.apply(lambda row: f"{row['Element']} " * row['Count'], axis=1))
+# 生成词云
+wordcloud = WordCloud(width=800, height=400, background_color='white',font_path=r'C:\Windows\Fonts\FZSTK.TTF').generate(text)
+wordcloud.to_file('wordcloud5.png')
+# 显示词云图
+plt.figure(figsize=(10, 5))
+plt.imshow(wordcloud, interpolation='bilinear')
+plt.axis('off')
+plt.show()