如何使用Python腳本為站群實現蜘蛛統計和創建獨立分析頁面？

import sys import pandas as pd  logfile = sys.argv[1] if len(sys.argv) > 1 else "Access.log"  # 讀取日志文件 try:     with open(logfile, 'r', encoding='utf-8') as f:  # 添加編碼處理，避免亂碼         log_data = f.readlines() except FileNotFoundError:     print(f"Error: Log file '{logfile}' not found.")     sys.exit(1)  # 解析日志數據 (根據你的日志格式調整) log_entries = [] for line in log_data:     try:         parts = line.split()         if len(parts) > 10:             log_entries.append({                 "ip": parts[0],                 "date": parts[3][1:],                 "request": parts[6], # 調整字段索引以匹配你的日志格式                 "status": parts[8],                 "agent": " ".join(parts[11:]) # 調整字段索引以匹配你的日志格式             })     except IndexError:         print(f"Warning: Skipping malformed log line: {line.strip()}")  df = pd.DataFrame(log_entries)  # 定義蜘蛛 User-Agent spider_agents = [     "googlebot",     "bingbot",     "baiduspider",     "yandexbot",     "sogou",     # 添加其他蜘蛛 User-Agent ]  # 篩選蜘蛛請求 df['spider'] = df['agent'].str.extract(f"({'|'.join(spider_agents)})", expand=False) spider_df = df[df['spider'].notna()]  # 按蜘蛛類型和日期匯總統計 spider_summary = spider_df.groupby(['spider', 'date']).size().reset_index(name='count')  print(spider_summary)  # 可選：保存數據到 CSV 文件 spider_summary.to_csv('spider_stats.csv', index=False)

python3 spider_stats.py access.log

from flask import Flask, render_template, JSonify import pandas as pd  app = Flask(__name__)  @app.route('/') def index():     try:         df = pd.read_csv('spider_stats.csv')         data = df.to_dict(orient='records')         return render_template('index.html', data=data)     except FileNotFoundError:         return "Error: spider_stats.csv not found."   if __name__ == '__main__':     app.run(debug=True) # debug模式方便開發，上線時需關閉