import os
import subprocess
import pandas as pd
from urllib.parse import urlparse
import signal
import sys
import datetime
from openpyxl import load_workbook

from mycode.base import BASE_DIR
from mycode.main import make_simple_csv_from_db, make_wechat_articles_full, ana_web, ana_wechat, output_dir
from mycode.crawl_chrome import chrome_main, failed_sites_file

python_exe = os.path.join(BASE_DIR, 'runtime/python.exe')
# scrapy_exe = os.path.join(BASE_DIR, 'runtime/Scripts/scrapy.exe')

def save_info_to_excel(info_list, output_filename):
    df = pd.DataFrame(info_list, columns=['单位', '主办' , '地址'])
    df.to_excel(output_filename, index=False)

# 定义 SIGINT 信号处理函数
def sigint_handler(signal, frame):
    print('收到 Ctrl-C 信号，正在关闭子进程...')
    for process in processes:
        process.terminate()
    print('子进程已关闭，程序退出。')
    sys.exit(0)

if __name__ == '__main__':
    print('巡查任务开始。。。')
    now = datetime.datetime.now()
    month = now.month

    print('正在组合微信公众号爬取内容。。。')
    make_simple_csv_from_db()
    make_wechat_articles_full()
    print('公众号爬取内容组装完毕!')

    print('开始进行网站爬取。。。')

    df = pd.read_excel('web_sites.xlsx', sheet_name='Sheet1')
    processes = []

    # 注册 SIGINT 信号处理函数
    signal.signal(signal.SIGINT, sigint_handler)

    ind = 0
    for ind, row in df.iterrows():
            group = row['单位']
            name = row['主办']
            url = row['地址']
            domain = urlparse(url).netloc.replace('www.', '')
            # output =  os.path.join(BASE_DIR, f'web_dir/{name}_{domain}.xlsx') 
            cmd = [python_exe, '-m', 'scrapy', 'crawl', 'basespider', '-a', f'domain={domain}', '-a', f'start_url={url}', '-a', f'name={name}', '-a', f'group={group}', '-o', f'web_dir/{name}_{domain}.xlsx']
            # cmd = ['scrapy', 'crawl', 'basespider', '-a', f'domain={domain}', '-a', f'start_url={url}', '-a', f'name={name}', '-a', f'group={group}', '-a', f'output={output}']
            process = subprocess.Popen(cmd)
            processes.append(process)

    # Wait for all processes to finish
    for process in processes:
        process.wait()

    print('网站爬取结束,校验中。。。')
    # Check output file sizes and save information if size is less than 20KB
    info_to_save = []
    for ind, row in df.iterrows():
        group = row['单位']
        name = row['主办']
        url = row['地址']
        domain = urlparse(url).netloc.replace("www.", "")
        output_filename = os.path.join(BASE_DIR, f'web_dir/{name}_{domain}.xlsx')
        if os.path.exists(output_filename):
            file_size = os.path.getsize(output_filename)
            if file_size < 20 * 1024:  # Convert KB to bytes
                info_to_save.append([group, name, url])

    if info_to_save:
        print('存在未爬取站点,正在调用Chrome继续爬取。。。')
        save_info_to_excel(info_to_save, failed_sites_file)
        chrome_main()
        os.remove(failed_sites_file)

    print('网站爬取完毕!')

    print('开始对比分析所有内容。。。')
    # Run WeChat Analysis
    wechat_results = ana_wechat()
    # Run Web Content Analysis
    web_results = ana_web()

    # Save results in an Excel file with two sheets
    output_excel_path = os.path.join(output_dir, f'{month}月-总院及下属公司官方公众号巡查结果汇总表.xlsx')
    # with pd.ExcelWriter(output_excel_path) as writer:
    #     df = pd.DataFrame(wechat_results, columns=['序号', '信源名称', '文章标题', '错误表述', '建议修改词语', '错误分类', '原文链接'])
    #     df.to_excel(writer, sheet_name='公众号', index=False)
    #     df2 = pd.DataFrame(web_results, columns=['序号', '信源名称', '文章标题', '错误表述', '建议修改词语', '错误分类', '原文链接'])
    #     df2.to_excel(writer, sheet_name='网站', index=False)
    template_path = os.path.join(output_dir, 'template.xlsx')
    workbook = load_workbook(template_path)

    # 选择要操作的工作表
    wechat_sheet = workbook['公众号']
    web_sheet = workbook['网站']
    for row in wechat_results:
        wechat_sheet.append(row)
    for row in web_results:
        web_sheet.append(row)
    workbook.save(output_excel_path)
    workbook.close()
    print('巡查任务执行完毕, 请查看summary文件夹, 可手动校对')
    os.system("pause")