# -*- coding: utf-8 -*-
# 获取server运行情况
# import json
# from datetime import datetime
#
# import paramiko
# import xlwt, xlrd
# from xlutils.copy import copy
#
# def get_host_cpu_memory():
# client = paramiko.SSHClient()
# client.set_missing_host_key_policy(paramiko.AutoAddPolicy())
# print('------------开始连接服务器-----------')
# client.connect('192.168.0.102', 22, username='hui', password='199317', timeout=4)
# print('------------认证成功!.....-----------')
#
# sheet_name = 'host-' + datetime.now().strftime('%Y-%m-%d-%H-%M-%S')
# # print('本次生成的表名为{}'.format(sheet_name))
# # 结果写入excel中
# book = xlwt.Workbook()
# sheet = book.add_sheet(sheetname='{}'.format(sheet_name))
# sheet_title = ['id', 'cpu_info', 'cpu_average', 'memory_info', 'memory_average']
# for i in range(0, len(sheet_title)):
# sheet.write(0, i, sheet_title[i])
# book.save('{}.xls'.format(sheet_name))
#
# # 远程环境中一定要导包。循环去获取server情况。不在这里控制频率
# cpu_average = 0
# memory_average = 0
# id = 1
# while True:
# stdin, stdout, stderr = client.exec_command('cd Desktop/code/25_processings; python host_script.py')
# content = stdout.read().decode('utf-8').split('\n')[:2:]
# # print(content)
# # print(len(content))
# # print(type(content))
#
# cpu_info = json.loads(content[0])
# memory_info = float(content[1])
#
# # cpu平均使用率
# cpu_info = sum(cpu_info) / len(cpu_info)
# cpu_average = cpu_info if cpu_average == 0 else (cpu_average + cpu_info) / 2
# cpu_average = round(cpu_average, 4)
#
# # memory平均使用率
# memory_average = memory_info if memory_average == 0 else (memory_average + memory_info) / 2
# memory_average = round(memory_average, 4)
#
# # 数据加入表中
# # ret_data = [cpu_average, memory_average]
# # print(ret_data)
# data = xlrd.open_workbook('{}.xls'.format(sheet_name), formatting_info=True)
# excel = copy(wb=data) # 完成xlrd对象向xlwt对象转换
# excel_table = excel.get_sheet(0) # 获得要操作的页
# table = data.sheets()[0]
# nrows = table.nrows # 获得行数
# ret_list = ['%.4f' % i for i in [cpu_info, cpu_average, memory_info, memory_average]]
# # print(ret_list)
#
#
# excel_table.write(nrows, 0, id)
# excel_table.write(nrows, 1, ret_list[0])
# excel_table.write(nrows, 2, ret_list[1])
# excel_table.write(nrows, 3, ret_list[2])
# excel_table.write(nrows, 4, ret_list[3])
# excel.save('{}.xls'.format(sheet_name))
# id += 1
#
# get_host_cpu_memory()
# 获取系统数据
# import psutil
# def get_sys_info():
# cpu_percent = psutil.cpu_percent(percpu=True, interval=5)
# rel_memory = psutil.virtual_memory()
# print(cpu_percent)
# print(rel_memory[2])
#
# if __name__ == '__main__':
# get_sys_info()
# 主要的code，多进程任务
# import time
# from multiprocessing import Process
#
#
#
# start_time = time.time()
#
#
# def get_host_info():
# while True:
# time.sleep(0.3)
# print('processing---1')
#
# def get_ctr_info():
# while True:
# time.sleep(0.3)
# print('processing---2')
#
# def get_train_info():
# print('开始计算，用时10秒')
# while time.time() - start_time < 10:
# time.sleep(0.3)
# print('计算')
# print('结束计算，用时10秒')
#
#
# def main():
# host_info = Process(target=get_host_info)
# ctr_info = Process(target=get_ctr_info)
# train_info = Process(target=get_train_info)
#
# host_info.start()
# ctr_info.start()
# train_info.start()
#
# # 等待大规模计算完成
# train_info.join()
#
# # 结束系统数据统计
# host_info.terminate()
# ctr_info.terminate()
#
# if __name__ == '__main__':
# main()
