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# -*- coding: utf-8 -*-
"""
Created on Tue Jun 5 16:12:56 2018
@author: Administrator
"""
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 19 16:41:49 2018
@author: Administrator
"""
import sched # 导入定时任务库
import time # 导入time模块
from datetime import datetime
from datetime import timedelta
from cmd import Cmd
import os
import pandas as pd
import random
sche=sched.scheduler(time.time,time.sleep) # 实例化sched.scheduler类
# =============================================================================
# 设置环境变量
# =============================================================================
data_path = 'd:\_4G基站断站'+'\\'
log_path = 'd:\_4G基站断站\logfiles'+'\\'
out_path = 'd_4G基站断站'+'\\'
bts = 'bts_list.xlsx'
df_bts = pd.read_excel(data_path + bts , encoding='utf-8') # 打开基站名称表
# =============================================================================
# 通过cmd ping测试基站
# =============================================================================
def task():
sche.enter(1800,1,task) # 调用sche实例的enter方法创建一个定时任务,1800秒之后执行,任务内容执行task()函数
current_time = str(datetime.now()).split('.')[0]
print('task start time:',current_time) # print任务开始时间
current_time = str(datetime.now()).split('.')[0]
current_time = current_time.replace(':','-')
with open(log_path + current_time + '.txt','w',encoding = 'utf8') as f:
for i in range(0,len(df_bts)):
ip = df_bts.loc[i,'IP']
BTS = df_bts.loc[i,'name']
eNodeB = df_bts.loc[i,'eNodeB']
command_line = 'ping'+ ' ' + ip + ' '+ '-n 1' # 生成ping命令列表
res = os.popen(command_line).readlines()
del(res[3])
current_time = str(datetime.now()).split('.')[0]
info = str(BTS) + ' ' + str(eNodeB) +' ' + str(ip) +' '+ 'Time:' + ' ' +current_time
f.write(info)
for line in res:
f.write(line)
f.write('\n')
current_time = str(datetime.now()).split('.')[0]
print('task end time:',current_time)
# =============================================================================
# 汇总处理ping测试数据
# =============================================================================
def get_time_info(record_file):
time_array = record_file[:-9]
time_info = time_array.replace('.',':')
return time_info
all_files = os.listdir(log_path)
file_list = []
df_break = pd.DataFrame(columns=('eNodeB','基站名称','网管名称','IP','状态','断站时间','持续时长(分)','恢复时间','数据更新时间'))
df_total = pd.DataFrame(columns=('IP','状态','数据更新时间'))
today = datetime.today()
yestoday = today - timedelta(days=1)
today = str(today).split(' ')[0]
yestoday = str(yestoday).split(' ')[0]
for file in all_files:
if get_time_info(file).split(' ')[0] == today or get_time_info(file).split(' ')[0] == yestoday:
file_list.append(file)
if len(file_list) > 0: # 如果取到的文件列表不为空,则开始处理文件
df_state=pd.DataFrame(columns=('eNodeB','基站名称','状态','更新时间')) # 新建表格用于存放基站状态汇总数据
df_result=pd.DataFrame(columns=('eNodeB','基站名称','状态','发生时间','持续时间(分钟)','恢复时间','数据更新时间')) #创建表格用于存放断站数据
for file_name in file_list:
with open(log_path + file_name,'r',encoding='utf-8') as file_tmp: # 用零时文件读取原始记录文件
content = file_tmp.readlines()
df_state_tmp=pd.DataFrame(columns=('eNodeB','基站名称','状态','更新时间')) # 新建零时表格用于存放打开的原始记录
for i in range(0,len(content)-2,1) :
if 'Time' in content[i]:
bts_name = content[i].split(' ')[0]
eNodeB = content[i].split(' ')[1]
updata_time = content[i].split(' ')[4] + ' ' + content[i].split(' ')[5]
state = content[i+2].split(' ')[0]
df_state_tmp.loc[i,'eNodeB']= eNodeB # 将原始记录写入df_state_tmp
df_state_tmp.loc[i,'基站名称']= bts_name # 将原始记录写入df_state_tmp
df_state_tmp.loc[i,'状态']= state
df_state_tmp.loc[i,'更新时间']= updata_time.strip ()
df_state=df_state.append(df_state_tmp,ignore_index=True) # 将 df_state_tmp加入到汇总表格 df_state
df_state = df_state.reset_index()
df_state=df_state.drop('index',axis=1)
df_state['状态']=df_state['状态'].map(lambda x:x.replace('Request','断站'))
df_state['状态']=df_state['状态'].map(lambda x:x.replace('Reply','正常'))
df_state['eNodeB']=df_state['eNodeB'].astype(int)
df_state = df_state.sort_values(by='更新时间',ascending = True) # 按时间顺序升序排列
df_state = df_state.reset_index()
del df_state['index']
df_break = df_state[df_state['状态'] == '断站'] #筛选出所有发生郭断站的基站
break_set=set(list(df_break['eNodeB'])) # 断站基站去重复
break_bts = list(break_set) # 得到去重后的断站list
for i in range(0,len(break_bts),1):
df_tmp = df_state[df_state['eNodeB'] == break_bts[i]] # 逐个筛选出发生过断站的基站,包含已恢复的
df_tmp = df_tmp.reset_index()
break_list = []
resume_list = []
start_time = df_tmp.loc[0,'更新时间'] # 取第一条记录时间为start_time
end_time = df_tmp.loc[len(df_tmp)-1,'更新时间'] # 取最后一条记录时间为end_time
if '正常' not in list(df_tmp['状态']): # 如果状态全是断站,则断站开始时间为第一条记录时间
break_list.append(start_time)
elif df_tmp.loc[0,'状态'] =='断站': # 如果第一条就是断站,则使用后面的前后关联方法无法提取出来,所以单独提取断站时间
break_list.append(start_time)
for j in range(0,len(df_tmp)-1,1):
if df_tmp.loc[j,'状态'] == '断站' and df_tmp.loc[j+1,'状态'] == '正常': # 如果断站后面有一行正常状态则表示故障恢复
resume_list.append(df_tmp.loc[j+1,'更新时间'])
elif df_tmp.loc[j,'状态'] == '正常' and df_tmp.loc[j+1,'状态'] == '断站': # 如果‘正常’后面有一行‘断站’则表示发生断站
break_list.append(df_tmp.loc[j+1,'更新时间'])
if len(resume_list) == 0 and len(break_list) > 0: # 表示发生过断站但一直没恢复,无需处理
pass
elif len(break_list) > 0 and len(resume_list) > 0:
if time.strptime(resume_list[0],'%Y-%m-%d %H:%M:%S') < time.strptime(break_list[0],'%Y-%m-%d %H:%M:%S'):
break_list.insert(0, start_time) # 如果恢复时间比断站时间还早则说明在更早的时候还有一次断站,断站时间为 start_time
df_result_tmp = pd.DataFrame(columns=('eNodeB','基站名称','状态','发生时间','持续时间(分钟)','恢复时间','数据更新时间')) #创建表格用于存放断站数据
for k in range(0,len(break_list),1):
df_result_tmp.loc[k,'eNodeB']= df_tmp.loc[0,'eNodeB']
df_result_tmp.loc[k,'基站名称']= df_tmp.loc[0,'基站名称']
df_result_tmp.loc[k,'状态']='断站'
df_result_tmp.loc[k,'发生时间']= break_list[k]
df_result_tmp.loc[k,'数据更新时间']= end_time
if len(resume_list) > k:
df_result_tmp.loc[k,'恢复时间']= resume_list[k]
df_result_tmp = df_result_tmp.fillna('-')
if df_result_tmp.loc[k,'恢复时间'] != '-' :
df_result_tmp.loc[k,'持续时间(分钟)']= (time.mktime(time.strptime(df_result_tmp.loc[k,'恢复时间'],'%Y-%m-%d %H:%M:%S')) - time.mktime(time.strptime(df_result_tmp.loc[k,'发生时间'],'%Y-%m-%d %H:%M:%S')))/60 # 计算基站中断持续的时间
else:
df_result_tmp.loc[k,'持续时间(分钟)']= (time.mktime(time.strptime(end_time,'%Y-%m-%d %H:%M:%S')) - time.mktime(time.strptime(df_result_tmp.loc[k,'发生时间'],'%Y-%m-%d %H:%M:%S')))/60 # 计算基站中断持续的时间
df_result = df_result.append(df_result_tmp,ignore_index=True)
current_time = str(datetime.now()).split('.')[0]
print('report finished:',current_time)
print('---------------------------------')
current_time = current_time.replace(':','.')
with pd.ExcelWriter(data_path + current_time + '_4G基站断站.xls') as writer :
df_result.to_excel(writer,current_time + '_断站')
# =============================================================================
# 延时10秒后启动任务
# =============================================================================
sche.enter(12,1,task) # 调用sche实力的enter方法创建一个定时任务,12秒之后执行,任务内容执行task()函数
print('task will run in 10 second') # 提示信息 10秒计时
for i in range(1,11,1):
print('----->',i)
time.sleep(1)
sche.run()
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